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My home-made bar replay for MT4

I made a home-made bar replay for MT4 as an alternative to the tradingview bar replay. You can change timeframes and use objects easily. It just uses vertical lines to block the future candles. Then it adjusts the vertical lines when you change zoom or time frames to keep the "future" bars hidden.
I am not a professional coder so this is not as robust as something like Soft4fx or Forex Tester. But for me it gets the job done and is very convenient. Maybe you will find some benefit from it.

Here are the steps to use it:
1) copy the text from the code block
2) go to MT4 terminal and open Meta Editor (click icon or press F4)
3) go to File -> New -> Expert Advisor
4) put in a title and click Next, Next, Finish
5) Delete all text from new file and paste in text from code block
6) go back to MT4
7) Bring up Navigator (Ctrl+N if it's not already up)
8) go to expert advisors section and find what you titled it
9) open up a chart of the symbol you want to test
10) add the EA to this chart
11) specify colors and start time in inputs then press OK
12) use "S" key on your keyboard to advance 1 bar of current time frame
13) use tool bar buttons to change zoom and time frames, do objects, etc.
14) don't turn on auto scroll. if you do by accident, press "S" to return to simulation time.
15) click "buy" and "sell" buttons (white text, top center) to generate entry, TP and SL lines to track your trade
16) to cancel or close a trade, press "close order" then click the white entry line
17) drag and drop TP/SL lines to modify RR
18) click "End" to delete all objects and remove simulation from chart
19) to change simulation time, click "End", then add the simulator EA to your chart with a new start time
20) When you click "End", your own objects will be deleted too, so make sure you are done with them
21) keep track of your own trade results manually
22) use Tools-> History center to download new data if you need it. the simulator won't work on time frames if you don't have historical data going back that far, but it will work on time frames that you have the data for. If you have data but its not appearing, you might also need to increase max bars in chart in Tools->Options->Charts.
23) don't look at status bar if you are moused over hidden candles, or to avoid this you can hide the status bar.


Here is the code block.
//+------------------------------------------------------------------+ //| Bar Replay V2.mq4 | //| Copyright 2020, MetaQuotes Software Corp. | //| https://www.mql5.com | //+------------------------------------------------------------------+ #property copyright "Copyright 2020, MetaQuotes Software Corp." #property link "https://www.mql5.com" #property version "1.00" #property strict #define VK_A 0x41 #define VK_S 0x53 #define VK_X 0x58 #define VK_Z 0x5A #define VK_V 0x56 #define VK_C 0x43 #define VK_W 0x57 #define VK_E 0x45 double balance; string balance_as_string; int filehandle; int trade_ticket = 1; string objectname; string entry_line_name; string tp_line_name; string sl_line_name; string one_R_line_name; double distance; double entry_price; double tp_price; double sl_price; double one_R; double TP_distance; double gain_in_R; string direction; bool balance_file_exist; double new_balance; double sl_distance; string trade_number; double risk; double reward; string RR_string; int is_tp_or_sl_line=0; int click_to_cancel=0; input color foreground_color = clrWhite; input color background_color = clrBlack; input color bear_candle_color = clrRed; input color bull_candle_color = clrSpringGreen; input color current_price_line_color = clrGray; input string start_time = "2020.10.27 12:00"; input int vertical_margin = 100; //+------------------------------------------------------------------+ //| Expert initialization function | //+------------------------------------------------------------------+ int OnInit() { Comment(""); ChartNavigate(0,CHART_BEGIN,0); BlankChart(); ChartSetInteger(0,CHART_SHIFT,true); ChartSetInteger(0,CHART_FOREGROUND,false); ChartSetInteger(0,CHART_AUTOSCROLL,false); ChartSetInteger(0,CHART_SCALEFIX,false); ChartSetInteger(0,CHART_SHOW_OBJECT_DESCR,true); if (ObjectFind(0,"First OnInit")<0){ CreateStorageHLine("First OnInit",1);} if (ObjectFind(0,"Simulation Time")<0){ CreateTestVLine("Simulation Time",StringToTime(start_time));} string vlinename; for (int i=0; i<=1000000; i++){ vlinename="VLine"+IntegerToString(i); ObjectDelete(vlinename); } HideBars(SimulationBarTime(),0); //HideBar(SimulationBarTime()); UnBlankChart(); LabelCreate("New Buy Button","Buy",0,38,foreground_color); LabelCreate("New Sell Button","Sell",0,41,foreground_color); LabelCreate("Cancel Order","Close Order",0,44,foreground_color); LabelCreate("Risk To Reward","RR",0,52,foreground_color); LabelCreate("End","End",0,35,foreground_color); ObjectMove(0,"First OnInit",0,0,0); //--- create timer EventSetTimer(60); return(INIT_SUCCEEDED); } //+------------------------------------------------------------------+ //| Expert deinitialization function | //+------------------------------------------------------------------+ void OnDeinit(const int reason) { //--- destroy timer EventKillTimer(); } //+------------------------------------------------------------------+ //| Expert tick function | //+------------------------------------------------------------------+ void OnTick() { //--- } //+------------------------------------------------------------------+ //| ChartEvent function | //+------------------------------------------------------------------+ void OnChartEvent(const int id, const long &lparam, const double &dparam, const string &sparam) { if (id==CHARTEVENT_CHART_CHANGE){ int chartscale = ChartGetInteger(0,CHART_SCALE,0); int lastchartscale = ObjectGetDouble(0,"Last Chart Scale",OBJPROP_PRICE,0); if (chartscale!=lastchartscale){ int chartscale = ChartGetInteger(0,CHART_SCALE,0); ObjectMove(0,"Last Chart Scale",0,0,chartscale); OnInit(); }} if (id==CHARTEVENT_KEYDOWN){ if (lparam==VK_S){ IncreaseSimulationTime(); UnHideBar(SimulationPosition()); NavigateToSimulationPosition(); CreateHLine(0,"Current Price",Close[SimulationPosition()+1],current_price_line_color,1,0,true,false,false,"price"); SetChartMinMax(); }} if(id==CHARTEVENT_OBJECT_CLICK) { if(sparam=="New Sell Button") { distance = iATR(_Symbol,_Period,20,SimulationPosition()+1)/2; objectname = "Trade # "+IntegerToString(trade_ticket); CreateHLine(0,objectname,Close[SimulationPosition()+1],foreground_color,2,5,false,true,true,"Sell"); objectname = "TP for Trade # "+IntegerToString(trade_ticket); CreateHLine(0,objectname,Close[SimulationPosition()+1]-distance*2,clrAqua,2,5,false,true,true,"TP"); objectname = "SL for Trade # "+IntegerToString(trade_ticket); CreateHLine(0,objectname,Close[SimulationPosition()+1]+distance,clrRed,2,5,false,true,true,"SL"); trade_ticket+=1; } } if(id==CHARTEVENT_OBJECT_CLICK) { if(sparam=="New Buy Button") { distance = iATR(_Symbol,_Period,20,SimulationPosition()+1)/2; objectname = "Trade # "+IntegerToString(trade_ticket); CreateHLine(0,objectname,Close[SimulationPosition()+1],foreground_color,2,5,false,true,true,"Buy"); objectname = "TP for Trade # "+IntegerToString(trade_ticket); CreateHLine(0,objectname,Close[SimulationPosition()+1]+distance*2,clrAqua,2,5,false,true,true,"TP"); objectname = "SL for Trade # "+IntegerToString(trade_ticket); CreateHLine(0,objectname,Close[SimulationPosition()+1]-distance,clrRed,2,5,false,true,true,"SL"); trade_ticket+=1; } } if(id==CHARTEVENT_OBJECT_DRAG) { if(StringFind(sparam,"TP",0)==0) { is_tp_or_sl_line=1; } if(StringFind(sparam,"SL",0)==0) { is_tp_or_sl_line=1; } Comment(is_tp_or_sl_line); if(is_tp_or_sl_line==1) { trade_number = StringSubstr(sparam,7,9); entry_line_name = trade_number; tp_line_name = "TP for "+entry_line_name; sl_line_name = "SL for "+entry_line_name; entry_price = ObjectGetDouble(0,entry_line_name,OBJPROP_PRICE,0); tp_price = ObjectGetDouble(0,tp_line_name,OBJPROP_PRICE,0); sl_price = ObjectGetDouble(0,sl_line_name,OBJPROP_PRICE,0); sl_distance = MathAbs(entry_price-sl_price); TP_distance = MathAbs(entry_price-tp_price); reward = TP_distance/sl_distance; RR_string = "RR = 1 : "+DoubleToString(reward,2); ObjectSetString(0,"Risk To Reward",OBJPROP_TEXT,RR_string); is_tp_or_sl_line=0; } } if(id==CHARTEVENT_OBJECT_CLICK) { if(sparam=="Cancel Order") { click_to_cancel=1; Comment("please click the entry line of the order you wish to cancel."); } } if(id==CHARTEVENT_OBJECT_CLICK) { if(sparam!="Cancel Order") { if(click_to_cancel==1) { if(ObjectGetInteger(0,sparam,OBJPROP_TYPE,0)==OBJ_HLINE) { entry_line_name = sparam; tp_line_name = "TP for "+sparam; sl_line_name = "SL for "+sparam; ObjectDelete(0,entry_line_name); ObjectDelete(0,tp_line_name); ObjectDelete(0,sl_line_name); click_to_cancel=0; ObjectSetString(0,"Risk To Reward",OBJPROP_TEXT,"RR"); } } } } if (id==CHARTEVENT_OBJECT_CLICK){ if (sparam=="End"){ ObjectsDeleteAll(0,-1,-1); ExpertRemove(); }} } //+------------------------------------------------------------------+ void CreateStorageHLine(string name, double value){ ObjectDelete(name); ObjectCreate(0,name,OBJ_HLINE,0,0,value); ObjectSetInteger(0,name,OBJPROP_SELECTED,false); ObjectSetInteger(0,name,OBJPROP_SELECTABLE,false); ObjectSetInteger(0,name,OBJPROP_COLOR,clrNONE); ObjectSetInteger(0,name,OBJPROP_BACK,true); ObjectSetInteger(0,name,OBJPROP_ZORDER,0); } void CreateTestHLine(string name, double value){ ObjectDelete(name); ObjectCreate(0,name,OBJ_HLINE,0,0,value); ObjectSetInteger(0,name,OBJPROP_SELECTED,false); ObjectSetInteger(0,name,OBJPROP_SELECTABLE,false); ObjectSetInteger(0,name,OBJPROP_COLOR,clrWhite); ObjectSetInteger(0,name,OBJPROP_BACK,true); ObjectSetInteger(0,name,OBJPROP_ZORDER,0); } bool IsFirstOnInit(){ bool bbb=false; if (ObjectGetDouble(0,"First OnInit",OBJPROP_PRICE,0)==1){return true;} return bbb; } void CreateTestVLine(string name, datetime timevalue){ ObjectDelete(name); ObjectCreate(0,name,OBJ_VLINE,0,timevalue,0); ObjectSetInteger(0,name,OBJPROP_SELECTED,false); ObjectSetInteger(0,name,OBJPROP_SELECTABLE,false); ObjectSetInteger(0,name,OBJPROP_COLOR,clrNONE); ObjectSetInteger(0,name,OBJPROP_BACK,false); ObjectSetInteger(0,name,OBJPROP_ZORDER,3); } datetime SimulationTime(){ return ObjectGetInteger(0,"Simulation Time",OBJPROP_TIME,0); } int SimulationPosition(){ return iBarShift(_Symbol,_Period,SimulationTime(),false); } datetime SimulationBarTime(){ return Time[SimulationPosition()]; } void IncreaseSimulationTime(){ ObjectMove(0,"Simulation Time",0,Time[SimulationPosition()-1],0); } void NavigateToSimulationPosition(){ ChartNavigate(0,CHART_END,-1*SimulationPosition()+15); } void NotifyNotEnoughHistoricalData(){ BlankChart(); Comment("Sorry, but there is not enough historical data to load this time frame."+"\n"+ "Please load more historical data or use a higher time frame. Thank you :)");} void UnHideBar(int barindex){ ObjectDelete(0,"VLine"+IntegerToString(barindex+1)); } void BlankChart(){ ChartSetInteger(0,CHART_COLOR_FOREGROUND,clrNONE); ChartSetInteger(0,CHART_COLOR_CANDLE_BEAR,clrNONE); ChartSetInteger(0,CHART_COLOR_CANDLE_BULL,clrNONE); ChartSetInteger(0,CHART_COLOR_CHART_DOWN,clrNONE); ChartSetInteger(0,CHART_COLOR_CHART_UP,clrNONE); ChartSetInteger(0,CHART_COLOR_CHART_LINE,clrNONE); ChartSetInteger(0,CHART_COLOR_GRID,clrNONE); ChartSetInteger(0,CHART_COLOR_ASK,clrNONE); ChartSetInteger(0,CHART_COLOR_BID,clrNONE);} void UnBlankChart(){ ChartSetInteger(0,CHART_COLOR_FOREGROUND,foreground_color); ChartSetInteger(0,CHART_COLOR_CANDLE_BEAR,bear_candle_color); ChartSetInteger(0,CHART_COLOR_CANDLE_BULL,bull_candle_color); ChartSetInteger(0,CHART_COLOR_BACKGROUND,background_color); ChartSetInteger(0,CHART_COLOR_CHART_DOWN,foreground_color); ChartSetInteger(0,CHART_COLOR_CHART_UP,foreground_color); ChartSetInteger(0,CHART_COLOR_CHART_LINE,foreground_color); ChartSetInteger(0,CHART_COLOR_GRID,clrNONE); ChartSetInteger(0,CHART_COLOR_ASK,clrNONE); ChartSetInteger(0,CHART_COLOR_BID,clrNONE);} void HideBars(datetime starttime, int shift){ int startbarindex = iBarShift(_Symbol,_Period,starttime,false); ChartNavigate(0,CHART_BEGIN,0); if (Time[WindowFirstVisibleBar()]>SimulationTime()){NotifyNotEnoughHistoricalData();} if (Time[WindowFirstVisibleBar()]=0; i--){ vlinename="VLine"+IntegerToString(i); ObjectCreate(0,vlinename,OBJ_VLINE,0,Time[i],0); ObjectSetInteger(0,vlinename,OBJPROP_COLOR,background_color); ObjectSetInteger(0,vlinename,OBJPROP_BACK,false); ObjectSetInteger(0,vlinename,OBJPROP_WIDTH,vlinewidth); ObjectSetInteger(0,vlinename,OBJPROP_ZORDER,10); ObjectSetInteger(0,vlinename,OBJPROP_FILL,true); ObjectSetInteger(0,vlinename,OBJPROP_STYLE,STYLE_SOLID); ObjectSetInteger(0,vlinename,OBJPROP_SELECTED,false); ObjectSetInteger(0,vlinename,OBJPROP_SELECTABLE,false); } NavigateToSimulationPosition(); SetChartMinMax();} }//end of HideBars function void SetChartMinMax(){ int firstbar = WindowFirstVisibleBar(); int lastbar = SimulationPosition(); int lastbarwhenscrolled = WindowFirstVisibleBar()-WindowBarsPerChart(); if (lastbarwhenscrolled>lastbar){lastbar=lastbarwhenscrolled;} double highest = High[iHighest(_Symbol,_Period,MODE_HIGH,firstbar-lastbar,lastbar)]; double lowest = Low[iLowest(_Symbol,_Period,MODE_LOW,firstbar-lastbar,lastbar)]; ChartSetInteger(0,CHART_SCALEFIX,true); ChartSetDouble(0,CHART_FIXED_MAX,highest+vertical_margin*_Point); ChartSetDouble(0,CHART_FIXED_MIN,lowest-vertical_margin*_Point); } void LabelCreate(string labelname, string labeltext, int row, int column, color labelcolor){ int ylocation = row*18; int xlocation = column*10; ObjectCreate(0,labelname,OBJ_LABEL,0,0,0); ObjectSetString(0,labelname,OBJPROP_TEXT,labeltext); ObjectSetInteger(0,labelname,OBJPROP_COLOR,labelcolor); ObjectSetInteger(0,labelname,OBJPROP_FONTSIZE,10); ObjectSetInteger(0,labelname,OBJPROP_ZORDER,10); ObjectSetInteger(0,labelname,OBJPROP_BACK,false); ObjectSetInteger(0,labelname,OBJPROP_CORNER,CORNER_LEFT_UPPER); ObjectSetInteger(0,labelname,OBJPROP_ANCHOR,ANCHOR_LEFT_UPPER); ObjectSetInteger(0,labelname,OBJPROP_XDISTANCE,xlocation); ObjectSetInteger(0,labelname,OBJPROP_YDISTANCE,ylocation);} double GetHLinePrice(string name){ return ObjectGetDouble(0,name,OBJPROP_PRICE,0); } void CreateHLine(int chartid, string objectnamey, double objectprice, color linecolor, int width, int zorder, bool back, bool selected, bool selectable, string descriptionn) { ObjectDelete(chartid,objectnamey); ObjectCreate(chartid,objectnamey,OBJ_HLINE,0,0,objectprice); ObjectSetString(chartid,objectnamey,OBJPROP_TEXT,objectprice); ObjectSetInteger(chartid,objectnamey,OBJPROP_COLOR,linecolor); ObjectSetInteger(chartid,objectnamey,OBJPROP_WIDTH,width); ObjectSetInteger(chartid,objectnamey,OBJPROP_ZORDER,zorder); ObjectSetInteger(chartid,objectnamey,OBJPROP_BACK,back); ObjectSetInteger(chartid,objectnamey,OBJPROP_SELECTED,selected); ObjectSetInteger(chartid,objectnamey,OBJPROP_SELECTABLE,selectable); ObjectSetString(0,objectnamey,OBJPROP_TEXT,descriptionn); } //end of code 
submitted by Learning_2 to Forex [link] [comments]

Former investment bank FX trader: Risk management part 3/3

Former investment bank FX trader: Risk management part 3/3
Welcome to the third and final part of this chapter.
Thank you all for the 100s of comments and upvotes - maybe this post will take us above 1,000 for this topic!
Keep any feedback or questions coming in the replies below.
Before you read this note, please start with Part I and then Part II so it hangs together and makes sense.
Part III
  • Squeezes and other risks
  • Market positioning
  • Bet correlation
  • Crap trades, timeouts and monthly limits

Squeezes and other risks

We are going to cover three common risks that traders face: events; squeezes, asymmetric bets.

Events

Economic releases can cause large short-term volatility. The most famous is Non Farm Payrolls, which is the most widely watched measure of US employment levels and affects the price of many instruments.On an NFP announcement currencies like EURUSD might jump (or drop) 100 pips no problem.
This is fine and there are trading strategies that one may employ around this but the key thing is to be aware of these releases.You can find economic calendars all over the internet - including on this site - and you need only check if there are any major releases each day or week.
For example, if you are trading off some intraday chart and scalping a few pips here and there it would be highly sensible to go into a known data release flat as it is pure coin-toss and not the reason for your trading. It only takes five minutes each day to plan for the day ahead so do not get caught out by this. Many retail traders get stopped out on such events when price volatility is at its peak.

Squeezes

Short squeezes bring a lot of danger and perhaps some opportunity.
The story of VW and Porsche is the best short squeeze ever. Throughout these articles we've used FX examples wherever possible but in this one instance the concept (which is also highly relevant in FX) is best illustrated with an historical lesson from a different asset class.
A short squeeze is when a participant ends up in a short position they are forced to cover. Especially when the rest of the market knows that this participant can be bullied into stopping out at terrible levels, provided the market can briefly drive the price into their pain zone.

There's a reason for the car, don't worry
Hedge funds had been shorting VW stock. However the amount of VW stock available to buy in the open market was actually quite limited. The local government owned a chunk and Porsche itself had bought and locked away around 30%. Neither of these would sell to the hedge-funds so a good amount of the stock was un-buyable at any price.
If you sell or short a stock you must be prepared to buy it back to go flat at some point.
To cut a long story short, Porsche bought a lot of call options on VW stock. These options gave them the right to purchase VW stock from banks at slightly above market price.
Eventually the banks who had sold these options realised there was no VW stock to go out and buy since the German government wouldn’t sell its allocation and Porsche wouldn’t either. If Porsche called in the options the banks were in trouble.
Porsche called in the options which forced the shorts to buy stock - at whatever price they could get it.
The price squeezed higher as those that were short got massively squeezed and stopped out. For one brief moment in 2008, VW was the world’s most valuable company. Shorts were burned hard.

Incredible event
Porsche apparently made $11.5 billion on the trade. The BBC described Porsche as “a hedge fund with a carmaker attached.”
If this all seems exotic then know that the same thing happens in FX all the time. If everyone in the market is talking about a key level in EURUSD being 1.2050 then you can bet the market will try to push through 1.2050 just to take out any short stops at that level. Whether it then rallies higher or fails and trades back lower is a different matter entirely.
This brings us on to the matter of crowded trades. We will look at positioning in more detail in the next section. Crowded trades are dangerous for PNL. If everyone believes EURUSD is going down and has already sold EURUSD then you run the risk of a short squeeze.
For additional selling to take place you need a very good reason for people to add to their position whereas a move in the other direction could force mass buying to cover their shorts.
A trading mentor when I worked at the investment bank once advised me:
Always think about which move would cause the maximum people the maximum pain. That move is precisely what you should be watching out for at all times.

Asymmetric losses

Also known as picking up pennies in front of a steamroller. This risk has caught out many a retail trader. Sometimes it is referred to as a "negative skew" strategy.
Ideally what you are looking for is asymmetric risk trade set-ups: that is where the downside is clearly defined and smaller than the upside. What you want to avoid is the opposite.
A famous example of this going wrong was the Swiss National Bank de-peg in 2012.
The Swiss National Bank had said they would defend the price of EURCHF so that it did not go below 1.2. Many people believed it could never go below 1.2 due to this. Many retail traders therefore opted for a strategy that some describe as ‘picking up pennies in front of a steam-roller’.
They would would buy EURCHF above the peg level and hope for a tiny rally of several pips before selling them back and keep doing this repeatedly. Often they were highly leveraged at 100:1 so that they could amplify the profit of the tiny 5-10 pip rally.
Then this happened.

Something that changed FX markets forever
The SNB suddenly did the unthinkable. They stopped defending the price. CHF jumped and so EURCHF (the number of CHF per 1 EUR) dropped to new lows very fast. Clearly, this trade had horrific risk : reward asymmetry: you risked 30% to make 0.05%.
Other strategies like naively selling options have the same result. You win a small amount of money each day and then spectacularly blow up at some point down the line.

Market positioning

We have talked about short squeezes. But how do you know what the market position is? And should you care?
Let’s start with the first. You should definitely care.
Let’s imagine the entire market is exceptionally long EURUSD and positioning reaches extreme levels. This makes EURUSD very vulnerable.
To keep the price going higher EURUSD needs to attract fresh buy orders. If everyone is already long and has no room to add, what can incentivise people to keep buying? The news flow might be good. They may believe EURUSD goes higher. But they have already bought and have their maximum position on.
On the flip side, if there’s an unexpected event and EURUSD gaps lower you will have the entire market trying to exit the position at the same time. Like a herd of cows running through a single doorway. Messy.
We are going to look at this in more detail in a later chapter, where we discuss ‘carry’ trades. For now this TRYJPY chart might provide some idea of what a rush to the exits of a crowded position looks like.

A carry trade position clear-out in action
Knowing if the market is currently at extreme levels of long or short can therefore be helpful.
The CFTC makes available a weekly report, which details the overall positions of speculative traders “Non Commercial Traders” in some of the major futures products. This includes futures tied to deliverable FX pairs such as EURUSD as well as products such as gold. The report is called “CFTC Commitments of Traders” ("COT").
This is a great benchmark. It is far more representative of the overall market than the proprietary ones offered by retail brokers as it covers a far larger cross-section of the institutional market.
Generally market participants will not pay a lot of attention to commercial hedgers, which are also detailed in the report. This data is worth tracking but these folks are simply hedging real-world transactions rather than speculating so their activity is far less revealing and far more noisy.
You can find the data online for free and download it directly here.

Raw format is kinda hard to work with

However, many websites will chart this for you free of charge and you may find it more convenient to look at it that way. Just google “CFTC positioning charts”.

But you can easily get visualisations
You can visually spot extreme positioning. It is extremely powerful.
Bear in mind the reports come out Friday afternoon US time and the report is a snapshot up to the prior Tuesday. That means it is a lagged report - by the time it is released it is a few days out of date. For longer term trades where you hold positions for weeks this is of course still pretty helpful information.
As well as the absolute level (is the speculative market net long or short) you can also use this to pick up on changes in positioning.
For example if bad news comes out how much does the net short increase? If good news comes out, the market may remain net short but how much did they buy back?
A lot of traders ask themselves “Does the market have this trade on?” The positioning data is a good method for answering this. It provides a good finger on the pulse of the wider market sentiment and activity.
For example you might say: “There was lots of noise about the good employment numbers in the US. However, there wasn’t actually a lot of position change on the back of it. Maybe everyone who wants to buy already has. What would happen now if bad news came out?”
In general traders will be wary of entering a crowded position because it will be hard to attract additional buyers or sellers and there could be an aggressive exit.
If you want to enter a trade that is showing extreme levels of positioning you must think carefully about this dynamic.

Bet correlation

Retail traders often drastically underestimate how correlated their bets are.
Through bitter experience, I have learned that a mistake in position correlation is the root of some of the most serious problems in trading. If you have eight highly correlated positions, then you are really trading one position that is eight times as large.
Bruce Kovner of hedge fund, Caxton Associates
For example, if you are trading a bunch of pairs against the USD you will end up with a simply huge USD exposure. A single USD-trigger can ruin all your bets. Your ideal scenario — and it isn’t always possible — would be to have a highly diversified portfolio of bets that do not move in tandem.
Look at this chart. Inverted USD index (DXY) is green. AUDUSD is orange. EURUSD is blue.

Chart from TradingView
So the whole thing is just one big USD trade! If you are long AUDUSD, long EURUSD, and short DXY you have three anti USD bets that are all likely to work or fail together.
The more diversified your portfolio of bets are, the more risk you can take on each.
There’s a really good video, explaining the benefits of diversification from Ray Dalio.
A systematic fund with access to an investable universe of 10,000 instruments has more opportunity to make a better risk-adjusted return than a trader who only focuses on three symbols. Diversification really is the closest thing to a free lunch in finance.
But let’s be pragmatic and realistic. Human retail traders don’t have capacity to run even one hundred bets at a time. More realistic would be an average of 2-3 trades on simultaneously. So what can be done?
For example:
  • You might diversify across time horizons by having a mix of short-term and long-term trades.
  • You might diversify across asset classes - trading some FX but also crypto and equities.
  • You might diversify your trade generation approach so you are not relying on the same indicators or drivers on each trade.
  • You might diversify your exposure to the market regime by having some trades that assume a trend will continue (momentum) and some that assume we will be range-bound (carry).
And so on. Basically you want to scan your portfolio of trades and make sure you are not putting all your eggs in one basket. If some trades underperform others will perform - assuming the bets are not correlated - and that way you can ensure your overall portfolio takes less risk per unit of return.
The key thing is to start thinking about a portfolio of bets and what each new trade offers to your existing portfolio of risk. Will it diversify or amplify a current exposure?

Crap trades, timeouts and monthly limits

One common mistake is to get bored and restless and put on crap trades. This just means trades in which you have low conviction.
It is perfectly fine not to trade. If you feel like you do not understand the market at a particular point, simply choose not to trade.
Flat is a position.
Do not waste your bullets on rubbish trades. Only enter a trade when you have carefully considered it from all angles and feel good about the risk. This will make it far easier to hold onto the trade if it moves against you at any point. You actually believe in it.
Equally, you need to set monthly limits. A standard limit might be a 10% account balance stop per month. At that point you close all your positions immediately and stop trading till next month.

Be strict with yourself and walk away
Let’s assume you started the year with $100k and made 5% in January so enter Feb with $105k balance. Your stop is therefore 10% of $105k or $10.5k . If your account balance dips to $94.5k ($105k-$10.5k) then you stop yourself out and don’t resume trading till March the first.
Having monthly calendar breaks is nice for another reason. Say you made a load of money in January. You don’t want to start February feeling you are up 5% or it is too tempting to avoid trading all month and protect the existing win. Each month and each year should feel like a clean slate and an independent period.
Everyone has trading slumps. It is perfectly normal. It will definitely happen to you at some stage. The trick is to take a break and refocus. Conserve your capital by not trading a lot whilst you are on a losing streak. This period will be much harder for you emotionally and you’ll end up making suboptimal decisions. An enforced break will help you see the bigger picture.
Put in place a process before you start trading and then it’ll be easy to follow and will feel much less emotional. Remember: the market doesn’t care if you win or lose, it is nothing personal.
When your head has cooled and you feel calm you return the next month and begin the task of building back your account balance.

That's a wrap on risk management

Thanks for taking time to read this three-part chapter on risk management. I hope you enjoyed it. Do comment in the replies if you have any questions or feedback.
Remember: the most important part of trading is not making money. It is not losing money. Always start with that principle. I hope these three notes have provided some food for thought on how you might approach risk management and are of practical use to you when trading. Avoiding mistakes is not a sexy tagline but it is an effective and reliable way to improve results.
Next up I will be writing about an exciting topic I think many traders should look at rather differently: news trading. Please follow on here to receive notifications and the broad outline is below.
News Trading Part I
  • Introduction
  • Why use the economic calendar
  • Reading the economic calendar
  • Knowing what's priced in
  • Surveys
  • Interest rates
  • First order thinking vs second order thinking
News Trading Part II
  • Preparing for quantitative and qualitative releases
  • Data surprise index
  • Using recent events to predict future reactions
  • Buy the rumour, sell the fact
  • The mysterious 'position trim' effect
  • Reversals
  • Some key FX releases
***

Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
submitted by getmrmarket to Forex [link] [comments]

THROW YOUR FD's in FDS

Factset: How You can Invest in Hedge Funds’ Biggest Investment
Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists
If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now:
Their latest 8k filing reported the following:
Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions.
Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region
Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic.
Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019.
Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results.
The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020.
FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders.
As you can see, there’s not much of a negative sign in sight here.
It makes sense considering how FactSet’s FCF has never slowed down:
https://preview.redd.it/frmtdk8e9hk51.png?width=276&format=png&auto=webp&s=1c0ff12539e0b2f9dbfda13d0565c5ce2b6f8f1a

https://preview.redd.it/6axdb6lh9hk51.png?width=593&format=png&auto=webp&s=9af1673272a5a2d8df28f60f4707e948a00e5ff1
FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with.
Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis:
https://www.investopedia.com/terms/f/factset.asp
https://preview.redd.it/yo71y6qj9hk51.png?width=355&format=png&auto=webp&s=a9414bdaa03c06114ca052304a26fae2773c3e45

FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015:

https://preview.redd.it/oxaa1wel9hk51.png?width=443&format=png&auto=webp&s=13d60d2518980360c403364f7150392ab83d07d7
So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33%
https://preview.redd.it/e4trju3p9hk51.png?width=387&format=png&auto=webp&s=6f6bee15f836c47e73121054ec60459f147d353e

EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded.
https://preview.redd.it/yl7f58tr9hk51.png?width=489&format=png&auto=webp&s=68906b9ecbcf6d886393c4ff40f81bdecab9e9fd

P/E has declined in the past 2 years, making it a great time to buy.

https://preview.redd.it/4mqw3t4t9hk51.png?width=445&format=png&auto=webp&s=e8d719f4913883b044c4150f11b8732e14797b6d
Increasing ROE despite lowering of leverage post 2016
https://preview.redd.it/lt34avzu9hk51.png?width=441&format=png&auto=webp&s=f3742ed87cd1c2ccb7a3d3ee71ae8c7007313b2b

Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself.
https://preview.redd.it/fliirmpx9hk51.png?width=370&format=png&auto=webp&s=1216eddeadb4f84c8f4f48692a2f962ba2f1e848

SGA expense/Gross profit has been declining despite expansion of offices
I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful.
Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in.
Calls have shitty greeks, but if you're ballsy October 450s LOL, I'm holding shares
I’d say it’s a great long term investment, and it should at least be on your watchlist.
submitted by WannabeStonks69 to wallstreetbets [link] [comments]

Profitable Forex Strategy Reddit | 3 Easy Forex Strategies Easy For MT4

Profitable Forex Strategy Reddit | 3 Easy Forex Strategies Easy For MT4

The need for a trading strategy in Forex market

https://preview.redd.it/r6u8stdmeaw51.jpg?width=1320&format=pjpg&auto=webp&s=1b0292502d6e68f5c220af5a5851aeb8061b395b
Almost all trading manuals talk about the need to have your own trading strategy. First of all, the process of creating your trading scheme allows you to perfectly understand trading and exclude from it any eventuality that hides additional risk.
Profitable forex strategy: it is a type of instruction for the trader, which helps to follow a clearly verified algorithm and safeguard his deposit from emotional errors and consequences of the unpredictability of the Forex currency market.
Thanks to her, you will always know the answer to the question: how to act in certain market conditions. You have the conditions of opening a transaction, the conditions of its closing, likewise, you do not guess if it is time or not. You do what the trading strategy tells you. This does not mean that it cannot be changed. A healthy trading scheme in the forex market must be constantly adjusted, it must comply with the realities of current market trends, but there must be no unfounded arguments in it.
>>> Forex Signals With Unbeatable Performance: Verified Forex Results And 5° Rated On Investing.com |Free Forex Signals Trial: CLICK HERE TO JOIN FOR FREE

Profitable Forex Strategy Reddit

Types of trading strategies
The forms of a trading strategy can combine a variety of methods. However, several of the most commonly used options can be highlighted.
  • Trading strategy based on various complementary technical indicators
  • Trading strategy using Bollinger Bands
  • Moving Average Strategy
  • Technical figures and patterns
  • Trading with Fibonacci levels
  • Candlestick trading strategy
  • Trend trading strategy
  • Flat trading strategy
  • Scalping
  • Fundamental analysis as the basis of the strategy

Three most profitable Forex strategies

Important! These strategies are the basis for building your own trading system. Indicator settings and recommended pending order levels are for consultation only. If you do not get a satisfactory outcome in the test result or in a live account, that does not mean that the problem is the strategy. It is enough to choose individual parameters of indicators under a separate asset and under the current market situation.

1. “Bali” scalping strategy

This strategy is one of the most popular, at least its description can be found on many websites. However, the recommendations will be different. According to the author's idea, "Bali" refers to scalping tactics, as it facilitates a fairly short stop loss (SL) and take profit (TP). However, the recommended time frame is high, because the signals appear not very often. The authors recommend using the H1 interval and the EUR / USD currency pair.
Indicators used:
  • Linear Weighted Moving Average. Period 48 (red line).
https://preview.redd.it/9mhs67mxeaw51.jpg?width=461&format=pjpg&auto=webp&s=913d428edd4cab0a3237e7039829a76dd587f1f5
The weighted linear moving average here acts as an additional filter. Due to the fact that LWMA gives more weight to the values ​​of the last periods, the indicator in the long periods practically excludes delays. In some cases, LWMA can give a signal beforehand, but in this strategy only the moving position relative to price is important. Bearish LWMA is a buy signal, sell bullish.
  • Trend Envelopes_v2. Period 2 (orange and blue lines).
https://preview.redd.it/8bap0s41faw51.jpg?width=627&format=pjpg&auto=webp&s=a6236ad06765280bbfd655fa1fb4153b28aaaf56
The indicator is also based on the moving average, but the formula is slightly different for the calculation. Its marking is more precise (the impact of price noise has been eliminated). It allows you to identify the twists of the trend compared to the usual mobile with a slight anticipation. Trend Envelopes has an interesting property: the color of the line and its new location changes when the price penetrates its old trend line, a kind of signal.
  • DSS of momentum. The configuration in the screenshot below.
https://preview.redd.it/9ch27cj4faw51.jpg?width=630&format=pjpg&auto=webp&s=00558bbd90378009bef33b7c96c77f884b912667
The indicator is placed in a separate window below the chart. This is an oscillator whose task is to determine the pivot points of the trend. And it does so much faster than standard oscillators. It has two lines: the signal is dotted, the additional line is solid, but the receiver has 2 kinds of colors (orange and green).
  • Important! Note that the indicators for the “Bali” strategy are chosen in such a way as to ultimately give an early signal. This gives the trader time to confirm the signal and check the fundamentals.
MA is one of the basics on MT4, the other two indicators can be found in the archive for free here. To add them to the platform, click on MT4: "File / Open data directory". In the folder that opens, follow the following path: MQL4 / Indicators. Copy the flags to the folder and restart the platform.
Also Read: Make Money With Trading
Conditions to open a long position:
  • Price penetrates the orange Trend Envelopes line from the bottom up. At the same time in the same candle there is a change of the orange line that falls to a growing celestial.
  • The candle is above LWMA. Once the above condition has been met, we wait for the candle to appear above the moving one. It is important that it closes above the LWMA red line. It is mandatory to have a Skyline Trend Envelopes on a signal candle.
  • The additional DSS of momentum line on the signal candle is green and is above the dotted line of the signal (that is, it crosses or crosses it).
We open a trade at the close of the signal candle. The recommended stop level is 20-25 points in 4-digit quotes, take profit at 40-50 points.
https://preview.redd.it/t48d55s8faw51.jpg?width=1000&format=pjpg&auto=webp&s=1e93863745e74dec536178539817225767cbeb1c
The arrow indicates a signal candle where a Trend Envelopes color change occurred. Note (purple ovals) that the blue line is below the orange line and goes upwards (in other cases the signal should be ignored). In the signal candle, the green DSS of momentum line is above the dotted line.
Conditions to open a short position:
  • Price penetrates the Trend Envelopes sky line from top to bottom. At the same time in the same candle there is a change from the increasing celestial line to the falling orange.
  • The candle is below LWMA. Once the above condition has been met, we wait for the candle to appear below the mobile. It is important that it closes below the LWMA red line. It is mandatory to have an orange Trend Envelopes line on a signal candle.
  • The additional DSS of momentum line on the signal candle is orange and is below the dotted line of the signal (i.e. crosses or crosses it).
https://preview.redd.it/6uixkl1dfaw51.jpg?width=1000&format=pjpg&auto=webp&s=dd53442c633e80c1e55da72cd5ffe9cda2e85b8a
Some examples where a transaction cannot be opened:
  1. In the screenshot below the signal candle closed at the moving level (red line), it was practically below it.
https://preview.redd.it/2o1wpocgfaw51.jpg?width=1000&format=pjpg&auto=webp&s=58d3286bf2884b5f0dfdaa0a62b68d2d50cdabf8
  1. In the screenshot below the signal candle is DSS below its signal line. Also, the celestial line is horizontal and not ascending.
https://preview.redd.it/1nfi1etjfaw51.jpg?width=801&format=pjpg&auto=webp&s=ff9fcbc10a485c5102ef7a135de47332827caf54
The signals are relatively rare, a signal can be expected for several days. In half the cases, it is better to control the transaction and close in advance, without waiting for profit taking. We do not operate at the time of flat. Try this strategy directly in the browser and see the result.
>>> Forex Signals With Unbeatable Performance: Verified Forex Results And 5° Rated On Investing.com |Free Forex Signals Trial: CLICK HERE TO JOIN FOR FREE

2. “Va-Bank” candle strategy

This profitable Forex strategy is weekly and can be used on different currency pairs. It is based on the spring principle of price movement, what went up quickly, sooner or later must fall. To trade you will only need a schedule on any platform and W1 time frame (although the daily interval can be used).
You should estimate the size of the candle bodies of different currency pairs ( AUDCAD , AUDJPY , AUDUSD , EURGBP , EURJPY , GBPUSD , CHFJPY , NZDCHF , EURAUD , AUDCHF , CADCHF , EURUSD , EURCAD , GBPCHF ) and choose the largest distance from the opening to the close of the candle in the framework of the week. In this to open a transaction at the beginning of the following week.
Conditions to open a long position:
  • The bearish candle, which signifies last week's movement, has a relatively large body.
Open a long position early next week. Make sure to place a stop loss at 100-140 points and a take profit at 50-70 points. When it is midweek, close the order if it has not yet been closed at take profit or stop loss. After that, wait again for the beginning of the week and repeat the procedure, in any case do not open operations at the end of the current week.
https://preview.redd.it/vuihnqspfaw51.jpg?width=1000&format=pjpg&auto=webp&s=7641e9d7701911cc255c4f0c8a53e1660c35c9fe
On this chart it is clearly seen that after each large bearish candle there is necessarily a bullish candle (although smaller). The only question is what period to take where it makes sense to compare the relative length of the candles. Here everything is individual for each currency pair. Note that a rising candle was observed followed by a few small bearish candles. But when it comes to minimizing risks, it is best not to open a long response position, as the relatively small decline from the previous week may continue.
Conditions to open a short position:
  • The bullish candle, which signifies last week's movement, has a relatively large body.
We open a short position early next week.
https://preview.redd.it/tv4zmf5ufaw51.jpg?width=1000&format=pjpg&auto=webp&s=61cd1dcfc4aebfa6f80343b6c51f7a6e46358602
The red arrows point to the candles that had a large body around the previous bullish candles. Almost all signals turned out to be profitable, except for the transactions indicated by a blue arrow. The shortcomings of the strategy are rare signs, albeit with a high probability of profit. The best thing is that it can be used in several pairs at the same time.
This strategy has an interesting modification based on similar logic. Investors with little capital opt for intraday strategies, as their money is insufficient to exert radical pressure on the market. Therefore, if there is a strong move on the weekly chart, this may indicate a cluster of large strong traders. In other words, if there are three weekly candles in one direction, it is most likely the fourth. Here you also have to take into account the psychological factor, 4 candles is equal to one month, and those who "push" the market in one direction, within a month will begin to set profits.
Strategy principle:
  • A "three candles" pattern (ascending and descending) formed on the weekly chart.
  • It is preferable that each subsequent candle was larger than the previous one. Doji is not taken into account (disembodied candles).
  • Stop is placed at the closing level of the first candle of the constructed formation. Take profit at 50-100% of the last candle, but it is often better to manually close the trade.
An example of this type of formation in the screenshot below.
https://preview.redd.it/iu7cwa7xfaw51.jpg?width=1000&format=pjpg&auto=webp&s=9195d24b72d2bda5394614380e9e5bc167f108a5
Of the 5 patterns, 4 were effective. Lack of strategy, the pattern can be expected 2-3 months. But when launching a multi-currency strategy this expectation is justified. Consider swaps!
>>> Forex Signals With Unbeatable Performance: Verified Forex Results And 5° Rated On Investing.com |Free Forex Signals Trial: CLICK HERE TO JOIN FOR FREE

3. Parabolic Profit Based on Moving Average

This strategy is universal and is usually given as an example for novice traders. It uses classic EMA (Exponential Moving Average) indicators for MT4 and Parabolic SAR, which acts as a confirmatory indicator.
The strategy is trend. Most sources suggest using it in "minutes", but price noise reduces its efficiency. It is better to use M15-M30 intervals. Currency pairs - Any, but you may need to adjust the indicator settings.
Indicators used:
  • EMA with periods 5, 25 and 50. EMA (5) in red, EMA (25) and EMA (50) in yellow. Apply to Close (closing price).
https://preview.redd.it/ly7ju8o3gaw51.jpg?width=1000&format=pjpg&auto=webp&s=61dee5b0d994d09a375e01e2b9afe188dd2ee0ed
  • Parabolic SAR, parameters remain unchanged (color correct at your discretion).
https://preview.redd.it/sonpv1m8gaw51.jpg?width=1000&format=pjpg&auto=webp&s=823e9ce5d279d3a98ef072694766a112a3ece775
Conditions to open a long position:
  • Red EMA (5) crosses the yellows from bottom to top.
  • Parabolic SAR is located under the sails.
Conditions to open a short position:
  • Red EMA (5) crosses the yellows from top to bottom.
  • Parabolic SAR is located above the candles.
The transaction can be opened on the same candle where the mobile crossover occurred. Stop loss at the local minimum, take profit at 20-25 points. But with the manual management of transactions you can extract great benefits. For example, close at the time of the transition from EMA (5) to a horizontal position (change of the angle of inclination of the growth to flat).
https://preview.redd.it/4un92jlegaw51.jpg?width=1000&format=pjpg&auto=webp&s=406a700c00722349622d031e20d0858e4196d18b
This screen shows that all three signals (two long and one short) were effective. It would be possible to enter the market on the candle by following the signal (in order to accurately verify the direction of the trend), but you would then miss the right time to enter. It is up to you to decide whether it is worth the risk. For one-hour intervals, these parameters hardly work, so be sure to check the performance of the indicators for each period of time in a minimum span of three years.
And now that you know the theory, a few words about how to put these strategies into practice.
Ready? Then let's get started!

From the theory to the practice

Step 1. Open demo account It's free, requires no deposit, takes up to 15 minutes, and no verification required. On the main page of your broker there is for sures a button "Register", click and follow the instructions. An account can also be opened from other menus (for example, from the top menu, from the commercial conditions of the account, etc.).
Step 2. Familiarize yourself with the functionality of the Personal Area. It won't take long. It is at the most user friendly and intuitive. You just need to understand the instruments of the platform and understand how the trades are opened.
Step 3. Launch the trading platform. The Personal Area has the platform incorporated, but it is impossible to add templates. Hence, the "Bali" and "Parabolic Profit" strategies can only be executed on MT4.

Characteristics of an effective Forex strategy Reddit

And finally, let's see what makes a profitable Forex strategy effective. What properties should it have? Perhaps three of the most important characteristics can be pointed out.
  • The minimum number of lag indicators. The smaller they are, the greater the forecast accuracy.
  • Easy. Understanding your strategy is more important than your saturation with complex elements, formulas, and schematics.
  • Uniqueness. Any trading strategy must be "tailored" to your trading style, your character, your circumstances, and so on.
It is very important to develop your own trading strategy, but it is necessary to test a large number of already available and proven strategies. On the Forex blog you will find trading strategies available for download. Before using a live account, test your chosen strategy on the demo account on the MetaTrader trading platform.
Conclusion. To successfully trade the Forex currency market, create your own trading strategy. Learn what's new, learn out-of-the-box trading schemes, and improve your individual action plan in the market. Only in this case, the trading results will satisfy you to the fullest. Success, dear readers!
>>> Forex Signals With Unbeatable Performance: Verified Forex Results And 5° Rated On Investing.com |Free Forex Signals Trial: CLICK HERE TO JOIN FOR FREE
Join the community for more articles on trading and making money on the Forex and Stock market.
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Disclosure: This post contains affiliate links, if you click and make a purchase I may receive a commission - This has NO extra cost for you.
submitted by kayakero to makemoneyforexreddit [link] [comments]

Level01Main App Launch on 10th Oct 2020

Level01Main App Launch on 10th Oct 2020
https://preview.redd.it/8y1d9ion4er51.jpg?width=1200&format=pjpg&auto=webp&s=8a260daa2b740980958dfa5a9459bcf7405f9727
Level01 is the World’s 1st DeFi Platform with AI-Guided Derivatives Trading. Our main app will be launched on 10 October 2020. Get ready for real money trading.
- Clear, Transparent and Fair Options Trading DApp - Decentralized: Peer to peer options trading for more profits - Trade Fairly: FairSense AI calculates contract Risk/Reward - Reliable Data from Bloomberg and Thomson Reuters - Control your own funds: Trade mobile app includes non-custodial private wallet - Blockchain-based smart contracts for transparency and reliability - No tampering: Settlement finality on ETH blockchain - Trade-In Multiple Markets: Forex, Crypto, Commodity - Easy To Use: Generate profits from price movements, hedging or insurance.
Download and try it, https://play.google.com/store/apps/details?id=io.level01.android Quickstart Guide: https://level01.io/quickstart-trading-guide/ Web: https://Level01.io
submitted by Level01Exchange to Level01io [link] [comments]

We are live! Get your hands on Level01, the World’s 1st DeFi Platform with AI-Guided Derivatives Trading.

We are live! Get your hands on Level01, the World’s 1st DeFi Platform with AI-Guided Derivatives Trading.
https://preview.redd.it/zw7phqsvbhs51.jpg?width=526&format=pjpg&auto=webp&s=1410d020d405ef7c3fb1f81d74e795e91b5dac3d
We are live! Get your hands on Level01, the World’s 1st DeFi Platform with AI-Guided Derivatives Trading. You can try either Demo trading or Real Money trading. We provide free 10,000 LVX demo token for you to experience trading with our FairSense AI guidance without risk.
- Clear, Transparent and Fair Options Trading DApp - Decentralized: Peer to peer options trading for more profits - Trade Fairly: FairSense AI calculates contract Risk/Reward - Reliable Data from Bloomberg and Thomson Reuters - Control your own funds: Trade mobile app includes non-custodial private wallet - Blockchain-based smart contracts for transparency and reliability - No tampering: Settlement finality on ETH blockchain - Trade In Multiple Markets: Forex, Crypto, Commodity - Easy To Use: Generate profits from price movements, hedging or insurance.
Download and try it, https://play.google.com/store/apps/details...
Quickstart Guide: https://level01.io/quickstart-trading-guide/
Web: https://Level01.io
submitted by Level01Exchange to Level01io [link] [comments]

One more day to our main app launch! Get ready for real money trading.

One more day to our main app launch! Get ready for real money trading.
https://preview.redd.it/38yqms52tzr51.jpg?width=526&format=pjpg&auto=webp&s=8ae9736c169a6451fc9824f26600e53801eeea24
Level01 is the World’s 1st DeFi Platform with AI-Guided Derivatives Trading.
- Clear, Transparent and Fair Options Trading DApp - Decentralized: Peer to peer options trading for more profits - Trade Fairly: FairSense AI calculates contract Risk/Reward - Reliable Data from Bloomberg and Thomson Reuters - Control your own funds: Trade mobile app includes non-custodial private wallet - Blockchain-based smart contracts for transparency and reliability - No tampering: Settlement finality on ETH blockchain - Trade In Multiple Markets: Forex, Crypto, Commodity - Easy To Use: Generate profits from price movements, hedging or insurance.
Download and try it, https://play.google.com/store/apps/details...
Quickstart Guide: https://level01.io/quickstart-trading-guide/
Web: https://Level01.io
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Our main app will be launched on 10 October 2020

Our main app will be launched on 10 October 2020
https://preview.redd.it/r2duflcppsr51.jpg?width=1080&format=pjpg&auto=webp&s=b5c77fba0dcade486c30fb580b7fd85348e7b195
Level01 is the World’s 1st DeFi Platform with AI-Guided Derivatives Trading. Our main app will be launched on 10 October 2020. Get ready for real money trading. ☑ Clear, Transparent and Fair Options Trading DApp ☑ Decentralized: Peer to peer options trading for more profits ☑ Trade Fairly: FairSense AI calculates contract Risk/Reward ☑ Reliable Data from Bloomberg and Thomson Reuters ☑ Control your own funds: Trade mobile app includes non-custodial private wallet ☑ Blockchain-based smart contracts for transparency and reliability ☑ No tampering: Settlement finality on ETH blockchain ☑ Trade In Multiple Markets: Forex, Crypto, Commodity ☑ Easy To Use: Generate profits from price movements, hedging or insurance.
Download and try it, https://play.google.com/store/apps/details?id=io.level01.android Quickstart Guide: https://level01.io/quickstart-trading-guide/ Web: https://Level01.io
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No, the British did not steal $45 trillion from India

This is an updated copy of the version on BadHistory. I plan to update it in accordance with the feedback I got.
I'd like to thank two people who will remain anonymous for helping me greatly with this post (you know who you are)
Three years ago a festschrift for Binay Bhushan Chaudhuri was published by Shubhra Chakrabarti, a history teacher at the University of Delhi and Utsa Patnaik, a Marxist economist who taught at JNU until 2010.
One of the essays in the festschirt by Utsa Patnaik was an attempt to quantify the "drain" undergone by India during British Rule. Her conclusion? Britain robbed India of $45 trillion (or £9.2 trillion) during their 200 or so years of rule. This figure was immensely popular, and got republished in several major news outlets (here, here, here, here (they get the number wrong) and more recently here), got a mention from the Minister of External Affairs & returns 29,100 results on Google. There's also plenty of references to it here on Reddit.
Patnaik is not the first to calculate such a figure. Angus Maddison thought it was £100 million, Simon Digby said £1 billion, Javier Estaban said £40 million see Roy (2019). The huge range of figures should set off some alarm bells.
So how did Patnaik calculate this (shockingly large) figure? Well, even though I don't have access to the festschrift, she conveniently has written an article detailing her methodology here. Let's have a look.
How exactly did the British manage to diddle us and drain our wealth’ ? was the question that Basudev Chatterjee (later editor of a volume in the Towards Freedom project) had posed to me 50 years ago when we were fellow-students abroad.
This is begging the question.
After decades of research I find that using India’s commodity export surplus as the measure and applying an interest rate of 5%, the total drain from 1765 to 1938, compounded up to 2016, comes to £9.2 trillion; since $4.86 exchanged for £1 those days, this sum equals about $45 trillion.
This is completely meaningless. To understand why it's meaningless consider India's annual coconut exports. These are almost certainly a surplus but the surplus in trade is countered by the other country buying the product (indeed, by definition, trade surpluses contribute to the GDP of a nation which hardly plays into intuitive conceptualisations of drain).
Furthermore, Dewey (2019) critiques the 5% interest rate.
She [Patnaik] consistently adopts statistical assumptions (such as compound interest at a rate of 5% per annum over centuries) that exaggerate the magnitude of the drain
Moving on:
The exact mechanism of drain, or transfers from India to Britain was quite simple.
Convenient.
Drain theory possessed the political merit of being easily grasped by a nation of peasants. [...] No other idea could arouse people than the thought that they were being taxed so that others in far off lands might live in comfort. [...] It was, therefore, inevitable that the drain theory became the main staple of nationalist political agitation during the Gandhian era.
- Chandra et al. (1989)
The key factor was Britain’s control over our taxation revenues combined with control over India’s financial gold and forex earnings from its booming commodity export surplus with the world. Simply put, Britain used locally raised rupee tax revenues to pay for its net import of goods, a highly abnormal use of budgetary funds not seen in any sovereign country.
The issue with figures like these is they all make certain methodological assumptions that are impossible to prove. From Roy in Frankema et al. (2019):
the "drain theory" of Indian poverty cannot be tested with evidence, for several reasons. First, it rests on the counterfactual that any money saved on account of factor payments abroad would translate into domestic investment, which can never be proved. Second, it rests on "the primitive notion that all payments to foreigners are "drain"", that is, on the assumption that these payments did not contribute to domestic national income to the equivalent extent (Kumar 1985, 384; see also Chaudhuri 1968). Again, this cannot be tested. [...] Fourth, while British officers serving India did receive salaries that were many times that of the average income in India, a paper using cross-country data shows that colonies with better paid officers were governed better (Jones 2013).
Indeed, drain theory rests on some very weak foundations. This, in of itself, should be enough to dismiss any of the other figures that get thrown out. Nonetheless, I felt it would be a useful exercise to continue exploring Patnaik's take on drain theory.
The East India Company from 1765 onwards allocated every year up to one-third of Indian budgetary revenues net of collection costs, to buy a large volume of goods for direct import into Britain, far in excess of that country’s own needs.
So what's going on here? Well Roy (2019) explains it better:
Colonial India ran an export surplus, which, together with foreign investment, was used to pay for services purchased from Britain. These payments included interest on public debt, salaries, and pensions paid to government offcers who had come from Britain, salaries of managers and engineers, guaranteed profts paid to railway companies, and repatriated business profts. How do we know that any of these payments involved paying too much? The answer is we do not.
So what was really happening is the government was paying its workers for services (as well as guaranteeing profits - to promote investment - something the GoI does today Dalal (2019), and promoting business in India), and those workers were remitting some of that money to Britain. This is hardly a drain (unless, of course, Indian diaspora around the world today are "draining" it). In some cases, the remittances would take the form of goods (as described) see Chaudhuri (1983):
It is obvious that these debit items were financed through the export surplus on merchandise account, and later, when railway construction started on a large scale in India, through capital import. Until 1833 the East India Company followed a cumbersome method in remitting the annual home charges. This was to purchase export commodities in India out of revenue, which were then shipped to London and the proceeds from their sale handed over to the home treasury.
While Roy's earlier point argues better paid officers governed better, it is honestly impossible to say what part of the repatriated export surplus was a drain, and what was not. However calling all of it a drain is definitely misguided.
It's worth noting that Patnaik seems to make no attempt to quantify the benefits of the Raj either, Dewey (2019)'s 2nd criticism:
she [Patnaik] consistently ignores research that would tend to cut the economic impact of the drain down to size, such as the work on the sources of investment during the industrial revolution (which shows that industrialisation was financed by the ploughed-back profits of industrialists) or the costs of empire school (which stresses the high price of imperial defence)

Since tropical goods were highly prized in other cold temperate countries which could never produce them, in effect these free goods represented international purchasing power for Britain which kept a part for its own use and re-exported the balance to other countries in Europe and North America against import of food grains, iron and other goods in which it was deficient.
Re-exports necessarily adds value to goods when the goods are processed and when the goods are transported. The country with the largest navy at the time would presumably be in very good stead to do the latter.
The British historians Phyllis Deane and WA Cole presented an incorrect estimate of Britain’s 18th-19th century trade volume, by leaving out re-exports completely. I found that by 1800 Britain’s total trade was 62% higher than their estimate, on applying the correct definition of trade including re-exports, that is used by the United Nations and by all other international organisations.
While interesting, and certainly expected for such an old book, re-exporting necessarily adds value to goods.
When the Crown took over from the Company, from 1861 a clever system was developed under which all of India’s financial gold and forex earnings from its fast-rising commodity export surplus with the world, was intercepted and appropriated by Britain. As before up to a third of India’s rising budgetary revenues was not spent domestically but was set aside as ‘expenditure abroad’.
So, what does this mean? Britain appropriated all of India's earnings, and then spent a third of it aboard? Not exactly. She is describing home charges see Roy (2019) again:
Some of the expenditures on defense and administration were made in sterling and went out of the country. This payment by the government was known as the Home Charges. For example, interest payment on loans raised to finance construction of railways and irrigation works, pensions paid to retired officers, and purchase of stores, were payments in sterling. [...] almost all money that the government paid abroad corresponded to the purchase of a service from abroad. [...] The balance of payments system that emerged after 1800 was based on standard business principles. India bought something and paid for it. State revenues were used to pay for wages of people hired abroad, pay for interest on loans raised abroad, and repatriation of profits on foreign investments coming into India. These were legitimate market transactions.
Indeed, if paying for what you buy is drain, then several billions of us are drained every day.
The Secretary of State for India in Council, based in London, invited foreign importers to deposit with him the payment (in gold, sterling and their own currencies) for their net imports from India, and these gold and forex payments disappeared into the yawning maw of the SoS’s account in the Bank of England.
It should be noted that India having two heads was beneficial, and encouraged investment per Roy (2019):
The fact that the India Office in London managed a part of the monetary system made India creditworthy, stabilized its currency, and encouraged foreign savers to put money into railways and private enterprise in India. Current research on the history of public debt shows that stable and large colonies found it easier to borrow abroad than independent economies because the investors trusted the guarantee of the colonist powers.

Against India’s net foreign earnings he issued bills, termed Council bills (CBs), to an equivalent rupee value. The rate (between gold-linked sterling and silver rupee) at which the bills were issued, was carefully adjusted to the last farthing, so that foreigners would never find it more profitable to ship financial gold as payment directly to Indians, compared to using the CB route. Foreign importers then sent the CBs by post or by telegraph to the export houses in India, that via the exchange banks were paid out of the budgeted provision of sums under ‘expenditure abroad’, and the exporters in turn paid the producers (peasants and artisans) from whom they sourced the goods.
Sunderland (2013) argues CBs had two main roles (and neither were part of a grand plot to keep gold out of India):
Council bills had two roles. They firstly promoted trade by handing the IO some control of the rate of exchange and allowing the exchange banks to remit funds to India and to hedge currency transaction risks. They also enabled the Indian government to transfer cash to England for the payment of its UK commitments.

The United Nations (1962) historical data for 1900 to 1960, show that for three decades up to 1928 (and very likely earlier too) India posted the second highest merchandise export surplus in the world, with USA in the first position. Not only were Indians deprived of every bit of the enormous international purchasing power they had earned over 175 years, even its rupee equivalent was not issued to them since not even the colonial government was credited with any part of India’s net gold and forex earnings against which it could issue rupees. The sleight-of-hand employed, namely ‘paying’ producers out of their own taxes, made India’s export surplus unrequited and constituted a tax-financed drain to the metropolis, as had been correctly pointed out by those highly insightful classical writers, Dadabhai Naoroji and RCDutt.
It doesn't appear that others appreciate their insight Roy (2019):
K. N. Chaudhuri rightly calls such practice ‘confused’ economics ‘coloured by political feelings’.

Surplus budgets to effect such heavy tax-financed transfers had a severe employment–reducing and income-deflating effect: mass consumption was squeezed in order to release export goods. Per capita annual foodgrains absorption in British India declined from 210 kg. during the period 1904-09, to 157 kg. during 1937-41, and to only 137 kg by 1946.
Dewey (1978) points out reliability issues with Indian agriculutural statistics, however this calorie decline persists to this day. Some of it is attributed to less food being consumed at home Smith (2015), a lower infectious disease burden Duh & Spears (2016) and diversified diets Vankatesh et al. (2016).
If even a part of its enormous foreign earnings had been credited to it and not entirely siphoned off, India could have imported modern technology to build up an industrial structure as Japan was doing.
This is, unfortunately, impossible to prove. Had the British not arrived in India, there is no clear indication that India would've united (this is arguably more plausible than the given counterfactual1). Had the British not arrived in India, there is no clear indication India would not have been nuked in WW2, much like Japan. Had the British not arrived in India, there is no clear indication India would not have been invaded by lizard people, much like Japan. The list continues eternally.
Nevertheless, I will charitably examine the given counterfactual anyway. Did pre-colonial India have industrial potential? The answer is a resounding no.
From Gupta (1980):
This article starts from the premise that while economic categories - the extent of commodity production, wage labour, monetarisation of the economy, etc - should be the basis for any analysis of the production relations of pre-British India, it is the nature of class struggles arising out of particular class alignments that finally gives the decisive twist to social change. Arguing on this premise, and analysing the available evidence, this article concludes that there was little potential for industrial revolution before the British arrived in India because, whatever might have been the character of economic categories of that period, the class relations had not sufficiently matured to develop productive forces and the required class struggle for a 'revolution' to take place.
A view echoed in Raychaudhuri (1983):
Yet all of this did not amount to an economic situation comparable to that of western Europe on the eve of the industrial revolution. Her technology - in agriculture as well as manufacturers - had by and large been stagnant for centuries. [...] The weakness of the Indian economy in the mid-eighteenth century, as compared to pre-industrial Europe was not simply a matter of technology and commercial and industrial organization. No scientific or geographical revolution formed part of the eighteenth-century Indian's historical experience. [...] Spontaneous movement towards industrialisation is unlikely in such a situation.
So now we've established India did not have industrial potential, was India similar to Japan just before the Meiji era? The answer, yet again, unsurprisingly, is no. Japan's economic situation was not comparable to India's, which allowed for Japan to finance its revolution. From Yasuba (1986):
All in all, the Japanese standard of living may not have been much below the English standard of living before industrialization, and both of them may have been considerably higher than the Indian standard of living. We can no longer say that Japan started from a pathetically low economic level and achieved a rapid or even "miraculous" economic growth. Japan's per capita income was almost as high as in Western Europe before industrialization, and it was possible for Japan to produce surplus in the Meiji Period to finance private and public capital formation.
The circumstances that led to Meiji Japan were extremely unique. See Tomlinson (1985):
Most modern comparisons between India and Japan, written by either Indianists or Japanese specialists, stress instead that industrial growth in Meiji Japan was the product of unique features that were not reproducible elsewhere. [...] it is undoubtably true that Japan's progress to industrialization has been unique and unrepeatable
So there you have it. Unsubstantiated statistical assumptions, calling any number you can a drain & assuming a counterfactual for no good reason gets you this $45 trillion number. Hopefully that's enough to bury it in the ground.
1. Several authors have affirmed that Indian identity is a colonial artefact. For example see Rajan 1969:
Perhaps the single greatest and most enduring impact of British rule over India is that it created an Indian nation, in the modern political sense. After centuries of rule by different dynasties overparts of the Indian sub-continent, and after about 100 years of British rule, Indians ceased to be merely Bengalis, Maharashtrians,or Tamils, linguistically and culturally.
or see Bryant 2000:
But then, it would be anachronistic to condemn eighteenth-century Indians, who served the British, as collaborators, when the notion of 'democratic' nationalism or of an Indian 'nation' did not then exist. [...] Indians who fought for them, differed from the Europeans in having a primary attachment to a non-belligerent religion, family and local chief, which was stronger than any identity they might have with a more remote prince or 'nation'.

Bibliography

Chakrabarti, Shubra & Patnaik, Utsa (2018). Agrarian and other histories: Essays for Binay Bhushan Chaudhuri. Colombia University Press
Hickel, Jason (2018). How the British stole $45 trillion from India. The Guardian
Bhuyan, Aroonim & Sharma, Krishan (2019). The Great Loot: How the British stole $45 trillion from India. Indiapost
Monbiot, George (2020). English Landowners have stolen our rights. It is time to reclaim them. The Guardian
Tsjeng, Zing (2020). How Britain Stole $45 trillion from India with trains | Empires of Dirt. Vice
Chaudhury, Dipanjan (2019). British looted $45 trillion from India in today’s value: Jaishankar. The Economic Times
Roy, Tirthankar (2019). How British rule changed India's economy: The Paradox of the Raj. Palgrave Macmillan
Patnaik, Utsa (2018). How the British impoverished India. Hindustan Times
Tuovila, Alicia (2019). Expenditure method. Investopedia
Dewey, Clive (2019). Changing the guard: The dissolution of the nationalist–Marxist orthodoxy in the agrarian and agricultural history of India. The Indian Economic & Social History Review
Chandra, Bipan et al. (1989). India's Struggle for Independence, 1857-1947. Penguin Books
Frankema, Ewout & Booth, Anne (2019). Fiscal Capacity and the Colonial State in Asia and Africa, c. 1850-1960. Cambridge University Press
Dalal, Sucheta (2019). IL&FS Controversy: Centre is Paying Up on Sovereign Guarantees to ADB, KfW for Group's Loan. TheWire
Chaudhuri, K.N. (1983). X - Foreign Trade and Balance of Payments (1757–1947). Cambridge University Press
Sunderland, David (2013). Financing the Raj: The City of London and Colonial India, 1858-1940. Boydell Press
Dewey, Clive (1978). Patwari and Chaukidar: Subordinate officials and the reliability of India’s agricultural statistics. Athlone Press
Smith, Lisa (2015). The great Indian calorie debate: Explaining rising undernourishment during India’s rapid economic growth. Food Policy
Duh, Josephine & Spears, Dean (2016). Health and Hunger: Disease, Energy Needs, and the Indian Calorie Consumption Puzzle. The Economic Journal
Vankatesh, P. et al. (2016). Relationship between Food Production and Consumption Diversity in India – Empirical Evidences from Cross Section Analysis. Agricultural Economics Research Review
Gupta, Shaibal (1980). Potential of Industrial Revolution in Pre-British India. Economic and Political Weekly
Raychaudhuri, Tapan (1983). I - The mid-eighteenth-century background. Cambridge University Press
Yasuba, Yasukichi (1986). Standard of Living in Japan Before Industrialization: From what Level did Japan Begin? A Comment. The Journal of Economic History
Tomblinson, B.R. (1985). Writing History Sideways: Lessons for Indian Economic Historians from Meiji Japan. Cambridge University Press
Rajan, M.S. (1969). The Impact of British Rule in India. Journal of Contemporary History
Bryant, G.J. (2000). Indigenous Mercenaries in the Service of European Imperialists: The Case of the Sepoys in the Early British Indian Army, 1750-1800. War in History
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We are live! Get your hands on Level01, the World’s 1st DeFi Platform with AI-Guided Derivatives Trading.

We are live! Get your hands on Level01, the World’s 1st DeFi Platform with AI-Guided Derivatives Trading.
https://preview.redd.it/6yikxzprbhs51.jpg?width=526&format=pjpg&auto=webp&s=49f372132681d480c122fdcf07dfb85d7821346e
We are live! Get your hands on Level01, the World’s 1st DeFi Platform with AI-Guided Derivatives Trading. You can try either Demo trading or Real Money trading. We provide free 10,000 LVX demo token for you to experience trading with our FairSense AI guidance without risk.
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Download and try it, https://play.google.com/store/apps/details...
Quickstart Guide: https://level01.io/quickstart-trading-guide/
Web: https://Level01.io
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One more day to our main app launch! Get ready for real money trading.

One more day to our main app launch! Get ready for real money trading.
https://preview.redd.it/7xixflx2szr51.jpg?width=526&format=pjpg&auto=webp&s=122f8cb099cbe0ce621fbd538e0cf0f432ec587b
Level01 is the World’s 1st DeFi Platform with AI-Guided Derivatives Trading.
- Clear, Transparent and Fair Options Trading DApp - Decentralized: Peer to peer options trading for more profits - Trade Fairly: FairSense AI calculates contract Risk/Reward - Reliable Data from Bloomberg and Thomson Reuters - Control your own funds: Trade mobile app includes non-custodial private wallet - Blockchain-based smart contracts for transparency and reliability - No tampering: Settlement finality on ETH blockchain - Trade In Multiple Markets: Forex, Crypto, Commodity - Easy To Use: Generate profits from price movements, hedging or insurance.
Download and try it, https://play.google.com/store/apps/details...
Quickstart Guide: https://level01.io/quickstart-trading-guide/
Web: https://Level01.io
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Our main app will be launched on 10 October 2020

Our main app will be launched on 10 October 2020
https://preview.redd.it/qxk5wf6tpsr51.jpg?width=1080&format=pjpg&auto=webp&s=450016dd1557e59309586b0db0b8ca92fa585d3a
Level01 is the World’s 1st DeFi Platform with AI-Guided Derivatives Trading. Our main app will be launched on 10 October 2020. Get ready for real money trading. ☑ Clear, Transparent and Fair Options Trading DApp ☑ Decentralized: Peer to peer options trading for more profits ☑ Trade Fairly: FairSense AI calculates contract Risk/Reward ☑ Reliable Data from Bloomberg and Thomson Reuters ☑ Control your own funds: Trade mobile app includes non-custodial private wallet ☑ Blockchain-based smart contracts for transparency and reliability ☑ No tampering: Settlement finality on ETH blockchain ☑ Trade In Multiple Markets: Forex, Crypto, Commodity ☑ Easy To Use: Generate profits from price movements, hedging or insurance.
Download and try it, https://play.google.com/store/apps/details?id=io.level01.android Quickstart Guide: https://level01.io/quickstart-trading-guide/ Web: https://Level01.io
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Integration with Financial Excel Add-In – Excel Price Feed

Integration with Financial Excel Add-In – Excel Price Feed

https://preview.redd.it/j4acwxvwfvr51.jpg?width=1920&format=pjpg&auto=webp&s=77df789ef696a2cdecf2e3266b550083ade09d59
Today we are happy to announce an integration with the financial Excel add-in – Excel Price Feed. Excel Price Feed is easy to use and featureful add-in for Excel owned and distributed by Coderun Technologies Ltd. It was launched in early 2019 and is regularly updated with new features, for EOD Historical Data the add-in has excellent support of Fundamental and End of Day APIs.
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  • Excel Price Feed is an Add-in that includes 100+ new Excel formulas for live, historical, and fundamental market data.
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Please note that you should have both subscriptions to use this plugin with our data: from EOD Historical Data and from Excel Price Feed. Our subscriptions do not include add-in licensing and it should be ordered separately.
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Factset DD

Factset: How You can Invest in Hedge Funds’ Biggest Investment
Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists
If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now:
Their latest 8k filing reported the following:
Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions.
Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region
Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic.
Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019.
Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results.
The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020.
FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders.
As you can see, there’s not much of a negative sign in sight here.
It makes sense considering how FactSet’s FCF has never slowed down
FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with.
Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis:
https://www.investopedia.com/terms/f/factset.asp

FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015:

So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33%

EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded.

P/E has declined in the past 2 years, making it a great time to buy.

Increasing ROE despite lowering of leverage post 2016

Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself.

SGA expense/Gross profit has been declining despite expansion of offices
I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful.
Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in.
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With Bitcoin Suddenly Surging, Canaan Stock Is Also Going Up Today

With Bitcoin Suddenly Surging, Canaan Stock Is Also Going Up Today



By signing up, you may receive emails concerning CoinDesk products and you agree to our terms & conditions and privacy policSTER ON THE SITE
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Do celebrities recommend the Bitcoin trader software?

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perior over different cryptocurrencies?
LATESTBITCOINETHEREUMALTCOINSTECHNOLOGYADOPTIONBLOCKCHAINEVENTSCONTACT
PRESS RELEASEWhy is Bitcoin superior over different cryptocurrencies?Akshay KSPublished a pair of weeks agoon August 12, 2020By Akshay KS
Source: Pixabay
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Bitcoin is that the one method of creating transactions daily as alternative currencies. But it's its options and uniqueness that make it superior. Bitcoin and different currencies are based mostly on the cryptographic algorithms or mathematics that are encrypted, with that the user becomes the owner of the currency. Bitcoin currencies are easily accessible at Bitcoin ATM and online exchange
The main feature of the bitcoin, which makes it superior is that it is the safest option for digital transactions. These will be used for on-line searching and transfer of money too.
There are many alternative blessings to using bitcoin. A number of them are mentioned below
Decentralized and digital
Bitcoin offers the freedom of exchanging the price without representatives that proves helpful in controlling the lower fees and high funds. Bitcoin is that the faster method of transaction than others. It is secure as it is free from theft and frauds and is constant. The main advantage is that bitcoin has its homeowners whereas the bank controls the money.
Makes online looking
Normally, bitcoin will be used for on-line shopping too. Bitcoin is the opposite face of e-wallet, that is created by blockchain technology that is used to store money and will easily pay everywhere digitally. For this reason, it also makes your searching easy by which you'll be able to look from your home solely

Bitcoin is accepted globally at each corner of the planet, which makes it less volatile than local currencies or cash. This feature makes it superior because it enables us to form transactions on-line and across the boundaries
Bitcoin unable the means of tracking cash

https://preview.redd.it/4vpws3gtz9j51.jpg?width=1280&format=pjpg&auto=webp&s=179af0fcc33f85322d48b6be65fce2e4442c6cd6
Bitcoin is created by blockchain technology. Blockchain is the sole technology which will either make it or break it. There are many computers which are used to keep up a permanent record of each bitcoin transactions with the help of cryptographic technique. In this approach, it becomes a lot of valuable together with the tracking of the payment. At the same time, there's no method of tracking the cash

While not any transformation method, it will be used over the entire world. It provides the simplest platform for the investment as it is free from the restrictions of governments or banks. It provides an open market and combines the simplest of gold and money.

Bitcoin provides the power to access the balance of the users with a password which is named a personal key. It additionally permits the exchange of values through the web without any middle person. Thus, bitcoin becomes safer, stuffed with privacy, and open to everyone
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Bitcoin Freedom failed to allow two persons to transact on the one price. Once the bitcoin is transferred, its possession is also transferred. So this is the simple approach of maintaining records for any tax functions. It conjointly makes it a easy and healthier metho

Bitcoin is the foremost reliable manner of online transactions. Many questions arise in folks’s minds that are solved on websites like bitcoin revolution. One in all them was the above-mentioned question. Bitcoin provides many facilities, and it comes with more and a lot of blessings which makes it distinctive and special over different cryptocurrencies. It can be preferred as the simplest digital platform for transac


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Disclaimer: AMBCrypto US and UK Market's content is informational in nature and is not meant to be investment advice. Buying, trading or selling crypto-currencies ought to be considered a high-risk investment and every reader is advised to do their due diligence before making any decisions.
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Browse the FAQ'sn news, CoinDesk is a media outlet that strives for the very best journalistic standards and abides by a strict set of editorial policies. CoinDesk is an independent operating subsidiary of Digital Currency Group, which invests in cryptocurrencies and blockchain startups.

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https://www.cryptoerapro.com/bitcoin-freedom/
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ADVICE FOR THE WISE - AUGUST 2020

FROM THE CEO’s DESK
Dear Investors, “Behind every dark cloud there is an every-shining sun. Just wait. In time, the cloud will pass.” Marianne Williamson. All inclusive, economies are seeing recuperation with pointers, for example, PMI showing an improvement in spite of infection resurgence in a couple of nations. U.S., Euro, and China manufacturing activities have picked up pace, with July numbers in these three regions crossing 50 mark, indicating expansion. Financial and monetary policies remain exceptionally accommodative, and liquidity remains buoyant, which should provide continued support for further economic recovery. Equity market declines provide opportunities to buy better stocks at lower valuations. We foresee this slowdown and the year 2020 from an investment opportunity viewpoint rather than worrying, as the risk-reward ratio in the current scenario is in favour of equity investments. The current positive outlook on the global markets is well backed by negative real rates, expansion of the central bank balance sheet along with growth recovery and medical progress on COVID-19 While there is a growing increase in the number of COVID cases on the domestic front, there has been an improvement in the recovery rate; in India it is about 68.41 percent while 64.05 percent globally. Early signs of pent-up demand are visible in the economy as indicated by high frequency indicators. Expected normal monsoon and higher sowing of Kharif crops YoY gives us the solace that the rural economy will play a major part in the future economic growth. Other macro factors such as low oil prices and stable currency, high forex reserves and current-account surplus will act as tailwinds for the domestic equity market. Expectations of the Q1 FY21 earnings to bottom out by FY21, while the economy and earnings are expected to normalize by FY23 keeping in mind the current low interest rate scenario and high liquidity, supports valuations. With the declining dollar index and humongous global liquidity we expect the money to flow into EMs. In July, the domestic equity market kept witnessing strong FII inflows coupled with steady SIP flows in mutual funds.
Know more - http://www.karvywealth.com/data/sites/1/skins/karvywealth/Download_media_report.aspx?FileName=35269F8C-8C0A-4624-9FED-793AD0998167|5252655
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The World This Week 10th July 2020 – 17th July 2020

Indian Equity Summary-
· Sensex ended higher by 1.2 percent as the bullish trend persisted for the fifth consecutive week in the domestic equity market ,on the back ofØ positive global cues and optimism over the development of Covid-19 vaccine .The focus is now turning to Q1FY21 earning season and more importantly for guidance and viewpoints of management.
· Going forward, global factors like development on the US -China relationship front , any resurgence of Covid-19 cases globally, as economiesØ have started opening up ; will continue to dictate the trend of the domestic equity market. We expect the trading range for Nifty between 10800-11200 in the near term.
Indian Debt Market-
· The bond prices fell as the yield on the latest 10-year benchmark 5.79% 2030 paper settled at 5.80% on Jul 17 compared with 5.76% on Jul 10.Ø
· Reserve Bank of India announces the auction of three Government of India 91day, 182 day and 364 day Treasury Bills for an aggregate amount ofØ ₹35,000, to be conducted on 22nd July 2020.
· State Governments announced to sell securities by way of an auction to be conducted on 21th July 2020, for an aggregate face value of ₹ 9,000 Cr.Ø
· We expect that RBI will be in wait and watch mood before taking any major decision of rate cut on the back of recent inflation print.Ø
· We expect the 10 year benchmark yield to trade between 5.80-6.05% in near term.Ø
Domestic News
· India’s retail trade has suffered a business loss of about Rs 15.5 lakh crore in past 100 days due to the COVID-19 pandemic as per theØ Confederation of All India Traders (CAIT).
· The Foreign Direct Investment (FDI) from the US to India has crossed the $40 billion mark as on year to date, reflecting the growing confidence ofØ American companies in the country.
· Forex reserves rose by $3.1 billion on a WoW basis to hit a record high of $516.36 billion for the week ended July 10, according to Reserve BankØ of India (RBI).
· According to the latest data released by the Ministry of StatisticsØ & Programme Implementation (MoSPI), India’s retail inflation(CPI) grew to 6.09% in the month of June as against the prior released figure of 5.84 in April for the month of March.
International News
· Hong Kong's April-June unemployment rises to 6.2%, being the highest in over 15 years.Ø
· Japan’s exports plunged 26.2% in June while Imports fell by 14.4% in June on a year on year basis , as per the data released byØ Ministry of Finance (MOF).
· Foreign direct investment (FDI) into China fell 1.3% in the first half of this year from a year earlier to 472.18 billion yuan ($67.47Ø billion)as per China’s commerce ministry.
· Gross domestic product (GDP) of China rose to 3.2% in the second-quarter from a year earlier as per the National Bureau ofØ Statistics, faster than the 2.5% forecast by analysts in a Reuters poll, with the easing of lockdown measures and ramping up of stimulus by policymakers to combat the virus-led downturn.
· US GDP is expected to contract by an annualised rate of 37% in the Q2 2020 and by 6.6%for 2020 as a whole as per theØ International Monetary Fund (IMF) staff.
Link - http://www.karvywealth.com/data/sites/1/skins/karvywealth/Download_media_report.aspx?FileName=B98EB615-C7D5-409D-AFF1-05C92C06DBE4|5234282
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on the fakeness of the internet

funny to see that subject pop up again. it was what drove me insane enough to find this sub in the first place.
at any rate, the problem is not the bots. I thought it was, but those are just part of the parasitic ecosystem.
but to get that, first we need to take a few steps back on web history, ad serving, UX, tracking technology and media advertising.
too lazy to gather links, but you know, do your googlin'.
I assume that most of you are fairly web literate here, but I'll try to go down into the bare bones as much as possible for those who aren't.
so let's start with a basic question - what is a web visitor anyway?
from the standpoint of a normal person, that would be a person browsing a given website or piece of content. from the standpoint of technology however all you know is that some device has downloaded content from your server using the http protocol. thanks to the wonderful technology of web browsers, you can plant browser cookies on a visitor - stuff that's used to remember if they logged in, what their preferences are, stuff that your service can read from the device. it also serves usually very basic telemetry like last visit time, session time, and so on.
this, over time has evolved in what we call browser fingerprinting, a convoluted bunch of technology that allows websites and web services to uniquely identify you.
it still doesn't know if you're a human or not, but from the standpoint of the web technology, you're a visitor.
now back in ye old days of the web, when the first banner ads were springing up, these were important questions. most consumers were still to be reached on traditional media channels, and ad spend would have to be justified somehow on the risky ventures of online business. so beyond traditional polls that would infer the value of visitors, websites would start tracking number of visitors, time on page and so on. these were used to milk the advertising cow so to speak, and it gave in to some funny developments like the creation of the popup ad - if I recon correctly on geocities, where they would just but the ads everywhere until some big auto company noticed that they're appearing on porn sites. so - put the ad in the popup, and you can claim it's not in the context of porn!
around this point in time the online ad business is still pretty low tech. you actually have to call a physical human being, they send you ppts and pdfs, you send back image files and excel sheets, you wire money, the ads run, and so on. this is called direct sales, and it's tracked again by counting a bunch of visitors, and telling you how much impressions and clicks your marvelous creatives and ad budget generated.
now enter google - or more precisely, a technology firm called doubleclick that was to be acquired by google. they developed a tool for automatic ad serving, later to be called programmatic advertising, that keeps the pesky sales dude out of the loop and achieves reasonable amounts of scale for a more hefty price - after all, if the sales are automated, you get a bidding war for attention between different advertisers, and you're paying for clicks.
so you can see how this was a strategic move for google - they already had the most valuable data available in this situation. they were seeing in real time what people were searching for, and using the programmatic ad serving system, you could effectively bid not just for general attention - but for attention with an intent to buy.
...and the way that google got this data is because they indexed the web, using bots. at least GoogleBot would identify itself as a site visitor, but in the meantime they developed a service for websites to comprehensively track their own visitors and where they were coming from and what they were doing on your website. incidentally, you could also put on google's ads on your webpage to earn quite a bit of money, as content relevant ads would be shown through the doubleclick system.
this kicked off two things:
one, the ability to classify your website visitors into different clusters and segments allowed businesses to start tailoring the appearance of the website or service to fit that specific audience segment, starting off the great fracture - segmentation of the web (in the sense that two people viewing the same website at the same time were not seeing the same thing)
two, it created a very strong financial incentive for people to trick google into thinking they were having actual human visitors that would click on ads, when in fact they were bots. in an even funnier twist, some of them were from browser hijackers, commonly known as malware at the time, which google cross-financed. look up download valley and crossrider.
at the cross section of the above two, you had one interesting twist: websites that would appear differently to the security bots or the compliance officers of Google as they would to fake visitors or malware jacked human beings. the former would get a benign looking website, while the latter would get bombarded with auto clicking ads.
this kicked off the billion dollar arms race called online advertising fraud.
I'm not here to shed a tear for big money corps bleeding money. the real fallout lay somewhere else, but for that you have to understand that you never really saw the real internet, you only saw your corner and the one that was personalized for you.
but if you ever had the pleasure of watching daytime TVs or off channels and witnessing the ads, you could kind of infer what kind of audience must be watching these shows generally. from quite clear rip offs to magic number lotteries and television fortune telling, these sorts of programming was aimed at the most gullible, bought for pennies, where the smallest audience portion had to be converted into a money making operation.
...and with audience segmentation and data gathering, that was now possible at unprecedented scale, automatically. so big was the scale in fact, that it gave birth to an entire new beast of an industry called affiliate marketing, where instead of a regular payroll, you'd get a cut of the sale should you figure out an angle on where to push whatever fucking bullshit the vendors were offering to whoever the fuck would be dumb enough to click on an ad and buy. (the funniest story I recall was someone pulling five figures a month because he figured out that if you buy ads on anime-hentai pages and sell PUA shit courses and e-books you'd make a killing)
at any rate, affiliate marketing brought with it the killer landing page, the thing that's supposed to hammer the nail in the coffin once you get through the banner ad. the earliest form of deceptiveness in memory comes from various pirate sites, that had fake download buttons as banner ads and virus alerts as the landing pages. but then at some point, some schmuck realized that for certain type of products, like diet pills or forex trading or whatever, the best lander is in fact a fake news page that comes packed with comments and all. that would convert like crazy, because it had the appearance of social proof.
until at least the lawsuits came raining down, and these sorts of landing pages and campaigns for being banned left right and centre on all platforms. which just launched a new arms race as the campaigns would be disguised for the bots doing the checkups, and aged facebook profiles would start selling for like 5K USD - these people were making 30-40k a day, they could afford to spend that much to continue running the shop.
speaking of facebook - it came just about the right time for the shit to brew max total. first they were unprecedented in the amount of data they were getting off of their users, and they came just in time to catch the full swing of what we call the 'responsive web' - that no user at the same time would see the same thing on their page, it was all allocated through an intricate web of recommendations, running real time, based on previously gathered and forecast behavioral data.
it also ran on one simple premise: take over the starting page position from google for most people, then they do not have to justify, ever, any ad spend that takes place on their platform, as long as it performs. furthermore, it was completely lacking any revenue share sort of scheme (save for the short period of facebook gaming, see Zynga), thus there was no incentive for the amount of bot traffic that the previous internet era had bred. instead, it came with an entirely different one - bots that would offer social proof in the way of shares and likes, but would not directly risk the business model, thus giving no incentive for facebook to fight them. (note that google didn't do much jack shit either besides indiscriminately penalizing websites it deemed suspicious when they reached critical payout thresholds)
the rest of the story you kind of sort of know. how the obama campaign was brilliant in using the new social media to inspire hope and blah blah blah, kicking the door open for big money politics who could hire the best snake oil salesmen in the market, who had the data and as you can see from the above, had the ethical standards of a shoe. at around 2014-2015 the press (the mainstream media) started to raise question about the duopoly, the buzzword of filter bubbles started appearing, not entirely unrelated to the fact that facebook by this time cannibalized their traffic with a fucking embedded share / like button and started charging money for them to reach their own audience. after 2016 the cries of fake news were everywhere, because there was no online space left which everyone was viewing the same way, and you had no way to verify what the person next to you was looking at.
since then, we've all become grandpa yelling at the television set, with nobody around us seeing what we're seeing on the screen, so we're being accused as bots and looking for bots under the carpet.
but it's been a long way coming, and the bots are honestly the least of our worries. trust me, I went bankrupt over that one. truth or fake doesn't even begin to describe the magnitude of the problem: more like we entered the phase where every word, event or picture is defined by who ever the fuck wins the auction over it, as the marketers of human attention grind the gears of the money mill without even understanding how fast they're digging towards hell.
don't believe me? look around the marketing and advertising related subs these days. the priests are eating the indulgences, and we're only now entering the period of deep fakes, good algo generated audio and good enough NLP. and in the meantime, the shadowrunners running up between two corp headquarter-highrises are skinning your belief systems.
so the best you can do is really, not litter the remnants of cyberspace which are not being mined, astroturfed or being pulled apart by the algos. no human connections on a nuclear trash heap mate.
submitted by gergo_v to sorceryofthespectacle [link] [comments]

Hibiscus Petroleum Berhad (5199.KL)


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Download PDF of this article here: https://docdro.id/6eLgUPo
In light of the recent fall in oil prices due to the Saudi-Russian dispute and dampening demand for oil due to the lockdowns implemented globally, O&G stocks have taken a severe beating, falling approximately 50% from their highs at the beginning of the year. Not spared from this onslaught is Hibiscus Petroleum Berhad (Hibiscus), a listed oil and gas (O&G) exploration and production (E&P) company.
Why invest in O&G stocks in this particularly uncertain period? For one, valuations of these stocks have fallen to multi-year lows, bringing the potential ROI on these stocks to attractive levels. Oil prices are cyclical, and are bound to return to the mean given a sufficiently long time horizon. The trick is to find those companies who can survive through this downturn and emerge into “normal” profitability once oil prices rebound.
In this article, I will explore the upsides and downsides of investing in Hibiscus. I will do my best to cater this report to newcomers to the O&G industry – rather than address exclusively experts and veterans of the O&G sector. As an equity analyst, I aim to provide a view on the company primarily, and will generally refrain from providing macro views on oil or opinions about secular trends of the sector. I hope you enjoy reading it!
Stock code: 5199.KL
Stock name: Hibiscus Petroleum Berhad
Financial information and financial reports: https://www.malaysiastock.biz/Corporate-Infomation.aspx?securityCode=5199
Company website: https://www.hibiscuspetroleum.com/

Company Snapshot

Hibiscus Petroleum Berhad (5199.KL) is an oil and gas (O&G) upstream exploration and production (E&P) company located in Malaysia. As an E&P company, their business can be basically described as:
· looking for oil,
· drawing it out of the ground, and
· selling it on global oil markets.
This means Hibiscus’s profits are particularly exposed to fluctuating oil prices. With oil prices falling to sub-$30 from about $60 at the beginning of the year, Hibiscus’s stock price has also fallen by about 50% YTD – from around RM 1.00 to RM 0.45 (as of 5 April 2020).
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While the company is domiciled in Malaysia, its two main oil producing fields are located in both Malaysia and the UK. The Malaysian oil field is commonly referred to as the North Sabah field, while the UK oil field is commonly referred to as the Anasuria oil field. Hibiscus has licenses to other oil fields in different parts of the world, notably the Marigold/Sunflower oil fields in the UK and the VIC cluster in Australia, but its revenues and profits mainly stem from the former two oil producing fields.
Given that it’s a small player and has only two primary producing oil fields, it’s not surprising that Hibiscus sells its oil to a concentrated pool of customers, with 2 of them representing 80% of its revenues (i.e. Petronas and BP). Fortunately, both these customers are oil supermajors, and are unlikely to default on their obligations despite low oil prices.
At RM 0.45 per share, the market capitalization is RM 714.7m and it has a trailing PE ratio of about 5x. It doesn’t carry any debt, and it hasn’t paid a dividend in its listing history. The MD, Mr. Kenneth Gerard Pereira, owns about 10% of the company’s outstanding shares.

Reserves (Total recoverable oil) & Production (bbl/day)

To begin analyzing the company, it’s necessary to understand a little of the industry jargon. We’ll start with Reserves and Production.
In general, there are three types of categories for a company’s recoverable oil volumes – Reserves, Contingent Resources and Prospective Resources. Reserves are those oil fields which are “commercial”, which is defined as below:
As defined by the SPE PRMS, Reserves are “… quantities of petroleum anticipated to be commercially recoverable by application of development projects to known accumulations from a given date forward under defined conditions.” Therefore, Reserves must be discovered (by drilling, recoverable (with current technology), remaining in the subsurface (at the effective date of the evaluation) and “commercial” based on the development project proposed.)
Note that Reserves are associated with development projects. To be considered as “commercial”, there must be a firm intention to proceed with the project in a reasonable time frame (typically 5 years, and such intention must be based upon all of the following criteria:)
- A reasonable assessment of the future economics of the development project meeting defined investment and operating criteria; - A reasonable expectation that there will be a market for all or at least the expected sales quantities of production required to justify development; - Evidence that the necessary production and transportation facilities are available or can be made available; and - Evidence that legal, contractual, environmental and other social and economic concerns will allow for the actual implementation of the recovery project being evaluated.
Contingent Resources and Prospective Resources are further defined as below:
- Contingent Resources: potentially recoverable volumes associated with a development plan that targets discovered volumes but is not (yet commercial (as defined above); and) - Prospective Resources: potentially recoverable volumes associated with a development plan that targets as yet undiscovered volumes.
In the industry lingo, we generally refer to Reserves as ‘P’ and Contingent Resources as ‘C’. These ‘P’ and ‘C’ resources can be further categorized into 1P/2P/3P resources and 1C/2C/3C resources, each referring to a low/medium/high estimate of the company’s potential recoverable oil volumes:
- Low/1C/1P estimate: there should be reasonable certainty that volumes actually recovered will equal or exceed the estimate; - Best/2C/2P estimate: there should be an equal likelihood of the actual volumes of petroleum being larger or smaller than the estimate; and - High/3C/3P estimate: there is a low probability that the estimate will be exceeded.
Hence in the E&P industry, it is easy to see why most investors and analysts refer to the 2P estimate as the best estimate for a company’s actual recoverable oil volumes. This is because 2P reserves (‘2P’ referring to ‘Proved and Probable’) are a middle estimate of the recoverable oil volumes legally recognized as “commercial”.
However, there’s nothing stopping you from including 2C resources (riskier) or utilizing 1P resources (conservative) as your estimate for total recoverable oil volumes, depending on your risk appetite. In this instance, the company has provided a snapshot of its 2P and 2C resources in its analyst presentation:
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Basically, what the company is saying here is that by 2021, it will have classified as 2P reserves at least 23.7 million bbl from its Anasuria field and 20.5 million bbl from its North Sabah field – for total 2P reserves of 44.2 million bbl (we are ignoring the Australian VIC cluster as it is only estimated to reach first oil by 2022).
Furthermore, the company is stating that they have discovered (but not yet legally classified as “commercial”) a further 71 million bbl of oil from both the Anasuria and North Sabah fields, as well as the Marigold/Sunflower fields. If we include these 2C resources, the total potential recoverable oil volumes could exceed 100 million bbl.
In this report, we shall explore all valuation scenarios giving consideration to both 2P and 2C resources.
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The company further targets a 2021 production rate of 20,000 bbl (LTM: 8,000 bbl), which includes 5,000 bbl from its Anasuria field (LTM: 2,500 bbl) and 7,000 bbl from its North Sabah field (LTM: 5,300 bbl).
This is a substantial increase in forecasted production from both existing and prospective oil fields. If it materializes, annual production rate could be as high as 7,300 mmbbl, and 2021 revenues (given FY20 USD/bbl of $60) could exceed RM 1.5 billion (FY20: RM 988 million).
However, this targeted forecast is quite a stretch from current production levels. Nevertheless, we shall consider all provided information in estimating a valuation for Hibiscus.
To understand Hibiscus’s oil production capacity and forecast its revenues and profits, we need to have a better appreciation of the performance of its two main cash-generating assets – the North Sabah field and the Anasuria field.

North Sabah oil field
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Hibiscus owns a 50% interest in the North Sabah field together with its partner Petronas, and has production rights over the field up to year 2040. The asset contains 4 oil fields, namely the St Joseph field, South Furious field, SF 30 field and Barton field.
For the sake of brevity, we shall not delve deep into the operational aspects of the fields or the contractual nature of its production sharing contract (PSC). We’ll just focus on the factors which relate to its financial performance. These are:
· Average uptime
· Total oil sold
· Average realized oil price
· Average OPEX per bbl
With regards to average uptime, we can see that the company maintains relative high facility availability, exceeding 90% uptime in all quarters of the LTM with exception of Jul-Sep 2019. The dip in average uptime was due to production enhancement projects and maintenance activities undertaken to improve the production capacity of the St Joseph and SF30 oil fields.
Hence, we can conclude that management has a good handle on operational performance. It also implies that there is little room for further improvement in production resulting from increased uptime.
As North Sabah is under a production sharing contract (PSC), there is a distinction between gross oil production and net oil production. The former relates to total oil drawn out of the ground, whereas the latter refers to Hibiscus’s share of oil production after taxes, royalties and expenses are accounted for. In this case, we want to pay attention to net oil production, not gross.
We can arrive at Hibiscus’s total oil sold for the last twelve months (LTM) by adding up the total oil sold for each of the last 4 quarters. Summing up the figures yields total oil sold for the LTM of approximately 2,075,305 bbl.
Then, we can arrive at an average realized oil price over the LTM by averaging the average realized oil price for the last 4 quarters, giving us an average realized oil price over the LTM of USD 68.57/bbl. We can do the same for average OPEX per bbl, giving us an average OPEX per bbl over the LTM of USD 13.23/bbl.
Thus, we can sum up the above financial performance of the North Sabah field with the following figures:
· Total oil sold: 2,075,305 bbl
· Average realized oil price: USD 68.57/bbl
· Average OPEX per bbl: USD 13.23/bbl

Anasuria oil field
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Doing the same exercise as above for the Anasuria field, we arrive at the following financial performance for the Anasuria field:
· Total oil sold: 1,073,304 bbl
· Average realized oil price: USD 63.57/bbl
· Average OPEX per bbl: USD 23.22/bbl
As gas production is relatively immaterial, and to be conservative, we shall only consider the crude oil production from the Anasuria field in forecasting revenues.

Valuation (Method 1)

Putting the figures from both oil fields together, we get the following data:
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Given that we have determined LTM EBITDA of RM 632m, the next step would be to subtract ITDA (interest, tax, depreciation & amortization) from it to obtain estimated LTM Net Profit. Using FY2020’s ITDA of approximately RM 318m as a guideline, we arrive at an estimated LTM Net Profit of RM 314m (FY20: 230m). Given the current market capitalization of RM 714.7m, this implies a trailing LTM PE of 2.3x.
Performing a sensitivity analysis given different oil prices, we arrive at the following net profit table for the company under different oil price scenarios, assuming oil production rate and ITDA remain constant:
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From the above exercise, it becomes apparent that Hibiscus has a breakeven oil price of about USD 41.8863/bbl, and has a lot of operating leverage given the exponential rate of increase in its Net Profit with each consequent increase in oil prices.
Considering that the oil production rate (EBITDA) is likely to increase faster than ITDA’s proportion to revenues (fixed costs), at an implied PE of 4.33x, it seems likely that an investment in Hibiscus will be profitable over the next 10 years (with the assumption that oil prices will revert to the mean in the long-term).

Valuation (Method 2)

Of course, there are a lot of assumptions behind the above method of valuation. Hence, it would be prudent to perform multiple methods of valuation and compare the figures to one another.
As opposed to the profit/loss assessment in Valuation (Method 1), another way of performing a valuation would be to estimate its balance sheet value, i.e. total revenues from 2P Reserves, and assign a reasonable margin to it.
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From the above, we understand that Hibiscus’s 2P reserves from the North Sabah and Anasuria fields alone are approximately 44.2 mmbbl (we ignore contribution from Australia’s VIC cluster as it hasn’t been developed yet).
Doing a similar sensitivity analysis of different oil prices as above, we arrive at the following estimated total revenues and accumulated net profit:
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Let’s assume that the above average of RM 9.68 billion in total realizable revenues from current 2P reserves holds true. If we assign a conservative Net Profit margin of 15% (FY20: 23%; past 5 years average: 16%), we arrive at estimated accumulated Net Profit from 2P Reserves of RM 1.452 billion. Given the current market capitalization of RM 714 million, we might be able to say that the equity is worth about twice the current share price.
However, it is understandable that some readers might feel that the figures used in the above estimate (e.g. net profit margin of 15%) were randomly plucked from the sky. So how do we reconcile them with figures from the financial statements? Fortunately, there appears to be a way to do just that.
Intangible Assets
I refer you to a figure in the financial statements which provides a shortcut to the valuation of 2P Reserves. This is the carrying value of Intangible Assets on the Balance Sheet.
As of 2QFY21, that amount was RM 1,468,860,000 (i.e. RM 1.468 billion).
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Quite coincidentally, one might observe that this figure is dangerously close to the estimated accumulated Net Profit from 2P Reserves of RM 1.452 billion we calculated earlier. But why would this amount matter at all?
To answer that, I refer you to the notes of the Annual Report FY20 (AR20). On page 148 of the AR20, we find the following two paragraphs:
E&E assets comprise of rights and concession and conventional studies. Following the acquisition of a concession right to explore a licensed area, the costs incurred such as geological and geophysical surveys, drilling, commercial appraisal costs and other directly attributable costs of exploration and appraisal including technical and administrative costs, are capitalised as conventional studies, presented as intangible assets.
E&E assets are assessed for impairment when facts and circumstances suggest that the carrying amount of an E&E asset may exceed its recoverable amount. The Group will allocate E&E assets to cash generating unit (“CGU”s or groups of CGUs for the purpose of assessing such assets for impairment. Each CGU or group of units to which an E&E asset is allocated will not be larger than an operating segment as disclosed in Note 39 to the financial statements.)
Hence, we can determine that firstly, the intangible asset value represents capitalized costs of acquisition of the oil fields, including technical exploration costs and costs of acquiring the relevant licenses. Secondly, an impairment review will be carried out when “the carrying amount of an E&E asset may exceed its recoverable amount”, with E&E assets being allocated to “cash generating units” (CGU) for the purposes of assessment.
On page 169 of the AR20, we find the following:
Carrying amounts of the Group’s intangible assets, oil and gas assets and FPSO are reviewed for possible impairment annually including any indicators of impairment. For the purpose of assessing impairment, assets are grouped at the lowest level CGUs for which there is a separately identifiable cash flow available. These CGUs are based on operating areas, represented by the 2011 North Sabah EOR PSC (“North Sabah”, the Anasuria Cluster, the Marigold and Sunflower fields, the VIC/P57 exploration permit (“VIC/P57”) and the VIC/L31 production license (“VIC/L31”).)
So apparently, the CGUs that have been assigned refer to the respective oil producing fields, two of which include the North Sabah field and the Anasuria field. In order to perform the impairment review, estimates of future cash flow will be made by management to assess the “recoverable amount” (as described above), subject to assumptions and an appropriate discount rate.
Hence, what we can gather up to now is that management will estimate future recoverable cash flows from a CGU (i.e. the North Sabah and Anasuria oil fields), compare that to their carrying value, and perform an impairment if their future recoverable cash flows are less than their carrying value. In other words, if estimated accumulated profits from the North Sabah and Anasuria oil fields are less than their carrying value, an impairment is required.
So where do we find the carrying values for the North Sabah and Anasuria oil fields? Further down on page 184 in the AR20, we see the following:
Included in rights and concession are the carrying amounts of producing field licenses in the Anasuria Cluster amounting to RM668,211,518 (2018: RM687,664,530, producing field licenses in North Sabah amounting to RM471,031,008 (2018: RM414,333,116))
Hence, we can determine that the carrying values for the North Sabah and Anasuria oil fields are RM 471m and RM 668m respectively. But where do we find the future recoverable cash flows of the fields as estimated by management, and what are the assumptions used in that calculation?
Fortunately, we find just that on page 185:
17 INTANGIBLE ASSETS (CONTINUED)
(a Anasuria Cluster)
The Directors have concluded that there is no impairment indicator for Anasuria Cluster during the current financial year. In the previous financial year, due to uncertainties in crude oil prices, the Group has assessed the recoverable amount of the intangible assets, oil and gas assets and FPSO relating to the Anasuria Cluster. The recoverable amount is determined using the FVLCTS model based on discounted cash flows (“DCF” derived from the expected cash in/outflow pattern over the production lives.)
The key assumptions used to determine the recoverable amount for the Anasuria Cluster were as follows:
(i Discount rate of 10%;)
(ii Future cost inflation factor of 2% per annum;)
(iii Oil price forecast based on the oil price forward curve from independent parties; and,)
(iv Oil production profile based on the assessment by independent oil and gas reserve experts.)
Based on the assessments performed, the Directors concluded that the recoverable amount calculated based on the valuation model is higher than the carrying amount.
(b North Sabah)
The acquisition of the North Sabah assets was completed in the previous financial year. Details of the acquisition are as disclosed in Note 15 to the financial statements.
The Directors have concluded that there is no impairment indicator for North Sabah during the current financial year.
Here, we can see that the recoverable amount of the Anasuria field was estimated based on a DCF of expected future cash flows over the production life of the asset. The key assumptions used by management all seem appropriate, including a discount rate of 10% and oil price and oil production estimates based on independent assessment. From there, management concludes that the recoverable amount of the Anasuria field is higher than its carrying amount (i.e. no impairment required). Likewise, for the North Sabah field.
How do we interpret this? Basically, what management is saying is that given a 10% discount rate and independent oil price and oil production estimates, the accumulated profits (i.e. recoverable amount) from both the North Sabah and the Anasuria fields exceed their carrying amounts of RM 471m and RM 668m respectively.
In other words, according to management’s own estimates, the carrying value of the Intangible Assets of RM 1.468 billion approximates the accumulated Net Profit recoverable from 2P reserves.
To conclude Valuation (Method 2), we arrive at the following:

Our estimates Management estimates
Accumulated Net Profit from 2P Reserves RM 1.452 billion RM 1.468 billion

Financials

By now, we have established the basic economics of Hibiscus’s business, including its revenues (i.e. oil production and oil price scenarios), costs (OPEX, ITDA), profitability (breakeven, future earnings potential) and balance sheet value (2P reserves, valuation). Moving on, we want to gain a deeper understanding of the 3 statements to anticipate any blind spots and risks. We’ll refer to the financial statements of both the FY20 annual report and the 2Q21 quarterly report in this analysis.
For the sake of brevity, I’ll only point out those line items which need extra attention, and skip over the rest. Feel free to go through the financial statements on your own to gain a better familiarity of the business.
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Income Statement
First, we’ll start with the Income Statement on page 135 of the AR20. Revenues are straightforward, as we’ve discussed above. Cost of Sales and Administrative Expenses fall under the jurisdiction of OPEX, which we’ve also seen earlier. Other Expenses are mostly made up of Depreciation & Amortization of RM 115m.
Finance Costs are where things start to get tricky. Why does a company which carries no debt have such huge amounts of finance costs? The reason can be found in Note 8, where it is revealed that the bulk of finance costs relate to the unwinding of discount of provision for decommissioning costs of RM 25m (Note 32).
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This actually refers to the expected future costs of restoring the Anasuria and North Sabah fields to their original condition once the oil reserves have been depleted. Accounting standards require the company to provide for these decommissioning costs as they are estimable and probable. The way the decommissioning costs are accounted for is the same as an amortized loan, where the initial carrying value is recognized as a liability and the discount rate applied is reversed each year as an expense on the Income Statement. However, these expenses are largely non-cash in nature and do not necessitate a cash outflow every year (FY20: RM 69m).
Unwinding of discount on non-current other payables of RM 12m relate to contractual payments to the North Sabah sellers. We will discuss it later.
Taxation is another tricky subject, and is even more significant than Finance Costs at RM 161m. In gist, Hibiscus is subject to the 38% PITA (Petroleum Income Tax Act) under Malaysian jurisdiction, and the 30% Petroleum tax + 10% Supplementary tax under UK jurisdiction. Of the RM 161m, RM 41m of it relates to deferred tax which originates from the difference between tax treatment and accounting treatment on capitalized assets (accelerated depreciation vs straight-line depreciation). Nonetheless, what you should take away from this is that the tax expense is a tangible expense and material to breakeven analysis.
Fortunately, tax is a variable expense, and should not materially impact the cash flow of Hibiscus in today’s low oil price environment.
Note: Cash outflows for Tax Paid in FY20 was RM 97m, substantially below the RM 161m tax expense.
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Balance Sheet
The balance sheet of Hibiscus is unexciting; I’ll just bring your attention to those line items which need additional scrutiny. I’ll use the figures in the latest 2Q21 quarterly report (2Q21) and refer to the notes in AR20 for clarity.
We’ve already discussed Intangible Assets in the section above, so I won’t dwell on it again.
Moving on, the company has Equipment of RM 582m, largely relating to O&G assets (e.g. the Anasuria FPSO vessel and CAPEX incurred on production enhancement projects). Restricted cash and bank balances represent contractual obligations for decommissioning costs of the Anasuria Cluster, and are inaccessible for use in operations.
Inventories are relatively low, despite Hibiscus being an E&P company, so forex fluctuations on carrying value of inventories are relatively immaterial. Trade receivables largely relate to entitlements from Petronas and BP (both oil supermajors), and are hence quite safe from impairment. Other receivables, deposits and prepayments are significant as they relate to security deposits placed with sellers of the oil fields acquired; these should be ignored for cash flow purposes.
Note: Total cash and bank balances do not include approximately RM 105 m proceeds from the North Sabah December 2019 offtake (which was received in January 2020)
Cash and bank balances of RM 90m do not include RM 105m of proceeds from offtake received in 3Q21 (Jan 2020). Hence, the actual cash and bank balances as of 2Q21 approximate RM 200m.
Liabilities are a little more interesting. First, I’ll draw your attention to the significant Deferred tax liabilities of RM 457m. These largely relate to the amortization of CAPEX (i.e. Equipment and capitalized E&E expenses), which is given an accelerated depreciation treatment for tax purposes.
The way this works is that the government gives Hibiscus a favorable tax treatment on capital expenditures incurred via an accelerated depreciation schedule, so that the taxable income is less than usual. However, this leads to the taxable depreciation being utilized quicker than accounting depreciation, hence the tax payable merely deferred to a later period – when the tax depreciation runs out but accounting depreciation remains. Given the capital intensive nature of the business, it is understandable why Deferred tax liabilities are so large.
We’ve discussed Provision for decommissioning costs under the Finance Costs section earlier. They are also quite significant at RM 266m.
Notably, the Other Payables and Accruals are a hefty RM 431m. What do they relate to? Basically, they are contractual obligations to the sellers of the oil fields which are only payable upon oil prices reaching certain thresholds. Hence, while they are current in nature, they will only become payable when oil prices recover to previous highs, and are hence not an immediate cash outflow concern given today’s low oil prices.
Cash Flow Statement
There is nothing in the cash flow statement which warrants concern.
Notably, the company generated OCF of approximately RM 500m in FY20 and RM 116m in 2Q21. It further incurred RM 330m and RM 234m of CAPEX in FY20 and 2Q21 respectively, largely owing to production enhancement projects to increase the production rate of the Anasuria and North Sabah fields, which according to management estimates are accretive to ROI.
Tax paid was RM 97m in FY20 and RM 61m in 2Q21 (tax expense: RM 161m and RM 62m respectively).

Risks

There are a few obvious and not-so-obvious risks that one should be aware of before investing in Hibiscus. We shall not consider operational risks (e.g. uptime, OPEX) as they are outside the jurisdiction of the equity analyst. Instead, we shall focus on the financial and strategic risks largely outside the control of management. The main ones are:
· Oil prices remaining subdued for long periods of time
· Fluctuation of exchange rates
· Customer concentration risk
· 2P Reserves being less than estimated
· Significant current and non-current liabilities
· Potential issuance of equity
Oil prices remaining subdued
Of topmost concern in the minds of most analysts is whether Hibiscus has the wherewithal to sustain itself through this period of low oil prices (sub-$30). A quick and dirty estimate of annual cash outflow (i.e. burn rate) assuming a $20 oil world and historical production rates is between RM 50m-70m per year, which considering the RM 200m cash balance implies about 3-4 years of sustainability before the company runs out of cash and has to rely on external assistance for financing.
Table 1: Hibiscus EBITDA at different oil price and exchange rates
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The above table shows different EBITDA scenarios (RM ‘m) given different oil prices (left column) and USD:MYR exchange rates (top row). Currently, oil prices are $27 and USD:MYR is 1:4.36.
Given conservative assumptions of average OPEX/bbl of $20 (current: $15), we can safely say that the company will be loss-making as long as oil remains at $20 or below (red). However, we can see that once oil prices hit $25, the company can tank the lower-end estimate of the annual burn rate of RM 50m (orange), while at RM $27 it can sufficiently muddle through the higher-end estimate of the annual burn rate of RM 70m (green).
Hence, we can assume that as long as the average oil price over the next 3-4 years remains above $25, Hibiscus should come out of this fine without the need for any external financing.
Customer Concentration Risk
With regards to customer concentration risk, there is not much the analyst or investor can do except to accept the risk. Fortunately, 80% of revenues can be attributed to two oil supermajors (Petronas and BP), hence the risk of default on contractual obligations and trade receivables seems to be quite diminished.
2P Reserves being less than estimated
2P Reserves being less than estimated is another risk that one should keep in mind. Fortunately, the current market cap is merely RM 714m – at half of estimated recoverable amounts of RM 1.468 billion – so there’s a decent margin of safety. In addition, there are other mitigating factors which shall be discussed in the next section (‘Opportunities’).
Significant non-current and current liabilities
The significant non-current and current liabilities have been addressed in the previous section. It has been determined that they pose no threat to immediate cash flow due to them being long-term in nature (e.g. decommissioning costs, deferred tax, etc). Hence, for the purpose of assessing going concern, their amounts should not be a cause for concern.
Potential issuance of equity
Finally, we come to the possibility of external financing being required in this low oil price environment. While the company should last 3-4 years on existing cash reserves, there is always the risk of other black swan events materializing (e.g. coronavirus) or simply oil prices remaining muted for longer than 4 years.
Furthermore, management has hinted that they wish to acquire new oil assets at presently depressed prices to increase daily production rate to a targeted 20,000 bbl by end-2021. They have room to acquire debt, but they may also wish to issue equity for this purpose. Hence, the possibility of dilution to existing shareholders cannot be entirely ruled out.
However, given management’s historical track record of prioritizing ROI and optimal capital allocation, and in consideration of the fact that the MD owns 10% of outstanding shares, there is some assurance that any potential acquisitions will be accretive to EPS and therefore valuations.

Opportunities

As with the existence of risk, the presence of material opportunities also looms over the company. Some of them are discussed below:
· Increased Daily Oil Production Rate
· Inclusion of 2C Resources
· Future oil prices exceeding $50 and effects from coronavirus dissipating
Increased Daily Oil Production Rate
The first and most obvious opportunity is the potential for increased production rate. We’ve seen in the last quarter (2Q21) that the North Sabah field increased its daily production rate by approximately 20% as a result of production enhancement projects (infill drilling), lowering OPEX/bbl as a result. To vastly oversimplify, infill drilling is the process of maximizing well density by drilling in the spaces between existing wells to improve oil production.
The same improvements are being undertaken at the Anasuria field via infill drilling, subsea debottlenecking, water injection and sidetracking of existing wells. Without boring you with industry jargon, this basically means future production rate is likely to improve going forward.
By how much can the oil production rate be improved by? Management estimates in their analyst presentation that enhancements in the Anasuria field will be able to yield 5,000 bbl/day by 2021 (current: 2,500 bbl/day).
Similarly, improvements in the North Sabah field is expected to yield 7,000 bbl/day by 2021 (current: 5,300 bbl/day).
This implies a total 2021 expected daily production rate from the two fields alone of 12,000 bbl/day (current: 8,000 bbl/day). That’s a 50% increase in yields which we haven’t factored into our valuation yet.
Furthermore, we haven’t considered any production from existing 2C resources (e.g. Marigold/Sunflower) or any potential acquisitions which may occur in the future. By management estimates, this can potentially increase production by another 8,000 bbl/day, bringing total production to 20,000 bbl/day.
While this seems like a stretch of the imagination, it pays to keep them in mind when forecasting future revenues and valuations.
Just to play around with the numbers, I’ve come up with a sensitivity analysis of possible annual EBITDA at different oil prices and daily oil production rates:
Table 2: Hibiscus EBITDA at different oil price and daily oil production rates
https://preview.redd.it/jnpfhr5n9br41.png?width=814&format=png&auto=webp&s=bbe4b512bc17f576d87529651140cc74cde3d159
The left column represents different oil prices while the top row represents different daily oil production rates.
The green column represents EBITDA at current daily production rate of 8,000 bbl/day; the orange column represents EBITDA at targeted daily production rate of 12,000 bbl/day; while the purple column represents EBITDA at maximum daily production rate of 20,000 bbl/day.
Even conservatively assuming increased estimated annual ITDA of RM 500m (FY20: RM 318m), and long-term average oil prices of $50 (FY20: $60), the estimated Net Profit and P/E ratio is potentially lucrative at daily oil production rates of 12,000 bbl/day and above.
2C Resources
Since we’re on the topic of improved daily oil production rate, it bears to pay in mind the relatively enormous potential from Hibiscus’s 2C Resources. North Sabah’s 2C Resources alone exceed 30 mmbbl; while those from the yet undiagnosed Marigold/Sunflower fields also reach 30 mmbbl. Altogether, 2C Resources exceed 70 mmbbl, which dwarfs the 44 mmbbl of 2P Reserves we have considered up to this point in our valuation estimates.
To refresh your memory, 2C Resources represents oil volumes which have been discovered but are not yet classified as “commercial”. This means that there is reasonable certainty of the oil being recoverable, as opposed to simply being in the very early stages of exploration. So, to be conservative, we will imagine that only 50% of 2C Resources are eligible for reclassification to 2P reserves, i.e. 35 mmbbl of oil.
https://preview.redd.it/mto11iz7abr41.png?width=375&format=png&auto=webp&s=e9028ab0816b3d3e25067447f2c70acd3ebfc41a
This additional 35 mmbbl of oil represents an 80% increase to existing 2P reserves. Assuming the daily oil production rate increases similarly by 80%, we will arrive at 14,400 bbl/day of oil production. According to Table 2 above, this would yield an EBITDA of roughly RM 630m assuming $50 oil.
Comparing that estimated EBITDA to FY20’s actual EBITDA:
FY20 FY21 (incl. 2C) Difference
Daily oil production (bbl/day) 8,626 14,400 +66%
Average oil price (USD/bbl) $68.57 $50 -27%
Average OPEX/bbl (USD) $16.64 $20 +20%
EBITDA (RM ‘m) 632 630 -
Hence, even conservatively assuming lower oil prices and higher OPEX/bbl (which should decrease in the presence of higher oil volumes) than last year, we get approximately the same EBITDA as FY20.
For the sake of completeness, let’s assume that Hibiscus issues twice the no. of existing shares over the next 10 years, effectively diluting shareholders by 50%. Even without accounting for the possibility of the acquisition of new oil fields, at the current market capitalization of RM 714m, the prospective P/E would be about 10x. Not too shabby.
Future oil prices exceeding $50 and effects from coronavirus dissipating
Hibiscus shares have recently been hit by a one-two punch from oil prices cratering from $60 to $30, as a result of both the Saudi-Russian dispute and depressed demand for oil due to coronavirus. This has massively increased supply and at the same time hugely depressed demand for oil (due to the globally coordinated lockdowns being implemented).
Given a long enough timeframe, I fully expect OPEC+ to come to an agreement and the economic effects from the coronavirus to dissipate, allowing oil prices to rebound. As we equity investors are aware, oil prices are cyclical and are bound to recover over the next 10 years.
When it does, valuations of O&G stocks (including Hibiscus’s) are likely to improve as investors overshoot expectations and begin to forecast higher oil prices into perpetuity, as they always tend to do in good times. When that time arrives, Hibiscus’s valuations are likely to become overoptimistic as all O&G stocks tend to do during oil upcycles, resulting in valuations far exceeding reasonable estimates of future earnings. If you can hold the shares up until then, it’s likely you will make much more on your investment than what we’ve been estimating.

Conclusion

Wrapping up what we’ve discussed so far, we can conclude that Hibiscus’s market capitalization of RM 714m far undershoots reasonable estimates of fair value even under conservative assumptions of recoverable oil volumes and long-term average oil prices. As a value investor, I hesitate to assign a target share price, but it’s safe to say that this stock is worth at least RM 1.00 (current: RM 0.45). Risk is relatively contained and the upside far exceeds the downside. While I have no opinion on the short-term trajectory of oil prices, I can safely recommend this stock as a long-term Buy based on fundamental research.
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