TRADING FRAMEWORK

Drawdowns and Risk of Ruin in Action

• Risk of ruin becomes extremely low when we size our positions based on a risk of equity between 1% – 2%. Not only would it take over 100 losing trades in a row to lose all of your money, but it would also take 35 or more losing trades in a row to get to a 50% drawdown. Such losing stretches are extremely unlikely, and as such this level of risk keeps your account very safe.

• Don’t assume that if you have a very small % risk per trade (between 1% – 2%) that you can’t make very large returns. You can. If you have a 0.2 expectancy strategy that generates about 2 trades a day, you can expect to make approximately 120% on your account even while only risking 1.5% per trade.

• The great benefit of having small risk per trade is that you can trade in a much more carefree manner. No single trade is important enough to really affect your account. So you don’t end up trading with fear, and you can instead focus on correct process with discipline.

• This implies that other than being a great form of risk management, using a low fixed % risk per trade also ends up being a great psychological tool. It allows you to trade in a relaxed manner and avoid all sorts of emotional mistakes.

• If you’re trading several different markets at the same time, look at your net exposure (longs minus shorts). If you’re heavily long the market with several positions on, realize that even if those markets which are uncorrelated will likely become very correlated in the event of a crash type scenario. In this case, you should look at the overall risk in your account. If you have 6 uncorrelated long positions on and each is risking 2%, your risk is much larger than you think because they will all move down if a major negative event suddenly hits the market. If you are net short, on the other hand, you have less to worry about. But either way, you can limit your overall portfolio risk by cutting the risk per trade when you have multiple positions on.

• If you’re a discretionary day trader, it makes a lot of sense to set a daily drawdown limit. Even though your general position sizing model will be protecting you overall, letting yourself lose too much in one day can have a psychological impact that affects your trading the following days. Also, you may just be reading the market incorrectly that day, and it’s good to have an emergency stop measure that forces you to quit trading after several losses in a row. The exact limit you set will depend on your psychology, but in general it shouldn’t be too high. Even if an 8% drawdown seems small, for example, if you have a $25,000 account that’s a $2,000 loss, and it won’t be easy to swallow all in one day. The daily drawdown limit helps you avoid such scenarios. (If you’re a mechanical ‘systems’ trader, you should take every single trade system generates. But we are discretionary traders, and as such we have the power to take ourselves out of the game when we’re off and losses are mounting).

Edge in Action: Expectancy and Frequency

• The statistical term for edge is Expectancy, which is a mathematical formula that shows the expected value of a system or strategy.

• Expectancy is calculated by combining the accuracy and reward-to-risk of any given strategy. The formula is: (% winners x $ per winner) – (% losers x $ per loser)

• As an example, if you have a strategy that has 40% winners and makes you $200 per winner while losing you $100 per loser on average, you would get the following expectancy: (0.4 x $200) – (0.6 x $100) = $20. This tells you that over a large number of trades, you can expect to make $20 per $100 risked. And if you happen to risk $100 per trade, this means that you’ll make $20 per trade over a large number of trades.

• A positive expectancy means that you have an edge in the market. A zero expectancy means you have no edge. A negative expectancy means that you have a negative edge. In the first case (positive), you can expect to make money over a large number of trades. In the second case (zero), you can expect to make no money over a large number of trades (loss when you account for commission). In the last case (negative), you can expect to lose money over a large number of trades.

• When we’re looking at the short-term (i.e. a small number of trades), any of these expectancy strategies (positive, zero, or negative) can make or lose money. It’s only over a large number of trades (due to the law of large numbers) that the strategy realizes its expectancy.

• In statistics, the smallest statistically significant number is 30. However, if you want to calculate the expectancy of your strategy, we recommend you use at least 100 trades. This can more safely be considered a large number in which the law of large numbers will more likely kick in.

• Expectancy doesn’t have to be calculated in overall dollar terms. If you specify the risk-toreward part of the equation as a ratio (e.g. If we have $200 per winner and $100 per loser, the ratio would be a 2:1), then we arrive at an expectancy per dollar risked. So an expectancy of 0.4 would be telling us that we can expect to make 40 cents per dollar risked. If, in turn, our average trade risks $100, then we can expect to make $40 ($100 x 0.4) per trade. Calculating expectancy in this way allows you to compare different strategies that may be using different account sizes and risk per trade. It allows you to compare them on an apples-to-apples basis by looking at the amount each makes per dollar risked.

• Our case study showed that while most traders want accuracy because it feels good to be right and ring the cash register, you really need to look at overall expectancy. Indeed, many of the systems you see being advertised online truly do have a great 90%+ accuracy, but what they don’t tell you is the expectancy of the system. Most often, such systems have very large losers and very small winners. This makes the reward-to-risk profile very weak, and often makes the system a negative expectancy system despite the high accuracy.

• Our case study also showed that a very low accuracy system or strategy can still have a positive expectancy and make money if the reward-to-risk profile is large enough. Many great traders (especially the trend followers), have accuracies in the 30% range and yet make huge amounts of money year over year.

• The other variable that determines the value of a strategy or system other than expectancy is Frequency. This variable tells you how many trades you have in a given period of time. Frequency combines with expectancy to give you the true value of your trading system or strategy.

• All things being equal, if you have two strategies with the same expectancies, the one with the higher frequency of trades will make you more money. If, on the other hand, you have two strategies with the same frequencies, the one with the higher expectancy will make you more money. If both frequencies and expectancies are different, multiply the expectancy by the average $ per winner, and then multiply that result by the frequency to find out how much money the strategy or system will make you. For example, if we have a 1.2 expectancy strategy (very good number) and we make $500 on average per winner, while taking 750 trades a year, we would make: 1.2 x $500 x 750 = $450,000. (If the expectancy is negative, multiply by the average $ per loser to know how much the strategy will lose you. The higher the frequency of trades, the more you’ll lose).

• Your first goal as a developing trader is to build your market reading abilities and trading skills to the point where you have a positive expectancy strategy. Once you have one, you can look at how to increase the frequency of those trades (i.e. find more good trade setups to take). But first you need the positive edge before you do anything else.

The Importance and Dynamics of Position Sizing

• It’s not enough to have a positive expectancy strategy. Incorrect position sizing can make you lose your whole account even while using a positive expectancy strategy. This can happen because if you size your positions too large, short-term luck can give you a stretch of losers that put you out of the game.

• Incorrect position sizing can often come from making wrong assumptions about probabilities. You fall for the gambler’s fallacy and believe that just because you’ve had a stretch of losing trades, you are now due for a winner. But the reality is that the odds of the next trade are completely independent from the past. No matter how many losing trades you’ve had in a row, the odds of the next trade being a winner do NOT increase. So don’t fall for this illusion and don’t be misguided by your feelings.

• The conclusion we come to is this: You can only realize the expectancy of a strategy by employing correct position sizing. This means that you’ll only achieve the expected results of a good strategy if you can stay in the game long enough for the probabilities to play out. But incorrect position sizing will take you out of the game too early, and therefore you won’t realize the expectancy of the strategy.

• You can make hundreds of mistakes in your market reads, strategy, and execution, but if you have correct position sizing (and discipline in exiting your losing trades quickly), you will survive. You will survive long enough to build your skills and become profitable. Conversely, you can do everything right in your market reads, strategy, and execution, but if you have incorrect position sizing (and are undisciplined in exiting your losing trades), you will lose all of your money. It’s not IF, it’s WHEN.

Overcoming the Hidden Psychology of Losses

• There are definite solutions to the obstacles that keep traders from cutting their losses. The feelings at the root of the obstacles may never disappear (since they are natural human emotions), but they can be countered with different ways of thinking that can keep them from unconsciously determining your behavior.

• The first solution is to understand and respect market realities. And the major market reality is that anything can happen at any time. The great traders all believe this to their very core. They realize that you can never truly predict anything in the market (you can just put the odds generally in your favor over a large number of trades). They realize that it only takes one major player to come off the sidelines and change the whole picture instantly. They realize that the markets can become ‘irrational’ and that they can stay irrational far longer than we as traders can stay liquid if we let our losses get larger.

• The outcome of understanding market realities is that great respect is born for the market. You realize that it can take you out of the game at any time if you don’t practice great risk management. And, indeed, you become more afraid not to cut your losses than you are afraid to take them. You fear the market’s power too much not to respect it. In this way, ‘discipline’ regarding stop losses becomes automatic. It’s regarded as a given that you wouldn’t dream trading without.

• The second solution is to understand probabilities and learn to think in these terms. You realize that it’s not about any given trade and whether it’s a winner or a loser. Rather, it’s about your overall edge or expectancy. So it’s about thinking in terms of a long series of trades and their overall outcome, with losing trades being a natural part of that long series of trades. The losing trades are already factored into your strategy’s expectancy, so there’s no reason to actively avoid them. Instead, you take each trade realizing that sometimes it’ll work and sometimes it won’t, and since you can’t predict which one will or won’t, you just execute all of them with discipline and take your losses quickly with discipline knowing that this is the other way (the first being correct position sizing) to realize the expectancy of your system or strategy.

• If you’re a beginning or developing trader that has yet to build a positive expectancy strategy and become consistently profitable, losses are still not a ‘bad’ thing to be avoided because they are your tuition for learning to trade the markets, and this tuition or investment will eventually lead to a great return. Indeed the only way to realize your eventual goal and return the tuition is to cut your losses quickly, take them with discipline, and stay in the game as you learn..

• The final solution is to understand yourself. This simply means to be consciously aware of the underlying feelings that act as obstacles for you. Awareness in itself is very powerful, and it builds its own momentum. When you become aware of certain feelings like the need to be right and fear of failure, and you watch them from a detached and non-judgmental point of view as they arise while you’re trading, you take them from the unconscious to the conscious level. Now they’re not running the show on automatic and leading you to conditioned repeatable patterns of destructive behavior. The key is to catch the feelings as they arise without trying to stop them. Just feel them and don’t judge them. If you let yourself feel them and even verbalize them to yourself, their power over you greatly diminishes. Now you’ve made them conscious and you’re no longer their slave.

• Traders have a wrong concept that they’ve been told which tells them to shut off their emotions. That is, to trade with no emotion. You must realize that this is not possible. As long as you’re a human being, you’ll have emotions and in and of themselves they’re neither good nor bad. Even so called negative emotions are neutral. The key is to not let your emotions unconsciously drive your behavior. That’s what trading with no emotion should really be taken to mean. It’s not that you don’t feel emotions. It’s that your conscious awareness of them and non-judgmental detachment from them allow you to trade well despite them. This is important to understand. If you try to suppress and deny them, they will unconsciously drive your behavior in a negative way.

• Once you bring all these three solutions together, you will now have acceptance of risk and losses. You accept the risk before you take the trade, and you accept the loss as it happens. Ultimately, what all of the obstacles were causing was a lack of acceptance of risk and losses. That’s the real problem. Once you can accept them, discipline becomes natural and easy.

• Therefore when you accept risk and losses (which comes from implementing the three solutions consistently and diligently) you realize that being ‘wrong’ is okay and just a part of a probabilistic game, and you understand that losses don’t mean you’re a failure, and you know that you can afford losses, and you’re not overconfident about your market reads, and you don’t try to avoid losses. i.e. You overcome the obstacles to being disciplined about cutting losses and not having excessively large losers.

• If you’re disciplined in this (along with position sizing), you can make every other mistake in the book and still survive and eventually prosper. If you’re not disciplined in these aspects, you won’t last long enough to make and retain any real money as a trader.

• The practical way to be disciplined with position sizing is to consistently use and unwaveringly stick to a good model with low risk per trade. And the practical way to be disciplined with losses is to:

Always use stop-loss orders on every single trade (indeed you need a stop-loss to be able to size positions correctly anyways or else you won’t know your true risk).  

Never revise your stop-loss while in a trade unless that revision decreases or keeps the risk constant. This means that if you want to widen your stop-loss because of legitimate factors, you need to decrease your position size accordingly (i.e. exit some of your position instantly) to keep the risk constant. Otherwise, you can tighten up your stop losses, which effectively reduces risk.

Systemizing Risk Management Through R-Multiples

• Through the previous sessions we’ve learned that good risk management is a combination of correct position sizing and correct trade management. The former is all about taking small percentage risk per trade, and the latter is all about consistently ensuring that you don’t take losses that are larger than your small predetermined risk by always being disciplined with stop losses.

• To systemize and simplify the whole process of risk management so it’s easy to understand, implement and track, you can use the concept of R-multiples. This concept has been used for decades by professional traders and money managers. It was introduced and popularized to the public by prominent trading coach and psychologist Van Tharp, who we all owe a big debt of gratitude.

• In any trade you take, you have an Initial Risk = R. If you’re using the % risk model, this R will always be equal on any trade you take in terms of percentage of your account balance. In this way, different setups and different markets can have equalized risk always represented by R, no matter how large or small the stop-loss is (because the position size will adjust for the stop size to keep % risk constant). So you represent each initial risk with R, no matter the size of the stop-loss.

• The R-multiple is simply a positive or negative multiple of R. If you have a profit on the trade, you will have a positive R-multiple. If you have a loss, you will have a negative R-multiple. For example, if you’re using a 2 point stop-loss and you have 4 point winner, your R-multiple is 2. That is, you’ve just made 2 R (or twice as much as you risked). If using a 4 point stop, you have an 8 point winner, your R-multiple is also 2. If using a 3 point stop, you have a 3 point loser, your R-multiple is -1, and you’ve lost 1 R.

• Using R makes expectancy very easy to calculate. Simply add up the total R of all the trades you’ve made and divide by the number of trades. You can do this because expectancy is nothing more than the average profit (or loss) per trade. i.e. How much can you expect to make (or lose in the case of a negative expectancy) per trade.

• To calculate expectancy and R-multiples correctly, you have to include the commissions you pay. To do that, you simply equate the commission to the point value of the instrument you trade. For instance, if you trade the ES (S&P 500 Futures) and you pay $5 commissions per round turn (i.e. as a total commission based on entry and exit), then this commission equals 0.1 ES points (since each ES point equals $50). So if you have a 2 point stop, your R is actually 2.1 points because that’s how much you’ll lose on the trade when commissions are added in (i.e. that’s your true risk). If now you make 4 points in profits, your actual net profits are 3.9 points (4 – 0.1). So your R-multiple would be 3.9 / 2.1 = 1.86 R. If you lose 2 points, your real loss would be 2.1 points, so it would be a -1 R trade. If you trade the NQ (NASDAQ 100 Futures) with $5 round-turn commissions, it would be equal to 0.25 NQ points, because the NQ trades at $20 a point. If you trade stocks there would be no need to convert anything because stocks don’t have a point value. You would just add in the $ commissions.

• To compare different trades and see which one was truly better, you simply look at the Rmultiple. The one with the higher R-multiple was the more profitable trade, regardless of the number of points the trade earned. For example, let’s say you have a $20,000 account and risk 2% per trade. Your risk is currently $400 a trade. On trade 1, you have a 2 point stop and get a 5 point winner. Forgetting about commissions for simplicity’s sake, this would have been a 2.5 R trade, which means you made $1000 (you know it’s $1000 because 2.5 x your R of $400 is $1000, and also because your position size must have been 4 contracts to give you $400 risk on a 2 point stop, and 4 contracts x 5 points x $50 a point = $1000). On trade 2, you have a 1 point stop and you get a 4 point winner. Now even though this winner is a 1 point less than the previous one, it’s actually the more profitable trade and you can easily see this when looking at R-multiples. This is a $1600 winner, because it’s a 4 R trade (4 x $400, or 8 contracts x 4 points x $50 a point).

• So tracking R-multiples automatically forces you to think in terms of Reward-to-Risk. You’re no longer looking at how many points you made on a trade, but rather at how many points you made in comparison with how many points you risked. The multiple is what matters.

• Using R-multiples also simplifies everything because now can now compare different setups, trades, timeframes, or markets, all on an equal risk basis. Even if you use different % risk for different setups or markets, you can still compare the pure edge of the trades through Rmultiples. The different % risk will just be a matter of higher or lower position sizing, but the edge will be determined through expectancy which can be calculated simply by adding up the R-multiples and dividing by the # of trades even without knowing what % risk is used on any given trade.

• Most importantly, using R-multiples brings together all aspects of risk management and forces you to use them. To even use the concept of R, you have to have a stop-loss, and you have to be using a consistent position sizing model to size each R appropriately, and you have to stick to your stop-loss because your goal will be to never have a loss that’s great than -1 R. Those losses will quickly damage your expectancy, and you’ll always be on alert to not let them happen because your focus is on R and expectancy instead of on trying to avoid taking losses.

 • The side benefit is that it also switches your focus from accuracy to large Reward-to-Risk trades, as you start trying to get the large R-multiples that can really improve your expectancy. • Using this system and recording your trades in an Excel file or journal in this way will give you a complete risk management system that will allow you to survive for the long-run and become a consistently profitable trader. It’s the simplest and easiest way ever devised to help you achieve this goal, so be sure to use it, because your competition is.

Understanding Drawdowns and Risk of Ruin

• Your #1 goal and priority in trading is capital protection. You need to stay in the game. If you think you can outsmart or figure out the markets and take bigger risks, you will lose your money. There is no question about that. The markets can stay irrational much longer than you can stay liquid. In plain terms, the markets can act weird and do things you think are impossible for them to do, and they can keep doing them far longer than your account size can handle- no matter how much money you have. Traders of all sizes, from 1 lot traders to multibillion dollar hedge funds, have experienced the harsh results of not understanding and truly believing that.

• There are two broad paths to losing your capital:

 o Going through a losing stretch while risking too much of your account per trade (incorrect position sizing).

 o Not cutting losses quickly and thereby ending up with losers that are too large (incorrect trade management).

• When you hit a losing stretch after reaching an Equity peak in your account, the size of the losses is called the Drawdown. The low point of the drawdown is called the Equity trough. The equity curve of a consistently profitable trader will look like an upward trending price chart. It will have successively higher equity peaks interrupted by regular draw-downs. Losing is a normal part of trading, even as the profitable trader makes money overall.

• What is considered an acceptable drawdown? This depends on math and also on your personal psychology. The math shows that the larger your drawdown, the greater the return percentage you need to make just to get back to break-even. This means that the more you dig yourself into a whole, the harder it is to get out of it. The psychology aspect of it tells us that if you lose a large percentage of your account, say 50%, even though mathematically speaking it’s still possible to recover, practically speaking you will likely become far too emotional and will start trading based on fear. The result is that your psychology won’t be able to recover and you’ll likely lose the rest of your money or be forced to quit.

• Given this, you should not accept a drawdown of more than 25% or 30%. It may need to be much lower than that for your personality, but no matter who you are, this should likely be your upper limit that you choose

Understanding the Hidden Psychology of Losses

• The #1 rule in trade management is to cut your losses quickly. You need to take small losses and make sure to never let a loser become large. Taking large losers is the most common reason why traders fail.

• The way to take small losses is two-fold. One is something we discussed in previous sessions, which is to size your positions correctly based on a small fixed % risk. The other is to have a predetermined stop-loss (which indeed is needed for you to be able to size positions using the % risk model in the first place), and to stick to that stop-loss when the market moves against you and hits it. It does no good to size positions correctly but then let the loss get larger and larger than what you pre-determine on trade entry.

• There are some major obstacles to cutting losses quickly:

  o The need to be right. Most people would rather be right than happy, and most traders would rather be right than make money. The proof of this is found in the fact that most traders would choose an 80% accuracy strategy that has a 0.2 expectancy over a 30% accuracy strategy that has a 0.5 expectancy (all else being equal) that will make much more money. It simply feels good to be right and ‘predict’ well, and it feels terrible to be wrong.

  o Feeling like taking losses is a failure. No one likes to feel like a failure. And trying to avoid this bad feeling causes traders to not want to take a loss because it is equated with failure. o Thinking you can’t afford the loss. If you think you can’t afford something, you will do everything in your power to avoid it. Traders especially feel like this when they’ve had several losers in a row or are in a general drawdown.

  o Over-confidence in your market reading abilities. Researchers have proven time and again that we are all over-confident about our prediction abilities. This over-confidence leads us to believe that we can predict the market with high accuracy and to have great faith in our predictions. And when you believe something strongly, your mind will filter reality to confirm your belief. If you think the market is going up, every up-tick will be taken as a confirmation of your views. And it’ll start to feel wrong to take the loss because you think your prediction will be proven right at any moment. So you let the loss get larger and larger as you wait for it to happen.

  o Trying to avoid losses. This doesn’t seem like an obstacle. In fact it seems like a good thing to try to avoid losses. But the problem here is that the assumption that losses are bad is what causes you to want to try to avoid losses, and yet the assumption is a faulty one. If there were no losses, there could be no winners. They’re just the other side of the coin, and they can’t be avoided. Losses are just a part of the game.

• Due to these obstacles, traders end up willing to take unwise gambles that can result in large losses, rather than being willing to take a sure small loser. They become risk-seeking in the realm of losses. The mind finds numerous reasons to rationalize the decision and make it seem like a logical choice. But in reality it NEVER is. We all have an unlimited ability to deceive ourselves. Always remember that and be aware of it when your mind is trying to rationalize why it’s better to not take the loss. Your mind will always make the reasons seem convincing, and will ‘reward’ you with great feelings if your risky behavior ends up allowing you to avoid the loss. This is the worst thing that can happen because in the bigger picture this behavior will cause you to lose all of your money.

Understanding Trading Edge

• Understanding basic probabilities is key to understanding trading edge. And having a trading edge is key to becoming a consistently profitable trader.

• Whether you’re flipping a coin ten times or one million times, you never know on any given flip which side it’ll land on. But the difference in the million flip scenario is that it is a large enough number of flips to allow the laws of probability to play out. In that scenario, you’re very likely to get close to 500,000 of each side. Whereas in the 10 flip scenario, the result could easily be titled to one side just based on short-term randomness. This shows that in any probability distribution, luck dominates in the short-term (making things seem random and chaotic), but the probabilities play out in the long-term and luck gets largely cancelled out.

• Most traders don’t really understand how short-term ‘luck’ and long-term probabilities work. They attempt to be right on any given trade that they take, not realizing that this is like trying to flip heads on a coin. That is, they try to control short-term luck (which can’t be controlled), while they really should be focusing on the long-term probabilities of their trading. Having a great strategy with appropriate risk and money management can ensure good long-term probabilities that will make you money, but you can never know how your wins and losses will be distributed (i.e. their order). That part is random (or luck), whereas the total results of that random distribution of wins and losses is not luck.

• The casino industry is a good example of an industry that makes use of the concepts of luck and long-term probability distributions. On any given roll of the dice or draw of the cards, luck reigns supreme and people can beat the casino. But over the long run, the ‘edge’ is in the casino’s favor. That is, the probabilities are in its favor, and in the long-term the random distribution of wins and losses will be tilted by a slight percentage towards the casino. This is how they continually make money in an arena that seems to be governed by luck. It’s just simple math and the law of large numbers at work.

• As a trader, you have to learn to think like a casino. You have to focus on the long-term, and not on the results of any specific trade. Just focus on the correct process, and if you’ve built a good strategy with solid money management (all things that we teach you in this training program) the odds will play out in your favor in the long run and you will make money. This is one of the secrets to trading. It’s a game of probabilities. [Note: the ‘long-run’ is not a specified period of time, but rather depends on how frequently you trade. If you’re an ultra active scalper who takes 1000 trades a month and has a good edge, it’s possible that you’ll never have a losing month because that is a large enough number for the ‘long-term’ probabilities to play out].

• The second coin flip experiment demonstrates that statistical edge can be arrived at in two different ways. On one end of the continuum we have Accuracy and on the other side we have Reward-to-Risk. The experiment showed that even if you have low accuracy, you can still come out ahead if your reward is high enough relative to your risk. That’s why a trading strategy of only 30% winners can still be very profitable if the winners are much larger than the losers.

• Accuracy and the reward-to-risk profile combine to give you edge in trading. The combinations that can produce a positive edge are literally infinite. Edge, in turn, is the expectation of how much money you’ll make over a large enough number of trades.

• The most fundamental thing you need to make money as a trader is an edge. Without a real edge, the best psychology and analysis is useless.

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