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How to Use Moving Averages to Find the Trend - BabyPips.com
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Former investment bank FX trader: Risk management part II
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful. If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic. As ever please comment/reply below with questions or feedback and I'll do my best to get back to you. Part II
Letting stops breathe
When to change a stop
Entering and exiting winning positions
Letting stops breathe
We talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise. Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight. Imagine being long and stopped out on a meaningless retracement ... ouch! One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure. For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that. If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it. There are also more analytical approaches. Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves. For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size. ATR is available on pretty much all charting systems Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart). Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon? Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.
Reasons to change a stop
As a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later. There are some good reasons to modify stops but they are rare. One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are. Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out. Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example. The mighty trailing stop loss order It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops. One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea. Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out. Otherwise, why even have a stop in the first place?
Entering and exiting winning positions
Take profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price. Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position. The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t. Sad to say but incredibly common: retail traders often take profits way too early This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter. Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid. The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.
Entering positions with limit orders
That covers exiting a position but how about getting into one? Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205. You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait. Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in. So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?! There are two more methods that traders often use for entering a position. Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action. You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market. Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders. Pyramiding into a position means buying more as it goes in your favour Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD. Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct. Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend. You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.
Risk:reward and win ratios
Be extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important! Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money. If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below. A combination of win % and risk:reward ratio determine if you are profitable A typical rule of thumb is that a ratio of 1:3 works well for most traders. That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips. One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline. Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.
Not all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad! The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below. The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility. Would you rather have the first trading record or the second? If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps . A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return. If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk. This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ... Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.
The Sharpe ratio works like this:
It takes the average returns of your strategy;
It deducts from these the risk-free rate of return i.e. the rate anyone could have got by investing in US government bonds with very little risk;
It then divides this total return by its own volatility - the more smooth the return the higher and better the Sharpe, the more volatile the lower and worse the Sharpe.
For example, say the return last year was 15% with a volatility of 10% and US bonds are trading at 2%. That gives (15-2)/10 or a Sharpe ratio of 1.3. As a rule of thumb a Sharpe ratio of above 0.5 would be considered decent for a discretionary retail trader. Above 1 is excellent. You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.
VAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%. A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade. Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment. Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often. These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.
Coming up in part III
Available here Squeezes and other risks Market positioning Bet correlation Crap trades, timeouts and monthly limits *** 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.
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
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.
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.
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.
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.
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.
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
Why use the economic calendar
Reading the economic calendar
Knowing what's priced in
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
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.
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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
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).
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).
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).
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.
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).
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 OnInvesting.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. ------------------------------------------------ ------------------------------------------------ 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.
Scalping is a type of trading strategy designed to profit from small price changes since the benefits of these transactions are obtained quickly and once an operation has become profitable. All forms of trading require discipline, but because the number of trades is so large, and the profits from each trade are so small, a scalper must rigorously stick to their trading system, to avoid large losses that could eliminate dozens. successful operations. The scalper traders: they will take small profits to take advantage of the gains as they appear. The goal is a successful trading strategy by means of a large number of profitable trades, rather than a few successful trades with large profits. The scalping of the idea of a better risk exposure as the current time each operation is quite short, which reduces the risk of an adverse event that causes a big move. Furthermore, it is considered that smaller movements are easier to achieve than larger movements and that smaller movements are more frequent than larger ones. >>> Forex Signals With Unbeatable Performance: Verified Forex Results And 5° Rated OnInvesting.com|Free Forex Signals Trial:CLICK HERE TO JOIN FOR FREE
The best scalping strategies
Stochastic Oscillator Strategy
Moving average strategy
Parabolic SAR Indicator Strategy
RSI (Relative Strength Index) Strategy
Reddit Forex Scalping Strategies:
1- Scalping trading using the stochastic oscillator
Scalping can be achieved by using the stochastic oscillator. The term stochastic refers to the current price point relative to its range over a recent period of time. When comparing the price of a security with its recent range, a stochastic tries to provide potential changes. The scalping using said oscillator aims to capture the movements of a market trend, ie, one that moves up or down accordingly. Prices tend to close near the extremes of the recent range before a change occurs, as in the example seen below: https://preview.redd.it/7wy3ixui2nw51.png?width=1397&format=png&auto=webp&s=91f50d685dd4841015c51322cee9fb90701aad33 the chart above, for Brent over a three minute period, we can see that the price rises even higher, and the lows in the stochastic (marked with arrows) provide entry points for long trades, when the black line of% K is crosses over with the red dotted line of% D. The operation is exited when the stochastic reaches the maximum value of its range, above 80, when a bearish convergence appears, when the line of% K crosses below with% D. Rather, short positions would be used in a downtrend market, as in the example below. This time, instead of 'buying dips', we are 'selling raises'. Therefore, we will look for a bearish convergence in the direction of the trend, as highlighted below: https://preview.redd.it/y3qqvejs2nw51.png?width=1398&format=png&auto=webp&s=627f3ded47e901c1f9ea97d5416caeea49b9dc3f
2- Scalping using the moving average
Another method is to use moving averages, usually with two relatively short-term and one longer-term to indicate the trend. In the examples below, on a three-minute chart of the EUR / USD pair , we are using 5- and 20-period moving averages in the short term, and a further 200-period moving averages in the long term. In the first chart, the longer-term moving average is rising, so we expect the five-period moving average to cross above the 20-period moving average, and then we take positions in the direction of the trend. These are marked with an arrow. https://preview.redd.it/22jquy1z2nw51.png?width=1499&format=png&auto=webp&s=ed4f724384b86f95dff584c596e25652f23f240d In the second example, the long-term moving average is declining, so we look for short positions when the price crosses below the 5-period moving average, which has already crossed below the 20-period moving average. https://preview.redd.it/0tl7mky23nw51.png?width=1496&format=png&auto=webp&s=ca7b44138901537185d9e0dbd639a799407ced08 It is important to remember that these trades are trending and that we are not trying to find and capture every move. As in any scalping strategy, it is essential to have good risk management with stops, which is vital to avoid large losses that could eliminate many small gains quickly. >>> Forex Signals With Unbeatable Performance: Verified Forex Results And 5° Rated OnInvesting.com|Free Forex Signals Trial:CLICK HERE TO JOIN FOR FREE
3- Scalping with the use of the parabolic SAR indicator
The Parabolic SAR is an indicator that highlights the direction in which the market is moving and also tries to provide entry and exit points. SAR is the acronym for ' stop and reversal ', which means stop and revocation. The indicator is a series of points placed above or below the price bars. One point below the price is bullish and one point above it is bearish. A change in the position of the points suggests that there is going to be a change in trend. The chart below shows the DAX on a five minute chart; You can open short trades when the price moves below the SAR points and long when the price moves above them. As you can see, some trends are quite widespread and at other times a trader will encounter many trades that generate losses. https://preview.redd.it/35uo837g3nw51.png?width=1498&format=png&auto=webp&s=f020a461c6ff1f8d49fab381da0713b1de75dbf7
What do you have to know before starting scalping strategies Reddit?
The scalping requires the trader has an iron discipline, but also very demanding as far as time is concerned. Although long-term times and smaller sizes allow investors to move away from their platforms, given that there are few possible entries and can be controlled remotely, scalping requires the investor's full attention. Possible entry points can appear and disappear very quickly and therefore a trader must be very vigilant about his platform. For individuals who have a day job or other activities, scalping is not necessarily an ideal strategy. On the other hand, long-term operations with higher profit objectives are a more suitable option. It is difficult to execute a successful scalping strategy. One of the main reasons is that many operations need to be performed over time. Some research in this regard usually shows that more frequent investors only lose money faster, and have a negative capital curve. Instead, most investors are more successful and reduce their time commitments to trading, and even reduce stress by using long-term strategies and avoiding scalping strategies. The scalping requires quick responses to market movements and the ability to forgo an operation if the exact moment has passed. 'Chase' trades, along with a lack of stop-loss discipline, are the key reasons why scalpers are often unsuccessful. The idea of only being in the market for a short period of time sounds appealing, but the chances of being stopped out on a sudden move with a quick correction are high. Trading is an activity that rewards patience and discipline. Although those who are successful with scalping do demonstrate these qualities, they are a small number. Most investors do better with a long-term view, smaller position sizes, and a less frenetic pace of activity. >>> Forex Signals With Unbeatable Performance: Verified Forex Results And 5° Rated OnInvesting.com|Free Forex Signals Trial:CLICK HERE TO JOIN FOR FREE
In all industries there are people credited to being the simplest . In design, the late Steve Jobs is credited to being the simplest in his industry. In boxing, Muhammad Ali was credited to being the simplest boxer of all time. In U.S. politics, there's a consensus that Lincoln was the nation’s greatest President by every measure applied. In the trading world, a variety of traders are known worldwide for his or her skills. From Jesse Livermore to George Soros, we are sharing these tales of past and present traders who had to claw their thanks to the highest . Here, we'll check out the five most famous traders of all time and canopy a touch bit about each trader and why they became so famous. Jesse Livermore Jesse Livermore jumped into the stock exchange with incredible calculations at the age of 15, amassed huge profits, then lost all of them , then mastered two massive crises and came out the opposite side while following his own rules, earning him the nickname “The Great Bear of Wall Street.” Livermore was born in 1877 in Shrewsbury, Massachusetts. Visit شركة اكويتي السعودية He is remembered for his incredible risk taking, his gregarious method of reading the potential moves within the stock exchange , derivatives and commodities, and for sustaining vast losses also as rising to fortune. He began his career having run far away from home by carriage to flee a lifetime of farming that his father had planned for him, instead choosing city life and finding work posting stock quotes at Paine Webber, a Boston stockbroker. Livermore bought his first share at 15 and earned a profit of $3.12 from $5 after teaching himself about trends. George Soros George Soros has a fantastic backstory. Born in Hungary in 1930 to Jewish parents, Soros survived the Holocaust and later fled the country when the Communists took power. He went on to become one among the richest men and one among the foremost famous philanthropists within the world. Most day traders know him for his long and prolific career as a trader who famously “broke the Bank of England” in 1992. Soros made an enormous bet against British Pound, which earned him $1 billion in profit in only 24 hours. Along with other currency speculators, he placed a bet against the bank’s ability to carry the road on the pound. He borrowed pounds, then sold them, helping to down the worth of the currency on forex markets and ultimately forcing the united kingdom to crash out of the ecu rate of exchange Mechanism. It was perhaps the quickest billion dollars anyone has ever made and one among the foremost famous trades ever taken, which later became referred to as “breaking the Bank of England”. Soros is believed to have netted a complete of about $44 billion through financial speculation. And he has used his fortune to find thousands of human rights, democracy, health, and education projects. Richard Dennis There are only a couple of traders which will take a little amount of cash and switch it into millions and Richard Dennis was one among them. Known as the “Prince of the Pit”, Dennis is claimed to have borrowed $1,600 when he was around 23 years old and turned it into $200 million in about 10 years trading commodities. Even more interesting to notice , he only traded $400 of the $1,600. Not only did he achieve great success as a commodities trader, he also went on to launch the famous “Turtle Traders Group”. Using mini contracts, Dennis began to trade his own account at the Mid America commodities exchange . He made a profit of $100,000 in 1973. The subsequent year, he capitalized on a runway soybean market to earn $500,000 in profits. He became an impressive millionaire at the top of the year. However, he incurred massive losses within the Black Monday stock exchange crash in 1987 and therefore the dot-com bubble burst in 2000. While he's famous for creating and losing tons of cash , Dennis is additionally famous for something else – an experiment. He and his friend William Eckhardt recruited and trained traders, a couple of men and ladies, the way to trade futures. These so-called Turtle Traders went on to form profits of $175 million in 4 years, consistent with a former student. Paul Tudor Jones Paul Tudor Jones thrust into the limelight within the 80s when he successfully predicted the 1987 stock exchange , as shown within the riveting one hour documentary called “Trader”. The legendary trader was born in Memphis, Tennessee in 1954. His father ran a financial and legal trade newspaper. While he was in college, he want to write articles for the newspaper under the pseudonym, “Eagle Jones”. Jones began his journey within the finance business by trading cotton. He started trading on his own following 4 years of non-trading experience, made profits from his trades but got bored, and later hired people to trade for him so he would not get bored. But the trade that shot him to fame came on Black Monday in 1987, when he made an estimated $100 million whilst the Dow Jones Industrial Average plunged 22%. He became a pioneer within the area of worldwide macro investing and was an enormous player within the meteoric growth of the hedge fund industry. He's also known for depending on currencies and interest rates. He founded his hedge fund, Tudor Investment Corp, in 1980. The fund currently has around $21 billion in assets under management and he himself has an estimated net worth of nearly $5.8 Billion. John Paulson Super-trader John Paulson built a private fortune worth $4.4 billion from managing other people’s money. Born in 1955, Paulson made his name and far of his money betting a huge amount of money against the U.S. housing market during the worldwide financial crisis of 2007–2008. Paulson bought insurance against defaults by subprime mortgages before the market collapse in 2007. He netted an estimated $20 billion on the collapse of the subprime mortgage market, dubbed the best trade ever. However, his diary since that bet has been patchy at the best . Within the years following the financial crisis, Paulson struggled to match this success. Failed bets on gold, healthcare and pharmaceutical stocks caused investors to escape his hedge fund Paulson & Co, cutting its assets under management to $10 billion as of January 2020 from a high of $36 billion in 2011. Earlier this year, Paulson announced the fund would stop managing money for outdoor clients and switch it into a family office. He launched the fund in 1994.
I have a habit of backtesting every strategy I find as long as it makes sense. I find it fun, and even if the strategy ends up being underperforming, it gives me a good excuse to gain valuable chart experience that would normally take years to gather. After I backtest something, I compare it to my current methodology, and usually conclude that mine is better either because it has a better performance or the new method requires too much time to manage (Spoiler: until now, I like this better) During the last two days, I have worked on backtesting ParallaxFx strategy, as it seemed promising and it seemed to fit my personality (a lazy fuck who will happily halve his yearly return if it means he can spend 10% less time in front of the screens). My backtesting is preliminary, and I didn't delve very deep in the data gathering. I usually track all sort of stuff, but for this first pass, I sticked to the main indicators of performance over a restricted sample size of markets. Before I share my results with you, I always feel the need to make a preface that I know most people will ignore.
I am words on your screen. You cannot trust me. I could have edited this or literally just typed random numbers on a spreadsheet. Do your own research if you want to trust my conclusion.
Even if you trust me, you need to do backtesting for yourself. The goal of backtesting isn't simply to figure out whether a strategy has an edge: it's a way to get used to how the market flows (valuable experience you will bring on to any other strategy) and how the strategy behaves. You need to see it with your own eyes to allow your subconscious mind to be at ease when it comes time to trade it live: the only way to truly trust your strategy during a period of drawdown, is to have seen it work over hundreds of trades in the past.
Strategy I am not going to go into the strategy in this thread. If you haven't read the series of threads by the guy who shared it, go here. As suggested by my mentioned personality type, I went with the passive management options of ParallaxFx's strategy. After a valid setup forms, I place two orders of half my risk. I add or remove 1 pip from each level to account for spread.
The first at the 23.6 retracement.
The second at the 38.2 retracement.
Both orders have a stop loss at the 78.6 retracement.
Both orders have the same target at the -100.0 extension.
If price moves to the -38.2 extension, I delete any unfilled orders.
I do not scale out, I do not move to breakeven, I place my orders and walk away.
Sample I tested this strategy over the seven major currency pairs: AUDUSD, USDCAD, NZDUSD, GBPUSD, USDJPY, EURUSD, USDCHF. The time period started on January 1th 2018 and ended on July 1th 2020, so a 2.5 years backtest. I tested over the D1 timeframe, and I plan on testing other timeframes. My "protocol" for backtesting is that, if I like what I see during this phase, I will move to the second phase where I'll backtest over 5 years and 28 currency pairs. Units of measure I used R multiples to track my performance. If you don't know what they are, I'm too sleepy to explain right now. This article explains what they are. The gist is that the results you'll see do not take into consideration compounding and they normalize volatility (something pips don't do, and why pips are in my opinion a terrible unit of measure for performance) as well as percentage risk (you can attach variable risk profiles on your R values to optimize position sizing in order to maximize returns and minimize drawdowns, but I won't get into that). Results I am not going to link the spreadsheet directly, because it is in my GDrive folder and that would allow you to see my personal information. I will attach screenshots of both the results and the list of trades. In the latter, I have included the day of entry for each trade, so if you're up to the task, you can cross-reference all the trades I have placed to make sure I am not making things up. Overall results: R Curve and Segmented performance. List of trades: 1, 2, 3, 4, 5, 6, 7. Something to note: I treated every half position as an individual trade for the sake of simplicity. It should not mess with the results, but it simply means you will see huge streaks of wins and losses. This does not matter because I'm half risk in each of them, so a winstreak of 6 trades is just a winstreak of 3 trades. For reference:
Profit Factor: 2.34
Return: 100.47 R
Strike rate: 48.28%
Average win: 2.51 R
Average loss: -1.00 R
Thoughts Nice. I'll keep testing. As of now it is vastly better than my current strategy.
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
The exact mechanism of drain, or transfers from India to Britain was quite simple.
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.
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.
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.
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 seeRajan 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.
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'.
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
All how to make on binary options strategies should take into account all market analysis options. You cannot make a decision on only one instrument, even if these are candlestick analysis patterns. Let's start with trend signals, see examples of vfxAlert binary signals. Currency pair GBP/USD and a strong signal on PUT-option signal. Let's look at the price chart - confirmation by the "Three Method" candlestick pattern and you can open an option with an expiration of 5-10 minutes. https://preview.redd.it/gwn6hg5fs8p51.png?width=1100&format=png&auto=webp&s=f67cae8d8fde0e38a27318f8eadea0e2c3cad495 The signal appeared at the intersection of the moving average ("MA" on the signal panel). Traders see this. The option opens on a reversal, but then there are also candlestick patterns, and new PUT-signals with the “MA” label open the next options with a large volume. The next signal on the CCI indicator shows the dynamics of the current trend. Created for the stock market, where trends are long and easier to find. On Forex, volatility is higher and there may be strong corrections and pullbacks that "break" the indicator. In the figure, binary options trading signals is confirmed by a strong candle pattern – the price goes towards the gap and you can open a CALL-option. Reversal real binary options signals vfxAlert. More reliable than trendy ones, beginners should start with them. It is easier to see and understand: "Bulling engulfing" pattern, which means the "bulls" managed to shift the balance of power to themselves and start an uptend on EUR / GBP. The vfxAlert signal confirms this by technical analysis of the RSI indicator. https://preview.redd.it/gpikbe6js8p51.png?width=1100&format=png&auto=webp&s=8581ebe0a59f665b78891996f23d95c289972250 Doji candlestick appeared on EUUSD. In candlestick analysis, this is the strongest reversal pattern. The vfxAlert binary options signal according to Parabolic SAR trend confirms the beginning of the downtrend. After one candlestick, the trend started you can open the PUT-option. The trader looks at «Power» value first, the market may be sideways, and candlestick patterns are false: https://preview.redd.it/efwtnupms8p51.png?width=1100&format=png&auto=webp&s=1170e6526704d44ec1a0ee936de5797f41e61d31 We always start testing combination "vfxAlert live binary signals + candlestick patterns" on a demo account. You only receive recommendations and must make sure that they fit your strategy, trading session and trading style.
PART 2 : https://www.reddit.com/wallstreetbets/comments/g0sd44/what_is_the_bottom/ PART 3: https://www.reddit.com/wallstreetbets/comments/g2enz2/why_the_printer_must_continue/ Edit: By popular demand, the too long didn't read is now at the top TL;DR SPY 220p 11/20 This will likely be a multi-part series. It should be noted that I am no expert by any means, I'm actually quite new to this, it is just an elementary analysis of patterns in price and time. I am not a financial advisor, and this is not advice for a person to enter trades upon. The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this DD, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. We will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY). In trading, little to no concern is given about value of underlying asset. We concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing. The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors. Markets ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature Markets rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market. According to trade theory, the unending purpose of a market is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains. We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The market is technically open 24-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy. Some important terms to keep in mind: § Discrete – terminal points at the extremes of ranges § Secondary Discrete – quantified retracement or correction between two discrete § Longs (asset appreciation) and shorts (asset depreciation)
- Technical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things. § Volume – derived from the market itself, it is mostly irrelevant. The major problem with volume is that the US market open causes tremendous volume surges eradicating any intrinsic volume analysis. At major highs and lows, the market is typically anemic. Most traders are not active at terminal discretes because of levels of fear. Allows us confidence in time and price symmetry market inflection points, if we observe low volume at a foretold range of values. We can rationalize that an absolute discrete is usually only discovered and anticipated by very few traders. As the general market realizes it, a herd mentality will push the market in the direction favorable to defending it. Volume is also useful for swing trading, as chances for swing’s validity increases if an increase in volume is seen on and after the swing’s activation. Therefore, due to the relatively high volume on the 23rd of March, we can safely determine that a low WAS NOT reached. § VIX – Volatility Index, this technical indicator indicates level of fear by the amount of options-based “insurance” in portfolios. A low VIX environment, less than 20 for the S&P index, indicates a stable market with a possible uptrend. A high VIX, over 20, indicates a possible downtrend. However, it is equally important to see how VIX is changing over time, if it is decreasing or increasing, as that indicates increasing or decreasing fear. Low volatility allows high leverage without risk or rest. Occasionally, markets do rise with high VIX. As VIX is unusually high, in the forties, we can be confident that a downtrend is imminent.
Trend Definition Analysis
– Trend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail. Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form. A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw an uptrend line on the SPY chart, but it is possible to correctly draw a downtrend – indicating that the overall trend is downwards.
Now that we have determined that the overall trend is downwards, the next issue is the question of when SPY will bottom out. Time is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding. Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading. Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure. Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price. Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not. We will complete our analysis of time by measuring it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in. What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours. Yearly Lows: 12/31/2000, 9/21/2001, 10/9/2002, 3/11/2003, 8/2/2004, 4/15/2005, 6/12/2006, 3/5/2007, 11/17/2008, 3/9/2009, 7/2/10, 10/3/11, 1/1/12, 1/1/13, 2/3/14, 9/28/15, 2/8/16, 1/3/17, 12/24/18, 6/3/19 Months: 1, 1, 1, 2, 2, 3, 3, 3, 4, 6, 6, 7, 8, 9, 9, 10, 10, 11, 12, 12 Days: 1, 1, 2, 2, 3, 3, 3, 3, 5, 8, 9, 9, 11, 12, 15, 17, 21, 24, 28, 31 Monthly Lows:3/23, 2/28, 1/27, 12/3, 11/1, 10/2, 9/3, 8/5, 7/1, 6/3, 5/31, 4/1 Days: 1, 1, 1, 2, 3, 3, 3, 5, 23, 27, 27, 31 Weighted Times are repetitions which appears multiple times within the same list, observed and accentuated once divided into relevant sections of the histogram. They are important in the presently defined trading time period and are similar to a mathematical mode with respect to a series. Phased times are essentially periodical patterns in histograms, though they do not guarantee inflection points*.* We see that SPY tends to have its lows between three major month clusters: 1-4, primarily March (which has actually occurred already this year), 6-9, averaged out to July, and 10-12, averaged out to November. Following the same methodology, we get the third and tenth days of the month as the likeliest days. However, evaluating the monthly lows for the past year, the end of the month has replaced the average of the tenth. Therefore, we have four primary dates for our histogram. 7/3/20, 7/27/20, and 11/3/20, 11/27/20 . How do we narrow this group down with any accuracy? Let us average the days together to work with two dates - 7/15/20 and 11/15/20. The 8.6-Year Armstrong-Princeton Global Economic Confidence model – states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is April 14th of 2022. However, we can time-shift to other peaks and troughs to determine a date for this year. If we consider 1/28/2018 as a localized high and apply this model, we get 3/23/20 as a low - strikingly accurate. I have chosen the next localized high, 9/21/2018 to apply the model to. We achieve a date of 11/14/2020. The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of the bear market - roughly speaking. Therefore, our timeline looks like:
11/14/20 - yearly low (selected from histogram averages, 11/15/20, and the 8.6 Year Confidence model)
7/28/21 - End of bear market (18 month average of 8/9, averaged with histogram date of 7/15)
4/14/22 - lesser correction.
As we move forward in time, our predictions may be less accurate. It is important to keep in mind that this analysis will likely change and become more accurate as we factor in Terry Laundry’s T-Theory, the Bradley Cycle, a more sophisticated analysis of Bull and Bear Market Cycles, the Fundamental Investor Cyclic Approach, and Seasons and Half-Seasons. I have also assumed that the audience believes in these models, which is not necessary. Anyone with free time may construct histograms and view these time models, determining for themselves what is accurate and what is not. Take a look at 1/28/2008, that localized high, and 2.15 years (1/4th of the sinusoidal wave of the model) later. The question now is, what prices will SPY reach on 11/14? Where will we be at 7/28? What will happen on 4/14/22?
One of my favourite ways to enter a trade - what market makers do
Hey Forex. Been a while since I've made an actual post. I still think 90%+ of the posts in here are a toxic wasteland, unfortunately. That being said, I wanted to share one of my entry tips with all of you. This is especially helpful given the dramatic increase in volatility we have seen across the currency markets. This isn't technical, there's no magic chart pattern or indicator. Rather, it is a concept. From what I've seen posted here, a common struggle is "where and how do I enter the trade?". This is a big question... and it can separate the analysts from the traders. How often have you had a view that xxx/xxx is going up/down and in fact... it does just that? The only problem is, you weren't onboard the trade. You either missed out entirely, or you chased it and bought the high/sold the low. The title for this post isn't just clickbait, this is in fact what market makers do. I have to emphasize this point once more, this is NOT a technical strategy. It is a different perspective on risk management that the retail crowd is largely unfamiliar with. I'm going to use point form to cover this concept from now on: Don't (DO NOT DO THESE THINGS): - Think of your entry as an all-or-nothing proposition - Think that you must shoot your entire shot all at once - That there's a perfect point at which you must pull the trigger, and if you miss this point then you miss the trade Do: - Split your risk allocation for a specific idea into different parts (for example if you want to risk $100,000 notional value on a USD/JPY trade, split your entry into 4 parts. Maybe that means each tranche is 25k, maybe it means that you go 10k, 20k, 30k, 40k) - Be a scale down buyer and a scale up seller - Pick bands in which you want to take action. For example if you think USD/JPY is a buy from 108.5 to 110, then pick a band in which you will be a buyer. Maybe it is between 108.5 and 108. That gives you a lot of room to stack orders (whether these are limits or market orders is up to you). The best case scenario is that all your orders get filled, and you have a fantastic overall average price point. The worst case scenario (other than simply being wrong) is that only your initial order is filled and price starts running away. Remember, you'll always be too light when it is going your way and too heavy when it is going in your face. - This also works on the way out when you want to exit. You can scale out of the trade, just as you scaled into it. This takes a lot of pressure off in terms of "sniping" an entry. I hear that term a lot, and it drives me crazy. Unless I'm hedging my options in the spot and I'm scalping for small points here and there, I'm not looking for a "sniper" entry. I'm looking for structural plays. Other hedge funds, banks, central banks, they're not dumping their entire load all at once. This approach allows you to spread your risk out across a band rather than being pigeonholed into picking a perfect level. It allows you to improve your dollar-cost average with clearly defined risk parameters. Unless you are consistently getting perfect entries with zero drawdown, this method just makes so much sense. The emotional benefit is incredible, as you don't have to worry about the price moving against you. Obviously you pick a stop where your idea is simply wrong, but otherwise this should help you remain (more) relaxed.
The Best (free) Multi time-frame Utility/Tool for MT4 to date
Disclaimer: I am not the creator nor am i promoting this tool for any personal gain whatsoever. This is a 100% free tool that can be downloaded from the web. I am not posting here to bring attention to myself or any other website regardless of context. I'm merely sharing this utility with the intention of helping new traders and veteran traders alike. I read the subreddit rules and it's prohibited to share links to blogs, youtube, and social media; nor can we post promotional marketing activity (promotions to generate sales). Since this post doesn't directly fall into those categories this post should hopefully be okay . Hello fellow traders, I'd like to make a quick post to share with you guys one of my absolute favorite MT4 tools in regards to multi time-frame analysis. I cant tell you how much this tool has helped me, especially when i was a new trader years ago trying to analyze various currency pairs. So i know this will help all of you as well. I'm sure many of you guys have asked yourself or wondered which currency pairs are the best to trade at any particular time. Well this mt4 dashboard should help steer you in the right direction when analyzing the market and add an extra level of confirmation and market sentiment to your strategy. What is does is measure price distance from moving averages and mimics the functionality of a currency strength meter on steroids. (I personally use it to find the the strongest and weakest currencies and trade those). This dashboard is fully customization in regards to time frame, MA method, price and length. To be safe i don't want to leave a link adding reason for mods to remove this post. Its called MaDash and can be found with a quick browser search (keywords "MaDash forex"). Remember, this is free and has always been free so if anyone is trying to charge for this then your're not at the right place. Anyway, i hope you all find this tool as beneficial to your trading repertoire as i have. Happy Trading! Screenshot of this dashboard for reference. https://preview.redd.it/y40fl0qmmrz41.png?width=1552&format=png&auto=webp&s=a7470825ca2f227d030281fda16abc1b62b0ddbb https://preview.redd.it/g72hmpn9vrz41.png?width=842&format=png&auto=webp&s=734aaf79a756c35ed9f0cb1d44cc20ca0680f87c
https://preview.redd.it/gp18bjnlabr41.jpg?width=768&format=pjpg&auto=webp&s=6054e7f52e8d52da403016139ae43e0e799abf15 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/
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). https://preview.redd.it/3dqc4jraabr41.png?width=641&format=png&auto=webp&s=7ba0e8614c4e9d781edfc670016a874b90560684 https://preview.redd.it/lvdkrf0cabr41.png?width=356&format=png&auto=webp&s=46f250a713887b06986932fa475dc59c7c28582e 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,Reservesare “… 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: https://preview.redd.it/o8qejdyc8br41.png?width=710&format=png&auto=webp&s=b3ab9be8f83badf0206adc982feda3a558d43e78 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. https://preview.redd.it/gk54qplf8br41.png?width=489&format=png&auto=webp&s=c905b7a6328432218b5b9dfd53cc9ef1390bd604 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 https://preview.redd.it/62nssexj8br41.png?width=1003&format=png&auto=webp&s=cd78f86d51165fb9a93015e49496f7f98dad64dd 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 https://preview.redd.it/586u4kfo8br41.png?width=1038&format=png&auto=webp&s=7580fc7f7df7e948754d025745a5cf47d4393c0f 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: https://preview.redd.it/7y6064dq8br41.png?width=700&format=png&auto=webp&s=2a4120563a011cf61fc6090e1cd5932602599dc2 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: https://preview.redd.it/xixge5sr8br41.png?width=433&format=png&auto=webp&s=288a00f6e5088d01936f0217ae7798d2cfcf11f2 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. https://preview.redd.it/o2eiss6u8br41.png?width=710&format=png&auto=webp&s=03960cce698d9cedb076f3d5f571b3c59d908fa8 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: https://preview.redd.it/h8hubrmw8br41.png?width=450&format=png&auto=webp&s=6d23f0f9c3dafda89e758b815072ba335467f33e 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 ofRM 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). https://preview.redd.it/hse8ttb09br41.png?width=881&format=png&auto=webp&s=82e48b5961c905fe9273cb6346368de60202ebec 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 billionapproximates the accumulated Net Profit recoverable from 2P reserves. To conclude Valuation (Method 2), we arrive at the following:
Accumulated Net Profit from 2P Reserves
RM 1.452 billion
RM 1.468 billion
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. https://preview.redd.it/h689bss79br41.png?width=810&format=png&auto=webp&s=ed47fce6a5c3815dd3d4f819e31f1ce39ccf4a0b 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). https://preview.redd.it/4omjptbe9br41.png?width=1019&format=png&auto=webp&s=eaabfc824134063100afa62edfd36a34a680fb60 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. https://preview.redd.it/1xrnwzm89br41.png?width=732&format=png&auto=webp&s=c078bc3e18d9c79d9a6fbe1187803612753f69d8 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).
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 https://preview.redd.it/gxnekd6h9br41.png?width=670&format=png&auto=webp&s=edbfb9621a43480d11e3b49de79f61a6337b3d51 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.
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:
FY21 (incl. 2C)
Daily oil production (bbl/day)
Average oil price (USD/bbl)
Average OPEX/bbl (USD)
EBITDA (RM ‘m)
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.
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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