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Hi guys, I have been using reddit for years in my personal life (not trading!) and wanted to give something back in an area where i am an expert. I worked at an investment bank for seven years and joined them as a graduate FX trader so have lots of professional experience, by which i mean I was trained and paid by a big institution to trade on their behalf. This is very different to being a full-time home trader, although that is not to discredit those guys, who can accumulate a good amount of experience/wisdom through self learning. When I get time I'm going to write a mid-length posts on each topic for you guys along the lines of how i was trained. I guess there would be 15-20 topics in total so about 50-60 posts. Feel free to comment or ask questions. The first topic is Risk Management and we'll cover it in three parts Part I
Why it matters
Using stops sensibly
Picking a clear level
Why it matters
The first rule of making money through trading is to ensure you do not lose money. Look at any serious hedge fund’s website and they’ll talk about their first priority being “preservation of investor capital.” You have to keep it before you grow it. Strangely, if you look at retail trading websites, for every one article on risk management there are probably fifty on trade selection. This is completely the wrong way around. The great news is that this stuff is pretty simple and process-driven. Anyone can learn and follow best practices. Seriously, avoiding mistakes is one of the most important things: there's not some holy grail system for finding winning trades, rather a routine and fairly boring set of processes that ensure that you are profitable, despite having plenty of losing trades alongside the winners.
Capital and position sizing
The first thing you have to know is how much capital you are working with. Let’s say you have $100,000 deposited. This is your maximum trading capital. Your trading capital is not the leveraged amount. It is the amount of money you have deposited and can withdraw or lose. Position sizing is what ensures that a losing streak does not take you out of the market. A rule of thumb is that one should risk no more than 2% of one’s account balance on an individual trade and no more than 8% of one’s account balance on a specific theme. We’ll look at why that’s a rule of thumb later. For now let’s just accept those numbers and look at examples. So we have $100,000 in our account. And we wish to buy EURUSD. We should therefore not be risking more than 2% which $2,000. We look at a technical chart and decide to leave a stop below the monthly low, which is 55 pips below market. We’ll come back to this in a bit. So what should our position size be? We go to the calculator page, select Position Size and enter our details. There are many such calculators online - just google "Pip calculator". https://preview.redd.it/y38zb666e5h51.jpg?width=1200&format=pjpg&auto=webp&s=26e4fe569dc5c1f43ce4c746230c49b138691d14 So the appropriate size is a buy position of 363,636 EURUSD. If it reaches our stop level we know we’ll lose precisely $2,000 or 2% of our capital. You should be using this calculator (or something similar) on every single trade so that you know your risk. Now imagine that we have similar bets on EURJPY and EURGBP, which have also broken above moving averages. Clearly this EUR-momentum is a theme. If it works all three bets are likely to pay off. But if it goes wrong we are likely to lose on all three at once. We are going to look at this concept of correlation in more detail later. The total amount of risk in our portfolio - if all of the trades on this EUR-momentum theme were to hit their stops - should not exceed $8,000 or 8% of total capital. This allows us to go big on themes we like without going bust when the theme does not work. As we’ll see later, many traders only win on 40-60% of trades. So you have to accept losing trades will be common and ensure you size trades so they cannot ruin you. Similarly, like poker players, we should risk more on trades we feel confident about and less on trades that seem less compelling. However, this should always be subject to overall position sizing constraints. For example before you put on each trade you might rate the strength of your conviction in the trade and allocate a position size accordingly: https://preview.redd.it/q2ea6rgae5h51.png?width=1200&format=png&auto=webp&s=4332cb8d0bbbc3d8db972c1f28e8189105393e5b To keep yourself disciplined you should try to ensure that no more than one in twenty trades are graded exceptional and allocated 5% of account balance risk. It really should be a rare moment when all the stars align for you. Notice that the nice thing about dealing in percentages is that it scales. Say you start out with $100,000 but end the year up 50% at $150,000. Now a 1% bet will risk $1,500 rather than $1,000. That makes sense as your capital has grown. It is extremely common for retail accounts to blow-up by making only 4-5 losing trades because they are leveraged at 50:1 and have taken on far too large a position, relative to their account balance. Consider that GBPUSD tends to move 1% each day. If you have an account balance of $10k then it would be crazy to take a position of $500k (50:1 leveraged). A 1% move on $500k is $5k. Two perfectly regular down days in a row — or a single day’s move of 2% — and you will receive a margin call from the broker, have the account closed out, and have lost all your money. Do not let this happen to you. Use position sizing discipline to protect yourself.
If you’re wondering - why “about 2%” per trade? - that’s a fair question. Why not 0.5% or 10% or any other number? The Kelly Criterion is a formula that was adapted for use in casinos. If you know the odds of winning and the expected pay-off, it tells you how much you should bet in each round. This is harder than it sounds. Let’s say you could bet on a weighted coin flip, where it lands on heads 60% of the time and tails 40% of the time. The payout is $2 per $1 bet. Well, absolutely you should bet. The odds are in your favour. But if you have, say, $100 it is less obvious how much you should bet to avoid ruin. Say you bet $50, the odds that it could land on tails twice in a row are 16%. You could easily be out after the first two flips. Equally, betting $1 is not going to maximise your advantage. The odds are 60/40 in your favour so only betting $1 is likely too conservative. The Kelly Criterion is a formula that produces the long-run optimal bet size, given the odds. Applying the formula to forex trading looks like this: Position size % = Winning trade % - ( (1- Winning trade %) / Risk-reward ratio If you have recorded hundreds of trades in your journal - see next chapter - you can calculate what this outputs for you specifically. If you don't have hundreds of trades then let’s assume some realistic defaults of Winning trade % being 30% and Risk-reward ratio being 3. The 3 implies your TP is 3x the distance of your stop from entry e.g. 300 pips take profit and 100 pips stop loss. So that’s 0.3 - (1 - 0.3) / 3 = 6.6%. Hold on a second. 6.6% of your account probably feels like a LOT to risk per trade.This is the main observation people have on Kelly: whilst it may optimise the long-run results it doesn’t take into account the pain of drawdowns. It is better thought of as the rational maximum limit. You needn’t go right up to the limit! With a 30% winning trade ratio, the odds of you losing on four trades in a row is nearly one in four. That would result in a drawdown of nearly a quarter of your starting account balance. Could you really stomach that and put on the fifth trade, cool as ice? Most of us could not. Accordingly people tend to reduce the bet size. For example, let’s say you know you would feel emotionally affected by losing 25% of your account. Well, the simplest way is to divide the Kelly output by four. You have effectively hidden 75% of your account balance from Kelly and it is now optimised to avoid a total wipeout of just the 25% it can see. This gives 6.6% / 4 = 1.65%. Of course different trading approaches and different risk appetites will provide different optimal bet sizes but as a rule of thumb something between 1-2% is appropriate for the style and risk appetite of most retail traders. Incidentally be very wary of systems or traders who claim high winning trade % like 80%. Invariably these don’t pass a basic sense-check:
How many live trades have you done? Often they’ll have done only a handful of real trades and the rest are simulated backtests, which are overfitted. The model will soon die.
What is your risk-reward ratio on each trade? If you have a take profit $3 away and a stop loss $100 away, of course most trades will be winners. You will not be making money, however! In general most traders should trade smaller position sizes and less frequently than they do. If you are going to bias one way or the other, far better to start off too small.
How to use stop losses sensibly
Stop losses have a bad reputation amongst the retail community but are absolutely essential to risk management. No serious discretionary trader can operate without them. A stop loss is a resting order, left with the broker, to automatically close your position if it reaches a certain price. For a recap on the various order types visit this chapter. The valid concern with stop losses is that disreputable brokers look for a concentration of stops and then, when the market is close, whipsaw the price through the stop levels so that the clients ‘stop out’ and sell to the broker at a low rate before the market naturally comes back higher. This is referred to as ‘stop hunting’. This would be extremely immoral behaviour and the way to guard against it is to use a highly reputable top-tier broker in a well regulated region such as the UK. Why are stop losses so important? Well, there is no other way to manage risk with certainty. You should always have a pre-determined stop loss before you put on a trade. Not having one is a recipe for disaster: you will find yourself emotionally attached to the trade as it goes against you and it will be extremely hard to cut the loss. This is a well known behavioural bias that we’ll explore in a later chapter. Learning to take a loss and move on rationally is a key lesson for new traders. A common mistake is to think of the market as a personal nemesis. The market, of course, is totally impersonal; it doesn’t care whether you make money or not. Bruce Kovner, founder of the hedge fund Caxton Associates There is an old saying amongst bank traders which is “losers average losers”. It is tempting, having bought EURUSD and seeing it go lower, to buy more. Your average price will improve if you keep buying as it goes lower. If it was cheap before it must be a bargain now, right? Wrong. Where does that end? Always have a pre-determined cut-off point which limits your risk. A level where you know the reason for the trade was proved ‘wrong’ ... and stick to it strictly. If you trade using discretion, use stops.
Picking a clear level
Where you leave your stop loss is key. Typically traders will leave them at big technical levels such as recent highs or lows. For example if EURUSD is trading at 1.1250 and the recent month’s low is 1.1205 then leaving it just below at 1.1200 seems sensible. If you were going long, just below the double bottom support zone seems like a sensible area to leave a stop You want to give it a bit of breathing room as we know support zones often get challenged before the price rallies. This is because lots of traders identify the same zones. You won’t be the only one selling around 1.1200. The “weak hands” who leave their sell stop order at exactly the level are likely to get taken out as the market tests the support. Those who leave it ten or fifteen pips below the level have more breathing room and will survive a quick test of the level before a resumed run-up. Your timeframe and trading style clearly play a part. Here’s a candlestick chart (one candle is one day) for GBPUSD. https://preview.redd.it/moyngdy4f5h51.png?width=1200&format=png&auto=webp&s=91af88da00dd3a09e202880d8029b0ddf04fb802 If you are putting on a trend-following trade you expect to hold for weeks then you need to have a stop loss that can withstand the daily noise. Look at the downtrend on the chart. There were plenty of days in which the price rallied 60 pips or more during the wider downtrend. So having a really tight stop of, say, 25 pips that gets chopped up in noisy short-term moves is not going to work for this kind of trade. You need to use a wider stop and take a smaller position size, determined by the stop level. There are several tools you can use to help you estimate what is a safe distance and we’ll look at those in the next section. There are of course exceptions. For example, if you are doing range-break style trading you might have a really tight stop, set just below the previous range high. https://preview.redd.it/ygy0tko7f5h51.png?width=1200&format=png&auto=webp&s=34af49da61c911befdc0db26af66f6c313556c81 Clearly then where you set stops will depend on your trading style as well as your holding horizons and the volatility of each instrument. Here are some guidelines that can help:
Use technical analysis to pick important levels (support, resistance, previous high/lows, moving averages etc.) as these provide clear exit and entry points on a trade.
Ensure that the stop gives your trade enough room to breathe and reflects your timeframe and typical volatility of each pair. See next section.
Always pick your stop level first. Then use a calculator to determine the appropriate lot size for the position, based on the % of your account balance you wish to risk on the trade.
So far we have talked about price-based stops. There is another sort which is more of a fundamental stop, used alongside - not instead of - price stops. If either breaks you’re out. For example if you stop understanding why a product is going up or down and your fundamental thesis has been confirmed wrong, get out. For example, if you are long because you think the central bank is turning hawkish and AUDUSD is going to play catch up with rates … then you hear dovish noises from the central bank and the bond yields retrace lower and back in line with the currency - close your AUDUSD position. You already know your thesis was wrong. No need to give away more money to the market.
Coming up in part II
EDIT: part II here Letting stops breathe When to change a stop Entering and exiting winning positions Risk:reward ratios Risk-adjusted returns
Coming up in part III
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.
Im looking for guidance for a trader with experience. (Read Please)
I'm looking for guidance from* a trader with experience. I'm 17 years old. I've been learning the markets for about 6 months now and when I turn 18 in 4 months, Ill be going hard on trading. People will think I'm young and naïve about my trading. I admit there's a lot I don't know. In my opinion, the stuff I don't know. Are things you must learn through experience. - What I am truly asking is if someone with trading experience would be able to maybe setup a meet with me so we can have a conversation and talk. If anybody was willing to be my mentor id literally be up 24/7 to learn from you. I would like to discuss a few things about my strategy and what my next steps should be from this point on. Honestly all advice helps See i know my strategy works through backtesting and demos and I'm still refining my trading strategy but even then nothing is set in stone because I'm in my first 6 months. If i told this community i think i could hop in the markets and make profit with my strategy by making 1-3 trades a week. Id be laughed, memed and destroyed but i truly do believe that. Since I've started this journey I haven't been able to talk to anyone about cause nobody fuckin understands - FOR THAT REASON, is why i need to talk to someone with experience. I will tell you my strategy and how i learned it and my whole plan. We can talk about anything forex related but if someone could sit down wit me for like a couple hours... that'd honestly be goated. DISCLAIMER - Save your ''you wont be making profits, you'll blow your account, your to confident" comments for someone else. Trust me i know yo, the way i think i can trade is literally the most cockiest thing ever. That's why I'm scared. I don't know where I'm going to mess up. I feel like i got the byakugan of forex and some kunai boutta hit my blind spot. (if u get that reference your already successful in my eyes) I also know that im going to lose trades. Obviously but I'm not concerned with my risk management style.
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.
Former investment bank FX trader: news trading and second order thinking
Thanks to everyone who responded to the previous pieces on risk management. We ended up with nearly 2,000 upvotes and I'm delighted so many of you found it useful. This time we're going to focus on a new area: reacting to and trading around news and fundamental developments. A lot of people get this totally wrong and the main reason is that they trade the news at face value, without considering what the market had already priced in. If you've ever seen what you consider to be "good" or "better than forecast" news come out and yet been confused as the pair did nothing or moved in the opposite direction to expected, read on... We are going to do this in two parts. Part I
Why use an economic calendar
How to read the calendar
Knowing what's priced in
First order thinking vs second order thinking
Knowing how to use and benefit from the economic calendar is key for all traders - not just news traders. In this chapter we are going to take a practical look at how to use the economic calendar. We are also going to look at how to interpret news using second order thinking. The key concept is learning what has already been ‘priced in’ by the market so we can estimate how the market price might react to the new information.
Why use an economic calendar
The economic calendar contains all the scheduled economic releases for that day and week. Even if you purely trade based on technical analysis, you still must know what is in store. https://preview.redd.it/20xdiq6gq4k51.png?width=1200&format=png&auto=webp&s=6cd47186db1039be7df4d7ad6782de36da48f1db Why? Three main reasons. Firstly, releases can help provide direction. They create trends. For example if GBPUSD has been fluctuating aimlessly within a range and suddenly the Bank of England starts raising rates you better believe the British Pound will start to move. Big news events often start long-term trends which you can trade around. Secondly, a lot of the volatility occurs around these events. This is because these events give the market new information. Prior to a big scheduled release like the US Non Farm Payrolls you might find no one wants to take a big position. After it is released the market may move violently and potentially not just in a single direction - often prices may overshoot and come back down. Even without a trend this volatility provides lots of trading opportunities for the day trader. https://preview.redd.it/u17iwbhiq4k51.png?width=1200&format=png&auto=webp&s=98ea8ed154c9468cb62037668c38e7387f2435af Finally, these releases can change trends. Going into a huge release because of a technical indicator makes little sense. Everything could reverse and stop you out in a moment. You need to be aware of which events are likely to influence the positions you have on so you can decide whether to keep the positions or flatten exposure before the binary event for which you have no edge. Most traders will therefore ‘scan’ the calendar for the week ahead, noting what the big events are and when they will occur. Then you can focus on each day at a time.
Reading the economic calendar
Most calendars show events cut by trading day. Helpfully they adjust the time of each release to your own timezone. For example we can see that the Bank of Japan Interest Rate decision is happening at 4am local time for this particular London-based trader. https://preview.redd.it/lmx0q9qoq4k51.jpg?width=1200&format=pjpg&auto=webp&s=c6e9e1533b1ba236e51296de8db3be55dfa78ba1 Note that some events do not happen at a specific time. Think of a Central Banker’s speech for example - this can go on for an hour. It is not like an economic statistic that gets released at a precise time. Clicking the finger emoji will open up additional information on each event.
How do you define importance? Well, some events are always unimportant. With the greatest of respect to Italian farmers, nobody cares about mundane releases like Italian farm productivity figures. Other events always seem to be important. That means, markets consistently react to them and prices move. Interest rate decisions are an example of consistently high importance events. So the Medium and High can be thought of as guides to how much each event typically affects markets. They are not perfect guides, however, as different events are more or less important depending on the circumstances. For example, imagine the UK economy was undergoing a consumer-led recovery. The Central Bank has said it would raise interest rates (making GBPUSD move higher) if they feel the consumer is confident. Consumer confidence data would suddenly become an extremely important event. At other times, when the Central Bank has not said it is focused on the consumer, this release might be near irrelevant.
Knowing what's priced in
Next to each piece of economic data you can normally see three figures. Actual, Forecast, and Previous.
Actual refers to the number as it is released.
Forecast refers to the consensus estimate from analysts.
Previous is what it was last time.
We are going to look at this in a bit more detail later but what you care about is when numbers are better or worse than expected. Whether a number is ‘good’ or ‘bad’ really does not matter much. Yes, really. Once you understand that markets move based on the news vs expectations, you will be less confused by price action around events This is a common misunderstanding. Say everyone is expecting ‘great’ economic data and it comes out as ‘good’. Does the price go up? You might think it should. After all, the economic data was good. However, everyone expected it to be great and it was just … good. The great release was ‘priced in’ by the market already. Most likely the price will be disappointed and go down. By priced in we simply mean that the market expected it and already bought or sold. The information was already in the price before the announcement. Incidentally the official forecasts can be pretty stale and might not accurately capture what active traders in the market expect. See the following example.
An example of pricing in
For example, let’s say the market is focused on the number of Tesla deliveries. Analysts think it’ll be 100,000 this quarter. But Elon Musk tweets something that hints he’s really, really, really looking forward to the analyst call. Tesla’s price ticks higher after the tweet as traders put on positions, reflecting the sentiment that Tesla is likely to massively beat the 100,000. (This example is not a real one - it just serves to illustrate the concept.) Tesla deliveries are up hugely vs last quarter ... but they are disappointing vs market expectations ... what do you think will happen to the stock? On the day it turns out Tesla hit 101,000. A better than the officially forecasted result - sure - but only marginally. Way below what readers of Musk's twitter account might have thought. Disappointed traders may sell their longs and close out the positions. The stock might go down on ‘good’ results because the market had priced in something even better. (This example is not a real one - it just serves to illustrate the concept.)
We know that interest rates heavily affect currency prices. For major interest rate decisions there’s a great tool on the CME’s website that you can use. See the link for a demo This gives you a % probability of each interest rate level, implied by traded prices in the bond futures market. For example, in the case above the market thinks there’s a 20% chance the Fed will cut rates to 75-100bp. Obviously this is far more accurate than analyst estimates because it uses actual bond prices where market participants are directly taking risk and placing bets. It basically looks at what interest rate traders are willing to lend at just before/after the date of the central bank meeting to imply the odds that the market ascribes to a change on that date. Always try to estimate what the market has priced in. That way you have some context for whether the release really was better or worse than expected.
Second order thinking
You have to know what the market expects to try and guess how it’ll react. This is referred to by Howard Marks of Oaktree as second-level thinking. His explanation is so clear I am going to quote extensively. It really is hard to improve on this clarity of thought: First-level thinking is simplistic and superficial, and just about everyone can do it (a bad sign for anything involving an attempt at superiority). All the first-level thinker needs is an opinion about the future, as in “The outlook for the company is favorable, meaning the stock will go up.” Second-level thinking is deep, complex and convoluted. Howard Marks He explains first-level thinking: The first-level thinker simply looks for the highest quality company, the best product, the fastest earnings growth or the lowest p/e ratio. He’s ignorant of the very existence of a second level at which to think, and of the need to pursue it. Howard Marks The above describes the guy who sees a 101,000 result and buys Tesla stock because - hey, this beat expectations. Marks goes on to describe second-level thinking: The second-level thinker goes through a much more complex process when thinking about buying an asset. Is it good? Do others think it’s as good as I think it is? Is it really as good as I think it is? Is it as good as others think it is? Is it as good as others think others think it is? How will it change? How do others think it will change? How is it priced given: its current condition; how do I think its conditions will change; how others think it will change; and how others think others think it will change? And that’s just the beginning. No, this isn’t easy. Howard Marks In this version of events you are always thinking about the market’s response to Tesla results. What do you think they’ll announce? What has the market priced in? Is Musk reliable? Are the people who bought because of his tweet likely to hold on if he disappoints or exit immediately? If it goes up at which price will they take profit? How big a number is now considered ‘wow’ by the market? As Marks says: not easy. However, you need to start getting into the habit of thinking like this if you want to beat the market. You can make gameplans in advance for various scenarios. Here are some examples from Marks to illustrate the difference between first order and second order thinking. Some further examples Trying to react fast to headlines is impossible in today’s market of ultra fast computers. You will never win on speed. Therefore you have to out-think the average participant.
Coming up in part II
Now that we have a basic understanding of concepts such as expectations and what the market has priced in, we can look at some interesting trading techniques and tools. 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 trimming position effect
Some key FX releases
Hope you enjoyed this note. As always, please reply with any questions/feedback - it is fun to hear from you. *** 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.
RBI & how its policies can start to affect the market
Disclaimer: This DD is to help start forming a market view as per RBI announcements. Also a gentle reminder that fundamentals play out over a longer time frame than intraday. The authors take no responsiblity for your yolos. With contributions by Asli Bakchodi, Bran OP & dragononweed! What is the RBI? RBI is the central bank of India. They are one of the key players who affect India’s economic trajectory. They control currency supply, banking rules and more. This means that it is not a bank in which retailers or corporates can open an account with. Instead they are a bank for bankers and the Government of India. Their functions can be broadly classified into 6. · Monetary authority · Financial supervisor for financial system · Issuer of currency · Manages Foreign exchange · Bankers bank · Banker to the government This DD will take a look at each of these functions. It will be followed by a list of rates the RBI sets, and how changes in them can affect the market. 1.Monetary Authority One of RBI’s functions is to achieve the goal of “Price Stability” in the economy. This essentially means achieving an inflation rate that is within a desired limit. A monetary policy committee (MPC) decides on the desired inflation rate and its limits through majority vote of its 6 members, in consultation with the GoI. The current inflation target for RBI is as follows Consumer Price Inflation (CPI): 4% Upper Limit: 6% Lower Limit: 2% An increase in CPI means less purchasing power. Generally speaking, if inflation is too high, the public starts cutting down on spending, leading to a negative impact on the markets. And vice versa. Lower inflation leads to more purchasing power, more spending, more investments leading to a positive impact on the market. 2.Financial Supervisor For Financial System A financial system consists of financial markets (Capital market, money market, forex market etc.), financial institutions (banks, stock exchanges, NBFC etc) & financial assets (currencies, bills, bonds etc) RBI supervises this entire system and lays down the rules and regulations for it. It can also use further ‘Selective Credit Controls’ to regulate banks. 3.Issues of currency The RBI is responsible for the printing of currency notes. RBI is free to print as much as it wants as long as the minimum reserve of Rs 200 Cr (Gold 112 Cr) is maintained. The RBI has total assets or a balance size sheet of Rs. 51 trillion (April 2020). (1 Trillion = 1 Lakh crore) India’s current reserves mean our increase in currency circulation is well managed. 4.Manages Foreign Exchange RBI regulates all of India’s foreign exchange transactions. It is the custodian of all of foreign currencies in India. It allows for the foreign exchange value of the rupee to be controlled. RBI also buy and sell rupees in the foreign exchange market at its discretion. In case of any currency movement, a country’s central bank can directly intervene to either push the currency up, as India has been doing, or to keep it artificially low, as the Chinese central bank does. To push up a currency, a central bank can sell dollars, which is the global reserve currency, or the currency against which all others are measured. To push down a currency, a central bank can buy dollars. The RBI deciding this depends on the import/export and financial health of the country. Generally a weaker rupee means imports are more expensive, but are favourable for exports. And a stronger rupee means imports are cheaper but are unfavourable for exports. A weaker rupee can make foreign investment more lucrative driving up FII. A stronger rupee can have an adverse effect of FII investing in markets. 5.Banker’s Bank Every bank has to maintain a certain amount of reserve with the RBI. A certain percentage of a bank’s liabilities (anywhere between 3-15% as decided by RBI) has to be maintained in this account. This is called the Cash Reserve Ratio. This is determined by the MPC during the monetary policy review (which happens every six weeks at present). It lends money from this reserve to other banks if they are short on cash, but generally, it is seen as a last resort move. Banks are encouraged to meet their shortfalls of cash from other resources. 6.Banker to the government RBI is the entity that carries out ALL monetary transactions on behalf of the Government. It holds custody of the cash balance of the Government, gives temporary loans to both central and state governments and manages the debt operations of the central Government, through instruments of debt and the interest rates associated with them - like bonds. The different rates set & managed by RBI - Repo rate The rate at which RBI is willing to lend to commercial banks is called as Repo Rate. Banks sometimes need money for emergency or to maintain the SLR and CRR (explained below). They borrow this from RBI but have to pay some interest on it. The interest that is to be paid on the amount to the RBI is called as Repo Rate. It does not function like a normal loan but acts like a forward contract. Banks have to provide collateral like government bonds, T-bills etc. Repo means Repurchase Option is the true meaning of Repo an agreement where the bank promises to repurchase these government securities after the repo period is over. As a tool to control inflation, RBI increases the Repo Rate making it more expensive for banks to borrow from the RBI with a view to restrict availability of money. Exact opposite stance shall be taken in case of deflationary environment. The change of repo rate is aimed to affect the flow of money in the economy. An increase in repo rate decreases the flow of money in the economy, while the decrease in repo rate increases the flow of money in the economy. RBI by changing these rates shows its stance to the economy at large whether they prioritize growth or inflation. - Reverse Repo Rate The rate at which the RBI is willing to borrow from the Banks is called as Reverse Repo Rate. If the RBI increases the reverse repo rate, it means that the RBI is willing to offer lucrative interest rate to banks to park their money with the RBI. Banks in this case agree to resell government securities after reverse repo period. Generally, an increase in reverse repo rate that banks will have a higher incentive to park their money with RBI. It decreases liquidity, affecting the market in a negative manner. Decrease in reverse repo rate increases liquidity affecting the market in a positive manner. Both the repo rate and reverse repo rate fall under the Liquidity Adjustment Facility tools for RBI. - Cash reserve ratio (CRR) Banks in India are required to deposit a specific percentage of their net demand and time liabilities (NDTL) in the form of CASH with the RBI. This minimum ratio (that is the part of the total deposits to be held as cash) is stipulated by the RBI and is known as the CRR or Cash Reserve Ratio. These reserves will not be in circulation at any point in time. For example, if a bank had a NDTL (like current Account, Savings Account and Fixed Deposits) of 100Cr and the CRR is at 3%, it would have to keep 3Cr as Cash reserve ratio to the RBI. This amount earns no interest. Currently it is at 3%. A lower cash ratio means banks can deposit just a lower amount and use the remaining money leading to higher liquidity. This translates to more money to invest which is seen as positive for the market. Inversely, a higher cash ratio equates to lower liquidity which translates to a negative market sentiment. Thus, the RBI uses the CRR to control excess money flow and regulate liquidity in the economy. - Statutory liquidity ratio (SLR) Banks in India have to keep a certain percentage of their net demand and time liabilities WITH THEMSELVES. And this can be in the form of liquid assets like gold and government securities, not just cash. A lot of banks keep them in government bonds as they give a decent interest. The current SLR ratio of 18.25%, which means that for every Rs.100 deposited in a bank, it has to invest Rs.18.50 in any of the asset classes approved by RBI. A low SLR means higher levels of loans to the private sector. This boosts investment and acts as a positive sentiment for the market. Conversely a high SLR means tighter levels of credit and can cause a negative effect on the market. Essentially, the RBI uses the SLR to control ease of credit in the economy. It also ensures that the banks maintain a certain level of funds to meet depositor’s demands instead of over liquidation. - Bank Rate Bank rate is a rate at which the Reserve Bank of India provides the loan to commercial banks without keeping any security. There is no agreement on repurchase that will be drawn up or agreed upon with no collateral as well. This is different from repo rate as loans taken with repo rate are taken on the basis of securities. Bank rate hence is higher than the repo rate. Currently the bank rate is 4.25%. Since bank rate is essentially a loan interest rate like repo rate, it affects the market in similar ways. - Marginal Cost of Funds based Lending Rate (MCLR) This is the minimum rate below which the banks are not allowed to lend. Raising this rate, makes loans more expensive, drying up liquidity, affecting the market in a negative way. Similarly, lower MCLR rates will bring in high liquidity, affecting the market in a positive way. MCLR is a varying lending rate instead of a single rate according to the kind of loans. Currently, the MCLR rate is between 6.65% - 7.15% - Marginal Standing facility Marginal Standing Facility is the interest rate at which a depository institution (generally banks) lends or borrows funds with another depository institution in the overnight market. Overnight market is the part of financial market which offers the shortest term loans. These loans have to be repaid the next day. MSF can be used by a bank after it exhausts its eligible security holdings for borrowing under other options like the Liquidity adjustment facilities. The MSF would be a penal rate for banks and the banks can borrow funds by pledging government securities within the limits of the statutory liquidity ratio. The current rate stands at 4.25%. The effect it has on the market is synonymous with the other lending rates such as repo rate & bank rate. - Loan to value ratio The loan-to-value (LTV) ratio is an assessment of lending risk that financial institutions and other lenders examine before approving a mortgage. Typically, loan assessments with high LTV ratios are considered higher risk loans. Basically, if a companies preferred form of collateral rises in value and leads the market (growing faster than the market), then the company will see the loans that it signed with higher LTV suddenly reduce (but the interest rate remains the same). Let’s consider an example of gold as a collateral. Consider a loan was approved with gold as collateral. The market price for gold is Rs 2000/g, and for each g, a loan of Rs 1500 was given. (The numbers are simplified for understanding). This would put LTV of the loan at 1500/2000 = 0.75. Since it is a substantial LTV, say the company priced the loan at 20% interest rate. Now the next year, the price of gold rose to Rs 3000/kg. This would mean that the LTV of the current loan has changed to 0.5 but the company is not obligated to change the interest rate. This means that even if the company sees a lot of defaults, it is fairly protected by the unexpected surge in the underlying asset. Moreover, since the underlying asset is more valuable, default rates for the loans goes down as people are more protective of the collateral they have placed. The same scenario for gold is happening right now and is the reason for gold backed loan providers like MUTHOOT to hit ATHs as gold is leading the economy right now. Also, these in these scenarios, it also enables companies to offer additional loan on same gold for those who are interested Instead of keeping the loan amount same most of the gold loan companies. Based on above, we can see that as RBI changes LTV for certain assets, we are in a position to identify potential institutions that could get a good Quarterly result and try to enter it early. Conclusion The above rates contain the ways in the Central Bank manages the monetary policy, growth and inflation in the country. Its impact on Stock market is often seen when these rates are changed, they act as triggers for the intraday positions on that day. But overall, the outlook is always maintained on how the RBI sees the country is doing, and knee jerk reactions are limited to intraday positions. The long term stance is always well within the limits of the outlook the big players in the market are expecting. The important thing to keep in mind is that the problems facing the economy needn’t be uni-dimensional. Problems with inflation, growth, liquidity, currency depreciation all can come together, for which the RBI will have to play a balancing role with all it powers to change these rates and the forex reserve. So the effect on the market needs to be given more thought than simply extrapolated as ‘rates go low, markets go up’. But understanding these individual effects of these rates allows you to start putting together the puzzle of how and where the market and the economy could go.
The cryptocurrency markets are evolving and changing at an alarming rate. New projects are created on a daily basis in support of change from the old monetary system we have all come to know and hate. Immutable code, applications, decentralized governance entities and exchanges are bringing out the best of blockchain, but sometimes these projects start off with a loud eruption of activity and volume only to fade slowly when development ends or hits a standstill, or even when a clone with more innovation becomes more popular. This is a common problem in the cryptocurrency space that has effectively created and then terminated thousands of legitimate projects and ideas looking to make a difference in this new uncharted world of cryptocurrency. Innovation always catches up, this time in the form of EcoFi. https://preview.redd.it/db42m7kcisu51.png?width=6510&format=png&auto=webp&s=f375bdf204479b7c869ecd9349f5071b068c2552 EcoFi bills itself as "an open-sourced, permission-less and censorship-resistant protocol built to power safe and responsible innovation in the Decentralized Finance space." EcoFi is focusing on putting an end to the vicious cycle or life and death of new projects by rewarding the communities strength and adoption. It plans on accomplishing this by creating a unique marketplace that builds on the principles of DeFi token pairs and an exclusive marketplace that is housed on the EcoFi website. https://preview.redd.it/q11uhakbisu51.png?width=4234&format=png&auto=webp&s=ee7ced8f4201323e19f51fa97f17c7d315ebc9d1 The EcoFi economy will consist of 3 tokens: ECO, EcoFi Genesis Token (EGT), and Sprout (SPRT) to bring about an active and innovative marketplace. ECOhas a total supply of 10,000,000 tokens and this supply is capped. ECO is earned during limiting periods which will allow you to farm it. ECO presents an opportunity to pair it with other tokens to create new and diverse liquidity pools. Staking Liquidity tokens via the EcoFi website, users can earn SPRT tokens as rewards. These tokens can also be purchased on Uniswap. ECO's other utility will include using it to obtain unique farm-able NFT's along with curation of NFT's along with other algorithmic-ally backed assets. EcoFi Genesis Token (EGT) will act as the governance token for the EcoFi ecosystem. It will allow holders to vote and help decide on future development, integration, and decision making in regards to the future of the ecosystem. EGT will also be utilized as a tool to receive airdropped ECO. The DAO Governance platform will be released at a later date. Early adopters and utilizers of the EcoFi economy will be rewarded in both EGT and ECO for helping share the EcoFi vision and helping build its community. Sprout (SPRT) is the token that is rewarded for staking your ECO. As your yield begins to sprout up from staking, you will be eligible to earn highly unique NFT's not available for purchase. These NFT's will vary in scope, but will include connections to real world assets and even rare easter-egg NFT's. The EcoFi tokens will be distributed as described below: - 50% will be given away for public contributions - 10% will be set aside for use as Eco Genesis Tokens - 20% will be utilized for airdrops and farming - 15% will be used for the Ecosystem and marketing - 5% will be sent to the core development team https://preview.redd.it/x6n4ywi9isu51.jpg?width=852&format=pjpg&auto=webp&s=af563b39b1063792f933d933e0af6e9c16d13b64 It is important to note that from 10/23/20 to 11/3 is the EGT airdrop period. During this period, users will be airdropped 1 ECO for every 100 EGT owned. The public contribution period will also last during the same time period and it will include an ECO member sale of 5,000,000 ECO. After the DAO is live, you will be able to use your EGT to vote. https://preview.redd.it/5fftge78isu51.jpg?width=924&format=pjpg&auto=webp&s=9469ad55f3a4727d2a018fd5e0f75b27fe676d1a The team behind EcoFi includes a diverse group of developers, artists, traders, and investors that have been a part of the Forex and Cryptocurrency landscape since 2014 with a focus on Ethereum's blockchain and environment. The team has top level Ethereum development skills which will allow for a productive and smooth launch. https://preview.redd.it/f0h6zik5isu51.jpg?width=931&format=pjpg&auto=webp&s=8eca52db558901fdd20037a54f4af4885a437996 Creating a sustainable and active Cryptocurrency ecosystem is difficult over time. Providing a solution via community building/tokenomical development via a decentralized self governance reward system can be the answer to the well known project burnout problem. Unique tokenomics are a very big draw for EcoFi. Adding in unique NFT’s while also planning for the implementation of real world NFT use is not only innovative but setting EcoFi up for a strong competitive build which could potentially pave the way for further NFT usecase. Following the EcoFi community and contributing may turn into one of DeFi’s biggest game-changers. Pertinent EcoFi Links: - Litepaper:https://ecofi.io/ECOFI\_LITEPAPER.pdf - Contact:[email protected] - Medium:https://medium.com/@EcoFinance/ecofi-eclisping-the-possibilites-of-defi-64b7dcf23fc1 - Website:https://ecofi.io/ - Twitter:https://twitter.com/finance\_eco - YouTube:https://youtube.com/channel/UCn\_pnNgrKWTsLSP5Jhi7MaQ - Telegram:https://t.me/EcoFiOfficial - Airdrop:https://t.me/ecofi\_airdrop\_bot (I write articles and reviews for legitimate, interesting, up and coming cryptocurrency projects. Feel free to PM me to review your project. Thank you!) ------------------- Disclaimer: This is not financial advice. The sole purpose of this post/article is to provide and create an informative and educated discussion regarding the project in question. Invest at your own risk.
The cryptocurrency markets are evolving and changing at an alarming rate. New projects are created on a daily basis in support of change from the old monetary system we have all come to know and hate. Immutable code, applications, decentralized governance entities and exchanges are bringing out the best of blockchain, but sometimes these projects start off with a loud eruption of activity and volume only to fade slowly when development ends or hits a standstill, or even when a clone with more innovation becomes more popular. This is a common problem in the cryptocurrency space that has effectively created and then terminated thousands of legitimate projects and ideas looking to make a difference in this new uncharted world of cryptocurrency. Innovation always catches up, this time in the form of EcoFi. EcoFi bills itself as "an open-sourced, permission-less and censorship-resistant protocol built to power safe and responsible innovation in the Decentralized Finance space." EcoFi is focusing on putting an end to the vicious cycle or life and death of new projects by rewarding the communities strength and adoption. It plans on accomplishing this by creating a unique marketplace that builds on the principles of DeFi token pairs and an exclusive marketplace that is housed on the EcoFi website. The EcoFi economy will consist of 3 tokens: ECO, EcoFi Genesis Token (EGT), and Sprout (SPRT) to bring about an active and innovative marketplace. ECOhas a total supply of 10,000,000 tokens and this supply is capped. ECO is earned during limiting periods which will allow you to farm it. ECO presents an opportunity to pair it with other tokens to create new and diverse liquidity pools. Staking Liquidity tokens via the EcoFi website, users can earn SPRT tokens as rewards. These tokens can also be purchased on Uniswap. ***ECO'***s other utility will include using it to obtain unique farm-able NFT's along with curation of NFT's along with other algorithmic-ally backed assets. EcoFi Genesis Token (EGT) will act as the governance token for the EcoFi ecosystem. It will allow holders to vote and help decide on future development, integration, and decision making in regards to the future of the ecosystem. EGT will also be utilized as a tool to receive airdropped ECO. The DAO Governance platform will be released at a later date. Early adopters and utilizers of the EcoFi economy will be rewarded in both EGT and ECO for helping share the EcoFi vision and helping build its community. Sprout (SPRT) is the token that is rewarded for staking your ECO. As your yield begins to sprout up from staking, you will be eligible to earn highly unique NFT's not available for purchase. These NFT's will vary in scope, but will include connections to real world assets and even rare easter-egg NFT's. The EcoFi tokens will be distributed as described below: - 50% will be given away for public contributions - 10% will be set aside for use as Eco Genesis Tokens - 20% will be utilized for airdrops and farming - 15% will be used for the Ecosystem and marketing - 5% will be sent to the core development team It is important to note that from 10/23/20 to 11/3 is the EGT airdrop period. During this period, users will be airdropped 1 ECO for every 100 EGT owned. The public contribution period will also last during the same time period and it will include an ECO member sale of 5,000,000 ECO. After the DAO is live, you will be able to use your EGT to vote. The team behind EcoFi includes a diverse group of developers, artists, traders, and investors that have been a part of the Forex and Cryptocurrency landscape since 2014 with a focus on Ethereum's blockchain and environment. The team has top level Ethereum development skills which will allow for a productive and smooth launch. Creating a sustainable and active Cryptocurrency ecosystem is difficult over time. Providing a solution via community building/tokenomical development via a decentralized self governance reward system can be the answer to the well known project burnout problem. Unique tokenomics are a very big draw for EcoFi. Adding in unique NFT’s while also planning for the implementation of real world NFT use is not only innovative but setting EcoFi up for a strong competitive build which could potentially pave the way for further NFT usecase. Following the EcoFi community and contributing may turn into one of DeFi’s biggest game-changers. Pertinent EcoFi Links: - Litepaper:https://ecofi.io/ECOFI\_LITEPAPER.pdf - Contact:[email protected] - Medium:https://medium.com/@EcoFinance/ecofi-eclisping-the-possibilites-of-defi-64b7dcf23fc1 - Website:https://ecofi.io/ - Twitter:https://twitter.com/finance\_eco - YouTube:https://youtube.com/channel/UCn\_pnNgrKWTsLSP5Jhi7MaQ - Telegram:https://t.me/EcoFiOfficial - Airdrop:https://t.me/ecofi\_airdrop\_bot (I write articles and reviews for legitimate, interesting, up and coming cryptocurrency projects. Feel free to PM me to review your project. Thank you!) ------------------- Disclaimer: This is not financial advice. The sole purpose of this post/article is to provide and create an informative and educated discussion regarding the project in question. Invest at your own risk.
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Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are. TL;DR at the bottom for those not interested in the details. This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.
For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX! I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose. This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem. I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.
I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:
I'm using the stop entry version - so I wait for the price to trade beyond the confirmation candle(in the direction of my trade) before entering. I don't have any data to support this decision, but I've always preferred this method over retracement-limit entries. Maybe I just like the feeling of a higher winrate even though there can be greater R:R using a limit entry. Variety is the spice of life.
I put my stop loss right at the opposite edge of the confirmation candle. NOT at the edge of the 2-candle pattern that makes up the system. I'll get into this more below - not enough trades are saved to justify the wider stops. (Wider stop means less $ per pip won, assuming you still only risk 1%).
All my profit/loss statistics are based on a 1% risk per trade. Because 1 is real easy to multiply.
There are definitely some questionable trades in here, but I tried to make it as mechanical as possible for evaluation purposes. They do fit the definitions of the system, which is why I included them. You could probably improve the winrate by being more discretionary about your trades by looking at support/resistance or other techniques.
I didn't use MBB much for either entering trades, or as support/resistance indicators. Again, trying to be pretty mechanical here just for data collection purposes. Plus, we all make bad trading decisions now and then, so let's call it even.
As stated in the title, this is for H1 only. These results may very well not play out for other time frames - who knows, it may not even work on H1 starting this Monday. Forex is an unpredictable place.
I collected data to show efficacy of taking profit at three different levels: -61.8%, -100% and -161.8% fib levels described in the system using the passive trade management method(set it and forget it). I'll have more below about moving up stops and taking off portions of a position.
And now for the fun. Results!
Total Trades: 241
TP at -61.8%: 177 out of 241: 73.44%
TP at -100%: 156 out of 241: 64.73%
TP at -161.8%: 121 out of 241: 50.20%
Adjusted Proft % (takes spread into account):
TP at -61.8%: 5.22%
TP at -100%: 23.55%
TP at -161.8%: 29.14%
As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker. EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.
A Note on Spread
As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits. Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way). However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades. You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term. Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.
Time of Day
Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either. On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
7pm-4am: Fewer setups, but winrate high.
5am-6am: Lots of setups, but but winrate low.
12pm-3pm Medium number of setups, but winrate low.
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate. That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.
Moving stops up to breakeven
This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers. Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability. One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)? Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Adjusted Proft % (takes spread into account): 5.36%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Adjusted Proft % (takes spread into account): -1.01% (yes, a net loss)
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right? Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Winrate(breakeven doesn't count as a win): 46.4%
Adjusted Proft % (takes spread into account): 17.97%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Winrate(breakeven doesn't count as a win): 65.97%
Adjusted Proft % (takes spread into account): 11.60%
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert. I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall. The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.
2-Candle vs Confirmation Candle Stops
Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it. Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL. Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.
As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular. Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system. This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here). Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses. Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels). Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant. One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak. EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
Total Trades: 75
TP at -61.8%: 84.00%
TP at -100%: 73.33%
TP at -161.8%: 60.00%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 53.33%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 53.33% (yes, oddly the exact same winrate. but different trades/profits)
Adjusted Proft % (takes spread into account):
TP at -61.8%: 18.13%
TP at -100%: 26.20%
TP at -161.8%: 34.01%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 19.20%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 17.29%
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much. I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system. This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions. There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated. I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful. Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.
What I will trade
Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
"System Details" I described above.
TP at -161.8%
Static SL at opposite side of confirmation candle - I won't move stops up to breakeven.
Trade only 7am-11am and 4pm-11pm signals.
Nothing where spread is more than 25% of trade width.
Looking at the data for these rules, test results are:
Adjusted Proft % (takes spread into account): 47.43%
I'll be sure to let everyone know how it goes!
Other Technical Details
ATR is only slightly elevated in this date range from historical levels, so this should fairly closely represent reality even after the COVID volatility leaves the scalpers sad and alone.
The sample size is much too small for anything really meaningful when you slice by hour or pair. I wasn't particularly looking to test a specific pair here - just the system overall as if you were going to trade it on all pairs with a reasonable spread.
Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.) I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.
I'm on the East Coast in the US, so the timestamps are Eastern time.
Time stamp is from the confirmation candle, not the indecision candle. So 7am would mean the indecision candle was 6:00-6:59 and the confirmation candle is 7:00-7:59 and you'd put in your order at 8:00.
I found a couple AM/PM typos as I was reviewing the data, so let me know if a trade doesn't make sense and I'll correct it.
Insanely detailed spreadsheet notes
For you real nerds out there. Here's an explanation of what each column means:
Pair - duh
Date/Time - Eastern time, confirmation candle as stated above
Win to -61.8%? - whether the trade made it to the -61.8% TP level before it hit the original SL.
Win to -100%? - whether the trade made it to the -100% TP level before it hit the original SL.
Win to -161.8%? - whether the trade made it to the -161.8% TP level before it hit the original SL.
Retracement level between -61.8% and -100% - how deep the price retraced after hitting -61.8%, but before hitting -100%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -61.8% to -100%. Positive 100 means it hit the original SL.
Retracement level between -100% and -161.8% - how deep the price retraced after hitting -100%, but before hitting -161.8%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -100% to -161.8%. Positive 100 means it hit the original SL.
Trade Width(Pips) - the size of the confirmation candle, and thus the "width" of your trade on which to determine position size, draw fib levels, etc.
Loser saved by 2 candle stop? - for all losing trades, whether or not the 2-candle stop loss would have saved the trade and how far it ended up getting if so. "No" means it didn't save it, N/A means it wasn't a losing trade so it's not relevant.
Spread(ThinkorSwim) - these are typical spreads for these pairs on ToS.
Spread % of Width - How big is the spread compared to the trade width? Not used in any calculations, but interesting nonetheless.
True Risk(Trade Width + Spread) - I set my SL at the opposite side of the confirmation candle knowing that I'm actually exposing myself to slightly more risk because of the spread(stop order = market order when submitted, so you pay the spread). So this tells you how many pips you are actually risking despite the Trade Width. I prefer this over setting the stop inside from the edge of the candle because some pairs have a wide spread that would mess with the system overall. But also many, many of these trades retraced very nearly to the edge of the confirmation candle, before ending up nicely profitable. If you keep your risk per trade at 1%, you're talking a true risk of, at most, 1.25% (in worst-case scenarios with the spread being 25% of the trade width as I am going with above).
Win or Loss in %(1% risk) including spread TP -61.8% - not going to go into huge detail, see the spreadsheet for calculations if you want. But, in a nutshell, if the trade was a win to 61.8%, it returns a positive # based on 61.8% of the trade width, minus the spread. Otherwise, it returns the True Risk as a negative. Both normalized to the 1% risk you started with.
Win or Loss in %(1% risk) including spread TP -100% - same as the last, but 100% of Trade Width.
Win or Loss in %(1% risk) including spread TP -161.8% - same as the last, but 161.8% of Trade Width.
Win or Loss in %(1% risk) including spread TP -100%, and move SL to breakeven at 61.8% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you moved SL to 0% fib level after price hit -61.8%. Then full TP at 100%.
Win or Loss in %(1% risk) including spread take off half of position at -61.8%, move SL to breakeven, TP 100% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you took of half the position and moved SL to 0% fib level after price hit -61.8%. Then TP the remaining half at 100%.
Overall Growth(-161.8% TP, 1% Risk) - pretty straightforward. Assuming you risked 1% on each trade, what the overall growth level would be chronologically(spreadsheet is sorted by date).
Based on the reasonable rules I discovered in this backtest:
Date range: 6/11-7/3
Adjusted Proft % (takes spread into account): 47.43%
Demo Trading Results
Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc). A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade. I'm heading out of town next week, then after that it'll be time to take this sucker live!
Date range: 7/9-7/30
Adjusted Proft % (takes spread into account): 20.73%
Starting Balance: $5,000
Ending Balance: $6,036.51
Live Trading Results
I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
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