The ULTIMATE Guide to Risk Management

Welcome to the ultimate guide to risk management.

In this course, you're going to learn everything from basic concepts to advanced risk management techniques that will help you protect and grow your capital responsibly and intelligently.

You're going to learn many secrets about risk management and actionable tools that will put you ahead of other traders who only pay attention to strategy.

This course is divided in two major parts.

In the first part, you're going to learn several concepts and intuitions about how risk works and how you should approach it since there are many non-obvious pitfalls and hidden dangers when it comes to risk in trading.

In the second part, you're going to learn the actionable riskmanagement techniques.

Just so you can have a taste, you're going to learn the two main challenges of risk management, the relationship between technique, risk, and behavior.

The ship and minefield analogies.

The science of winning in losing streaks.

Illusions and fallacies of risk management.

The power of compounding.

The asymmetry of wins and losses.

The main prospect theory insight.

The danger of leverage.

Misconceptions about consistency and edge.

Win rates and riskreward ratios.

Statistical pitfalls of risk management.

Several types of stop and take-profit targets.

Risk transformation techniques position sizing models, including the ones used by trading champions averaging and martingale, antifragility and derivatives risk, and much more.

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Let's begin the course by talking about basic intuitions about risk and the properties of how profits and losses occur over time. To truly understand what risk is, we must first grasp the concept of uncertainty.

Uncertainty is the state of not knowing what will happen. Risk is the measurable part of uncertainty. It is the quantifiable potential for loss or harm that you are prepared to tolerate if the outcome goes against you. This leads us to a powerful conclusion about how trading truly works. You can never know whether you win or lose the next trade regardless of how good your strategy is or how good you are as a trader, but you can and absolutely should know exactly how much you're willing to lose if things go wrong.

It is impossible to eliminate uncertainty because in trading we are always dealing with the future and the market is too complicated to be perfectly predicted.

But with proper risk management, we can neutralize the danger of uncertainty and survive the market in the long term.

Notice that before thriving in the long term, you must learn how to survive.

The trader essentially faces two core challenges in risk management.

The first is how to minimize the size of stop- losses without increasing the likelihood of being prematurely stopped out while also maximizing profit targets without leaving gains on the table.

The second is determining the optimum amount of capital to risk in each trade to ensure maximum account growth without exposing the account to a dangerous level of risk.

In summary, sizing your exposure and managing that exposure for optimal and safe growth in the long term.

Even though this sounds simple, there's a lot that goes into it and there are many hidden dangers waiting for you.

As is always the case in trading at this point, it's common knowledge that successful trading lies in the intersection of three main areas.

Trading technique, trading psychology and risk management. Like I said previously, trading technique is never perfect.

No matter how great your strategy is, you cannot know the outcomes of your trades with certainty.

Trading psychology is an even bigger problem because the behavior of traders under uncertainty is deeply complex.

Just so you can have an idea about how deep this problem is, in this image we have what's called a cognitive bias codeex.

Each one of these lines is a cognitive bias we all have.

Cognitive biases are basically patterns of thinking that deviates us from what is rational.

These are the things steering your behavior without you even realizing it in most cases.

You cannot eliminate biases in trading just like you cannot eliminate risk.

You can only manage them. Our behavior is complicated and full of nuances since most cognitive biases are unconscious.

Life circumstances affect your trading behavior.

Knowing what to do doesn't mean you will do it. Having a plan doesn't mean you will follow it and so on.

The third leg of this tripod is risk management and is the only thing you can fully control.

And because of that, it can be used to mitigate the imperfections of the other two major aspects of trading.

Whenever traders begin to experience losses, their instinctive reaction is often to change something, switch time frames, try a different market, or adopt a new strategy.

This leads to a neverending cycle of reoptimization, constantly chasing the illusion of a perfect strategy.

But in a lot of cases, the real problem is not the strategy.

The true solution often lies in risk management.

Yet, ironically, it's the last thing most traders address because it's not as exciting as seeking the new trading technique that will solve all your problems. With that said, risk management is not a magic wand.

You cannot just use any strategy and expect it to become profitable through risk control alone.

Not all strategies are created equal.

Some are based on sound market principles while others are illusions dressed up with indicators or false narratives.

It's clear that certain strategies and concepts are inherently more robust than others.

It's self-evident that price action and order flow are better than trying to trade based on moon cycles, for example.

In general terms, bad risk management can destroy a good trade. You can be correct about the future direction of price, but if you place your stop- loss in the wrong place, you will lose money despite being correct about the future direction of price.

However, good risk management can mitigate the damage of a bad trade.

In that sense, risk management is more important than trading technique.

Risk management allows you to survive the market and make money even with lots of mistakes along the way, which is great news.

Although trading technique trading psychology, and risk management are often taught as separate disciplines, in reality, they constantly interact and influence one another.

Your trading technique affects your behavior.

A clear, well- tested strategy builds confidence and reduces hesitation.

On the other hand, a vague or inconsistent method can lead to second-guing, fear, and impulsive decisions.

Your behavior affects your execution of both technique and risk management.

Even the best strategy fails if you panic, overtrade, or deviate from your rules under pressure.

Risk management affects your behavior.

When you know exactly how much you stand to lose, you reduce fear and decision fatigue.

Poor risk management, on the other hand, amplifies emotional swings and undermines discipline.

Risk management also shapes your technique.

Knowing how much capital you're risking can influence which setups you choose how aggressively you enter, and how you scale in or out. In short, these three domains form a feedback loop.

You cannot fully optimize one without understanding its effects on the others.

Mastery in trading comes not from isolating these components, but from integrating them into a coherent framework.

Even though risk management is the most controllable aspect of trading, it doesn't exist in a vacuum.

is directly influenced by other elements, your trading technique and your behavior which are far less controllable.

So while the mechanics of risk management are simple and fully within your control, the execution of those mechanics depends on variables that are not. That's why you cannot afford to overlook any part of the trading tripod, technique, psychology and risk.

They are deeply interconnected, and a weakness in one can undermine the strength of the others.

This leads us to a paradox in risk management.

Even though risk management is fully under the trader's control when observed in isolation, its application depends on variables that are not fully controllable like the trader's behavior, personality, life circumstance, access to information, and risk, tolerance.

, For example, there are two very useful analogies for you to grasp the true power of risk management and the way you should approach it.

The first analogy is of a ship in a seatorm. Imagine you are going out on the sea and there is a 100% chance of going through not one storm but several.

You can choose between two types of vessels, a large ship or a small one.

Which vessel would you choose?

The large ship is slow but is steady and built for durability.

It's designed to withstand rough conditions and long journeys. It might not reach the destination quickly, but it almost always survives the storm.

This is analogous to the responsible trader focused on sustainability, consistency capital preservation, and most importantly, the ability to survive the dangerous moments that will inevitably come.

On the other hand, this small boat is fast, agile, and thrilling.

It can reach high speeds and get to the destination faster, but is fragile.

One large wave can easily flip it over.

There is no room for error and no margin for safety.

This is the overleveraged trader chasing fast gains but extremely vulnerable to wipe out. If you know beforehand that you will have to go through not one but several storms in a very long journey, which vessel would you choose?

At this point, it should be obvious to you that the large ship is the best alternative because long-term sustainable trading is all about surviving the market in the first place.

It's not about how fast you can get to your destination or the thrill of the ride.

It's about whether you get there at all.

Ironically, in trading, the slow way is the fastest way to build capital because it's the only approach that can actually survived long enough to reach the long term.

High-speed, high-risk strategies may create bursts of growth but they eventually collapse.

Slow discipline growth through consistent risk management and strategic patience might feel boring in the short term, but it's the only path that compounds over time.

Sustainability beats intensity.

In the long run, the trader who survives is the trader who wins. Don't get hung up on the performance achieved in trading competitions, for example.

Because even though there are many impressive results, competitions are a sprint.

Trading your own capital is a marathon.

The second analogy is the minefield analogy.

Trading is like crossing a minefield.

Trying to predict where the minds are is like using technical analysis.

It is necessary and it helps but by itself is too dangerous.

There are several things one can do in order to reduce the chances of stepping on a mine.

For example, you can take fewer steps, take shorter paths, step lightly follow blast marks, stand still when unsure, and wear armor.

These are all things under your control and they have nothing to do with predicting where the mines are.

They are smart moves to counteract the fact that you cannot predict where the minds are precisely.

Just like in trading where risk management serves the purpose of counteracting the fact that technical analysis is imperfect. In the retail trading world, everyone is worried about becoming consistently profitable.

But beginners often interpret this as consistently making money as if it was possible to become your own ATM machine and produce an endless winning streak.

That is an illusion. The type of consistency you should be after is consistency of behavior. That is the only thing that will allow you to overcome the losing streaks and draw downs that will inevitably appear no matter how great you are as a trader.

So consistency of profits in the long term is an illusion because drawdowns are inevitable.

It's only possible in the short term, but consistency of behavior is not only possible but a prerequisite for long-term survival.

So remember consistently profitable means consistency of behavior that leads to overall profit in the long term with many losing streaks and draw downs along the way.

Every trader worries about losing streaks and dreams about winning streaks for obvious reasons.

The reality of how streaks happen hide a few pitfalls though, and we need some concepts to understand why that's the case.

To make this as simple as it can be, let's imagine a series of coin tosses.

This is a useful exercise because everyone is familiar with the simple probabilities of a coin toss.

We have 50% chance of heads and 50% chance of tails.

Very simple.

Imagine now a series of three coin tosses.

Imagine also that all three of these coin tosses resulted in heads.

If we calculate the probability of the actual experiment, we'll reach the conclusion that there is a 100% chance of getting heads in a coin toss.

That is called experimental probability.

However, we know there is a 50/50 chance of heads or tails. So, how is this possible?

The answer lies in the number of coin tosses in the experiment. The larger the number of tosses, the closer the experimental probability will come to the theoretical probability.

In statistics, this is called the law of large numbers.

The experimental probability gets closer to the theoretical probability as the sample size grows.

translating that to a trading paradigm.

You cannot judge your ability based on a few trades.

As your sample of trades increases, the reality of your ability will begin to truly emerge.

And this goes both ways.

If you were right in the last four out of five trades, it doesn't mean this 80% win rate will continue as the sample of trades increases.

On the other hand, if you were wrong in the last four out of five trades, it doesn't mean that this 20% win rate will continue.

Also, the big lesson here is that short-term results and small samples are highly illusory and do not represent what's going to happen in the long term.

This is the illusion of getting funded by a prop firm nowadays, which can be done with very few trades. When a trader receives a certificate, the trader feels like his or her ability has been verified or proven. Needless to say most funded traders lose the funded account right after, proving that small samples of trades lead to illusory conclusions about performance.

Another concept related to streaks is the theory of runs. The theory of runs is a concept from probability theory that studies sequences of similar outcomes in a series of independent trials.

These sequences are called runs.

So a winning or losing streak is a run.

This theory allows us to calculate the probability of streaks of various sizes occurring which is given by this formula.

The probability of n losses in a row is equal to the loss rate to the power of n. So for example, let's say that a trader has a win rate of 60% therefore having a loss rate of 40%.

and he wants to calculate the probability of a losing streak with five losses in a row.

Plugging these values in the formula will have a probability of just 1.024%.

This seems like good news because the probability of an unusually large losing streak seems too small. But there is a fundamental flaw in this idea.

The theory of runs assumes that trials are independent, which is not true in trading, mainly because the last trade will alter how you treat the next one in most cases.

and your strategy responds differently to different market conditions.

So loss rate is variable. This is the feedback loop between technique, risk management and behavior we talked about previously.

Winning or losing the current trade will affect how you manage the next one.

Beginner traders assume that in every trade there is a 50/50 chance of winning or losing because there are only two possible outcomes.

But that's not true.

Unlike a fair coin toss, stops and targets are not equally probable.

Market conditions are not random.

Your strategy, entry, exit, and risk management matter.

Biases, emotions, and skill also play a role here.

Technical analysis, trading psychology, and risk management are all about skewing risk in your favor.

If there was a 50/50 chance in each trade, all we would need to make money is to use a riskreward ratio greater than one. But in reality, that's far from being enough.

In trading, the misunderstanding of how probabilities work lead to the gamblers's fallacy and the hot hand fallacy.

The gamblers's fallacy is assuming that a winning trade is more likely to happen after a losing streak.

The reality is that a losing streak causes a psychological effect that increases the chances of the losing streak continuing.

On the other hand, the hot hand fallacy occurs when a trader believes that a winning trade increases the chances of another winning trade occurring and therefore the greater the winning streak, the greater the likelihood that it will continue. This is the mirror image of the gamblers's fallacy in a way and it is also an illusion.

Both winning and losing cause psychological effects that can impact the next trade.

In the case of winning, a winning streak can cause the trader to overlook important aspects of technique and management out of overconfidence, which will of course increase the chances of a loss rather than increasing the chances of a win.

In the case of losing, the trader assumes that it's not possible to have an unusually large losing streak.

And therefore, as the losing streak grows the odds will naturally tilt to the trader side, also causing the trader to overlook important aspects of technique and risk management, but for a different reason.

Another thing that many traders also overlook is the inherent asymmetry of wins and losses, which puts all traders in a disadvantageous position before they even start trading. This is very simple to understand with a practical experiment.

Imagine that you have $100,000 and you experience a loss of 10%.

Your account will go to 90,000.

In order to go back to the 100,000 you now need a profit of 11.1%.

The greater the draw down, the greater this asymmetry becomes. In this table you can see how drastic this can be.

A 50% loss requires a 100% profit just to break even.

A 90% draw down requires a whopping 900% profit just to break even.

Another way of looking at this is that if you make a 10% win, therefore going to 110,000 you need a loss smaller than 10% to destroy your profit. In this case, a 9.09% loss would be enough.

In this table, you can see the other side of this asymmetry, meaning the required loss to break even after a given profit.

Let's take this to the extreme for illustration sake.

If you have a 90% draw down in your account, you need a 900% profit to go back to the starting position.

However, if you have a 90% profit in your account, you only need a 47.37% loss to wipe it out. This is one of the reasons you should aim to make more than what you risk in every trade to compensate for this asymmetry.

Another hidden danger in risk management lies in the use of variable leverage.

Using leverage is basically borrowing money to supercharge the potential profits.

Everything has a cost though and traders often ignore the fact that leverage also supercharges losses.

Many thousands of trading accounts have been wiped out in minutes because of leverage.

Beyond the obvious danger there are more subtle problems with leverage.

If a trader uses different levels of leverage in different trades usually based on gut feeling about the trade outcome, which is a very stupid idea since trading is a game of incomplete and asymmetric information this trader can actually lose money by being right.

Let me demonstrate mathematically how that's possible.

Imagine that a trader produces a series of unleveraged returns.

If we calculate the accumulative return we'll observe 4.73% of profit.

However if the trader uses variable leverage and ends up overleveraging the trades that go bad, he will end up with a negative cumulative return despite producing positive and leveraged returns.

Make no mistake about it, if you rely on gut feeling to do this, you will develop an amazing ability to leverage the wrong trade.

New traders usually focus on the win rate because we all have the innate need to be correct. However, the win rate by itself is meaningless in trading.

A trader with a high win rate can lose all his money and a trader with low win rate can make money in the long run.

The secret here is to always judge the quality of your win rate relative to your average riskreward ratio.

A high riskreward ratio allows you to have a much lower win rate and still profit in the long run. A small ratio requires you to have a high win rate in order to stay in the game. For example, let's say a trader has 30% win rate and an average riskreward ratio of 1 to 3.5.

A 30% win ratio seems too low, but in the context of a 3.5 ratio, it's more than enough because for this ratio, the break even win rate is only 22.2%.

So, this trader will make money despite the low win rate. In order to know the break even win rate for a given riskreward ratio, you can use this simple formula.

1 divided by 1 plus the riskreward ratio.

If you have a poor riskreward ratio, you need to be correct most of the time and that by itself will already place you in a disadvantageous position psychologically speaking.

A higher ratio allows you to make lots of mistakes and still make money.

We'll go back to riskreward ratios later.

The Peltzman effect is when safety measures such as a stop-loss order end up increasing risk instead of decreasing it.

That's possible when traders assume that just because they are using a stop, they are safe.

Based on that, they will overlook many other important aspects of risk management.

Therefore, increasing the overall risk despite using a stop-loss order.

The classic example of the pelman effect is when drivers using seat belts feel safer and therefore drive more recklessly, which in turn increases the chances of an accident defeating the purpose of using the seat belt in the first place. The point is to understand that stop- losses and seat belts are just one safety measure.

They are not full protection. You can still make lots of terrible riskmanagement mistakes even if you have a stop-loss in all your trades.

Risk management is about efficient protection and growth of capital.

And in order to fully understand how that works, we need to understand the intricacies of compounding.

Compound interest is often times referred to as the eighth wonder of the world.

It is in fact what can create massive wealth in the long term.

To quote Benjamin Franklin, "Money makes money and the money that money makes makes more money." However, for compounding to do its magic, you need to reinvest your profits. Traders tend to focus on the wrong part of compounding.

Let's look at the compound interest formula to see why that's the case.

When we look at this formula, it becomes clear that time is the most important factor of all because it is used as an exponent and beyond that time is always on your favor since time only moves forward.

Traders have the bad habit of focusing on the return which is exactly the part of this formula that cannot be fully controlled.

If you want to experience the amazing effects of compounding, you have to give up this idea of withdrawing profits to make a living. Like Charlie Mer says the first rule of compounding is never interrupted unnecessarily.

In a sense, the opportunity cost of trading for a living is the possibility of experiencing massive wealth in the future.

Trading for a living gives you cash flow, but it costs you a fortune in the end.

By understanding that compounding is the most powerful force in the financial markets and time is its main driver, it becomes clear that trying to make a lot of money quickly is a vain exercise.

Some traders spend their whole life trying to figure out how to make money quickly.

Meanwhile, all this time could have been used to compound returns slowly and steadily, creating substantial wealth over time.

Many retail traders have a lopsided view of what it means to have an edge.

They don't understand the phrase you find in every financial disclaimer.

Past performance does not guarantee future results.

That means that it's perfectly possible for you to lose your edge.

The market is not a static entity and neither are you. It's a highly dynamic environment where inefficiencies go in and out of existence. In order to properly calculate your edge, you need the expectancy formula.

For example, let's say that a trader has 45% win rate, an average win of $30, and an average loss of $10. If we plug these values in the expectancy formula, we'll observe that this trader currently has an edge of $8 per trade. But then again these numbers will change over time.

So you can only calculate your current edge.

In other words, you cannot say that you are profitable. You can only say that you have been profitable.

Prospect theory developed by psychologists Daniel Canaman and Emma Stiverki and later earning Canaman the Nobel Prize in economics mathematically demonstrates how humans tend to become riskaverse in gains and risk-seeking in losses challenging the assumption of rational decision-m in classic economic theory.

That happens because we are fundamentally loss averse. A loss feels worse than an equivalent gain feels good.

This can be visually understood with what is called the S-shaped value function in prospect theory. Like we can see here, the negative value obtained from a loss is greater than the positive value obtained from an equivalent gain.

This shows why you want to stay in the trade when you are losing and why you want to close the trade as soon as it becomes profitable.

In the first case you are afraid of realizing the loss and in the second case, you are afraid of losing what you already conquered.

In other words, the prospect theory shows that human beings are predictably irrational unlike classic economics which assumes we always seek to maximize utility.

This leads to a powerful idea that sits at the intersection between risk management and trading psychology.

The idea of delayed gratification.

It's impossible to be successful in the long term in the financial markets without an ability to delay gratification.

This is the true meaning of discipline.

Delayed gratification is the ability to resist the temptation of an immediate reward in favor of a larger and more enduring reward in the future.

This concept deeply rooted in psychology and behavioral economics is a cornerstone of effective risk management in trading.

Discipline is basically your capacity to delay gratification.

To quote Abraham Lincoln, "Discipline is choosing between what you want now and what you want most.

" It's the art of saying no today so you can say better yes tomorrow so to speak.

The ability to delay gratification is also crucial if you want to trade with higher riskreward ratios and lower win rates. In a sense delaying gratification is the price you must pay for having margin of error and peace of mind in trading.

Another important aspect of risk management is risk tolerance.

Different traders using the same strategy will produce different results. And it's not just because of their technical ability.

Traders have different risk tolerances because risk tolerance is not just a trading concept.

It's a psychological and biological trait shaped by multiple personal and contextual factors.

This is part of the reason why different traders with the same strategy will produce different results.

Risk tolerance is shaped by neurochemistry psychological makeup, financial situation, experience level, life circumstance, cultural and social influences, and cognitive biases.

In other words, risk tolerance is the intersection between psychology biology, and environment.

One very basic and yet effective rule about risk is that if you are worried or bothered by being stopped out, you are risking too much. What might be too much risk for you can be too little risk for someone else.

Risk, like beauty, is in the eye of the beholder, so to speak. In other words there's not a formula that will tell you how much you should risk in each trade because that depends on your risk tolerance, and each trader is different.

It's also useful to understand a little bit how the brain perceives risk and how that perception will alter your behavior.

Taking too much risk can literally impair your brain's ability to make rational decisions. When you take excessive risk, your amygdala, the brain sphere center, becomes hyperactive.

This triggers a fightor-flight response releasing cortisol, known as the stress hormone and adrenaline, which is responsible for arousal and vigilance.

These chemicals shift your brain away from careful rational thinking and towards survivalbased decision-m.

The prefrontal cortex, the thinking brain gets impaired.

The prefrontal cortex is responsible for logical reasoning, weighing probabilities delaying gratification, and long-term planning.

But under stress in fear from high risk, cortisol dampens the activity of the prefrontal cortex.

This means your brain starts relying more on habitual, impulsive, or emotion-driven decisions, often managed by more primitive parts of the brain.

Dopamine distorts your perception of reward.

When you take big risks, the dopamineergic system lights up in anticipation of a large reward.

But high risk and reward overstimulate the system leading to overconfidence bias, optimism bias, and an inability to assess losses realistically.

You might feel euphoric even when the odds are against you. It's similar to addiction where a person chases the high rather than perceiving the consequence of chasing the high. Too much stress narrows your cognitive bandwidth.

Cognitive load becomes overwhelmed when you're juggling fear, uncertainty, and the need to perform. This narrows your working memory and attention span making it harder to analyze information spot patterns, and stick to your plan.

In essence, your brain blinds itself to reduce overload, which leads to poor judgment.

All of this is triggered when your brain senses there is too much risk.

The neuroscience of risk-taking obviously goes much further than this, but this is one example of how your brain will sabotage itself as a survival mechanism.

Remember, the danger detecting part of our brain evolved in a time when human beings were trying to avoid lions in the savannah.

It's not fine-tuned for trading.

Let's now turn our attention to the allimportant riskreward ratio.

The riskreward ratio is a fundamental concept in risk management.

It compares the potential profit of a trade to its potential loss.

Understanding its properties is at the core of successful trading.

Let's begin with the definition and types of ratios and then we'll move on to their properties.

The riskreward ratio is nothing more than the size of the reward divided by the size of the risk you're taking as is given by this formula.

Right from the start, it's important to understand the different types of ratios. Mainly, we have the initial, final, and average riskreward ratios.

The initial ratio is the one before the trade is open.

It's an estimation of the final ratio.

The final ratio is the one when the trade is closed.

It's useless to have a good initial ratio if you're going to mess around with the stop and target in the middle of the trade in such a way that will hinder the final ratio.

So the final ratio is more important than the initial ratio.

The average ratio is simply the average of all final ratios.

The first property of ratios is asymmetry.

Meaning that good riskreward ratios are asymmetric by design in order to compensate for the problems we saw previously.

mainly the asymmetry between profits and losses or inherent loss aversion and the possibility of making money despite being wrong most of the time.

The expectancy of a strategy depends on the riskreward ratio and the win rate.

A high riskreward ratio can compensate for a low win rate.

A low riskreward ratio requires a higher win rate to be profitable. In general, a low ratio requires high win rates and high ratios require low win rates to be profitable.

This is why it doesn't make sense to analyze the win rate of a strategy in isolation without considering the average riskreward ratio.

Ratios can be fixed, meaning that once the trade is opened, the ratio doesn't change and the market will either hit the stop or target you originally planned, meaning that the initial and final ratios are the same.

Ratios can also be dynamic, meaning that you will alter stop and target placement while the trade is opened in the attempt to enhance the final riskreward ratio.

Obviously, you are not supposed to alter the stop and target in such a way that the final ratio becomes worse than the initial ratio because that would render the initial ratio meaningless.

The placement of stops and targets is dependent on market structure.

The stop loss must be placed in such a way that reduces the possibility of being prematurely stopped and the target must consider whether there are support and resistance and significant fair or unfair value zones along the way.

You need to assess this before you enter the trade.

Sometimes the trade makes sense from a technical perspective, but the low riskreward potential invalidates it.

Trend following strategies usually require much larger ratios in comparison to mean-reverting strategies, for example, which can be profitable with lower ratios.

Higher ratios usually mean that you need to be more patient and delay gratification, which can be difficult depending on your psychological makeup.

Lower ratios don't have that problem, but on the other hand, they increase the pressure to be correct most of the time, which is perhaps a more difficult challenge.

With all else maintained equal, the linear reduction of stop-loss size produces a nonlinear increase in riskreward ratio.

This is why precision is so important in trading.

Even a slightly better entry can dramatically increase your final riskreward ratio.

For example, if you have a 1:3 trade and you reduce the stop size in half by getting a better entry you will increase the riskreward ratio to seven.

However, as you'll see later this can shift the different kinds of risks in a trade. Given all these intuitions about risk, technique, and behavior, it's now time to study the tools a trader can use to avoid these problems as much as possible and achieve the main goals of risk management.

The tools a trader has for controlling risk in a trade are the stop-loss and the take-profit target.

And even though this sounds like a simple thing to manage there's a lot that goes into the definition and management of stop and target.

The incorrect management of these tools can destroy your capital even if you have a good trading technique and discipline.

Let's begin first by talking about the stop-loss. The stop-loss is the level where the trade idea is invalidated.

The stop-loss serves various purposes such as the protection of capital from large draw downs, the definition and quantification of risk before entering the trade, maintainance of discipline and prevention of emotional decision-m and the possibility of proper position sizing based on risk tolerance.

A stop-loss being triggered does not necessarily mean you're going to lose money.

There are special situations where a stop-loss means profit.

The stop-loss means you're going to stop losing, but that can mean a smaller profit, too.

Let's talk about the different kinds of stop-loss orders.

A technical stop is based on trading technique, meaning that is placed in such a way that it minimizes the chances of being hit while minimizing potential loss, too.

Placing a stop below a demand zone creates a cushion of protection for a long trade, for example. A money stop is a stop based on the amount of money you are willing to lose in that particular trade.

This is usually a bad idea because the market doesn't care about the amount of money you are willing to lose. Your stop should not be based on what you want. You should be based on what the market is doing like what happens in a technical stop.

A mental stop, also called a discretionary stop, is when a trader exits a position voluntarily without actually placing a stop-loss.

The trader decides mentally that it's time to get out of the market.

This is a very stupid idea because you'll be influenced by what's happening in the moment and without a plan, the alternation between risk-seeking and risk averse behavior will lead you to ruin.

Not to mention the other mathematical pitfalls of risk we already went over.

A timebased stop is a stop that is triggered once the trader has been exposed to risk in a particular trade for a determined amount of time.

The reasoning is that if the trade doesn't take off in a certain amount of time, it's better to get out of it.

This is also not a good idea most of the time because there are many situations where the trade seems like it's not going to work, but then it does.

Beyond that this predetermined amount of time is arbitrary.

The volatility stop is a stop based on the current volatility of the market, usually measured through the ATR or standard deviation. The trader will choose an ATR multiple, for example, and use that to calculate the stop- loss.

This makes sense because it's based on information given by the market.

A combined stop is when a trader places the stop in such a way that makes sense in terms of technique and in terms of volatility simultaneously.

So, the stop has a double layer of protection, so to speak.

This is probably the best alternative in terms of logical stop-loss placement.

Sometimes the added layer of protection provided by the volatility stop will prevent you from being stopped out in a trade that makes sense but suffers from a small bull or bear trap before taking off, for example. The liquidity based stop is one special type of technical target that aims to exit a position where extreme levels of liquidity exist.

The rationale behind this is that liquidity pools tend to be targeted for manipulation.

So the idea is to place a stop using these pools as a cushion of protection.

You can learn more about liquidity in the video in the card.

The break even stop is a special situation when the stop-loss order is moved to the entry level.

In that way, if the trader is stopped out, it doesn't lose any money to move your stop to break even.

However, it is necessary that the market moves enough into profitable territory.

Otherwise, you can end up breaking even in a trade that would have been profitable.

A trailing stop is a stop-loss that is progressively moved into profitable territory over time to lock in the profits in a good trade.

The trader must be careful to move the stop strategically to avoid being stopped out prematurely.

There are many types of trailing stops, but the one that makes the most sense is the structural trailing stop, where the trader moves the stop dynamically behind market structure that is less likely to get hit.

One important rule about the stop-loss is that you should never increase the size of your stop once the trade is opened because that defeats the purpose of planning the stop before the trade and it messes up the management of risk.

Let's now move on to the different kinds of take-profit targets. First looking at the basic definition, the take-profit target is the level where the trade idea is validated.

It's a level where trying to make a greater profit is not worth the risk.

Let's see the different kinds of take-profit targets.

The fixed R multiple is a way to determine the target based on a multiple of the stop size regardless of market information.

This removes the cognitive pressure of deciding an optimal place to put the target, especially if it is a dynamic target.

This simplifies the process, but it's not optimal. For example, you can always use a target three times larger than the risk.

A technical target is just like a technical stop.

It's planning the exit of a trade on the location that makes technical sense.

This can also serve as a filter not to enter the trade.

If the entry looks good, but the trade doesn't have enough profit potential, it's best not to enter the trade.

Just like you can define a stop-loss based on market volatility, you can define a target based on volatility as well.

This is a type of target that adapts to the market and it's defined based on a multiple of ATR or standard deviation.

A timebased target is the idea of getting out of a trade that has been opened for a predetermined amount of time.

The hypothesis is that if the trade doesn't hit the target in a certain amount of time and it's already in profit, it's wiser to close it with a smaller profit.

This is usually not a good idea because the final riskreward ratio can suffer. We can dynamically alter targets based on what the market is doing.

Needless to say, you should never decrease your target, at least not in a way that will erode your final riskreward ratio.

Channel lines and pitchforks are good examples of tools you can use for dynamic targets.

The longer you stay in the market, the greater the reward, so to speak.

The liquidity based target is one special type of technical target that aims to exit a position where extreme levels of liquidity exist.

The rationale behind this is that liquidity pools tend to be targeted for manipulation.

So there is a greater chance that these levels will be hit and then the market will reverse.

Therefore optimizing the target. We can divide risk management in two main categories.

Passive management and dynamic management.

Successful risk management lies in the intersection between these two categories.

In simple terms, passive management is the control of risk before a trade is open.

So stop-loss type, risk sizing, position sizing, and initial riskreward assessment.

Dynamic management is the control of risk after the trade is open.

So the minimization of risk through trailing stops and or scaling out, maximization of profit with dynamic targets and or scaling in, risk transformation to maximize positional exposure, and management of realized profits.

In summary, the intersection between passive and dynamic management allows traders to maximize the units of profit obtained per unit of risk taken in a way that maximizes growth and minimizes the overall risk of ruin in the long term.

Let's talk first about passive management.

The very first decision of passive management is risk sizing. This is the percentage of your capital you're going to risk in every trade. There are many different approaches to determine how much you should risk in each trade.

Let's take a look at the most common methods which are the fixed fractional fixed dollar risk, fixed units volatility based sizing, fixed ratio and the Cali criterion.

In the fixed fractional method, you always risk a fixed percentage of your capital in each trade. For example, you can risk 1% of your account in each trade, and you're going to calculate your position size based on that percentage and the size of your stop-loss.

For example, let's say you trade forex, and the trade you want to make has a 20 pip stop-loss.

You also decided to use the fixed fractional model, risking 2% of your capital in each trade.

You have a $10,000 account.

To calculate your position size, you need to multiply your capital by the risk level you chose. So 10,000 * 2% which equals $200.

This is known as the dollar risk or capital risk.

Now you need to adjust the position size based on your stop size.

You do that by dividing the dollar risk by the size of your stop.

So $200 divided by 20 equals $10 per pip.

In forex, one lot gives you $10 per pip.

So in this case, you would need to trade one lot.

If your stop was 10 pips instead of 20, you would need to trade two lots to maintain the same dollar risk in this trade. In other words, the position size, which is the number of shares, contracts, or lots you trade will vary according to the stop-loss size in order to maintain the dollar risk consistent across trades.

The advantage of this method is that risk scales automatically as the account grows or shrinks. The disadvantage is that the recovery from deeper drawd downs can be more difficult due to the asymmetry between profits and losses we saw before.

Next, we move to the fixed dollar risk.

In this method, you're always going to risk the same dollar amount per trade regardless of account size and stop size.

For example, you can decide to always risk $100 per trade. You need to calibrate the position size so that your stop-loss represents this fixed dollar amount.

Like in the previous method, the advantage of this is that it maintains losses consistent in dollar terms, but the disadvantage is that risk percentage changes irrationally as the account grows or shrinks.

Fixed units. In this method, you're always going to risk the same number of shares, lots, or contracts regardless of account size and stop-loss size.

The advantage here is that it's a very simple way of calculating position size.

The disadvantage is that risk sizing and dollar risk will fluctuate irrationally.

Volatility based sizing. In this method you're going to adjust your position size depending on the market volatility usually measured through the ATR indicator or standard deviation.

In high volatility markets, you will decrease position size and in low volatility markets, you will increase position size.

The advantage is that this keeps risk consistent across different market conditions.

The disadvantage is that it can be tricky to calculate especially when you are trading lower time frames where you need to make quicker decisions.

Fixed ratio. This method was created by Ryan Jones and it was introduced in his book called the trading game.

In this method, you are only going to increase position size when the account reaches a profit milestone called delta.

Ryan Jones establishes a formula for you to calculate the number of contracts you should be trading according to accumulated profit in your account and the delta which is defined by the trader.

The formula goes as follows.

For example, if you have an accumulated profit of $12,000 and you define a delta of $2,000, the fixed ratio formula will return four contracts.

The advantage is that you don't have to calculate position size in each trade but your equity still scales geometrically.

You only update position size when the profit milestone is reached.

The disadvantage relies on the fact that delta is arbitrary and can vastly change how the equity scales.

Kelly criterion.

This method tells you what percentage of your account risk to maximize the long-term growth rate of your equity.

It's a formula developed in 1956 by Joan Kelly Jr. originally for optimizing signal to noise ratios in telecommunications later applied to betting in trading by the mathematician hedge fund manager and blackjack player Edward Thorp.

The formula goes as follows.

To calculate the risk size according to the Kelly criterion, first you need a significant sample of your trades in order to calculate your win rate and average riskreward ratio.

And it cannot be 10 or 20 trades.

The larger the sample, the better.

Remember the law of large numbers in statistics. So for example let's say you have a sample of 100 trades.

Your win rate is 60% and your average win is 200 and your average loss is 100.

So an average riskreward ratio of two.

If you put these numbers in the Kelly formula, it will return a whopping 40%.

meaning that according to your stats the Kelly criterion states that you should risk 40% of your capital in each trade to maximize the long-term growth rate of your equity. This is the riskmanagement model used by Larry Williams in his iconic Robins Cup Championship victory in 1987. He took a $10,000 account to $1,147,67 in one year, yielding an astonishing 11,376% return.

In his famous book, Long-Term Secrets to Short-Term Trading, Larry Williams admits he did not know very well what he was doing at the time regarding the formula, but it ended up working for him since he had a high win rate.

He also warns against the use of folk Kelly which often suggests extremely high risk percentages.

Ral Fence, a friend of Larry Williams warned him about the problems of using Faux Kelly.

Ral Fins has some of the most advanced books on money management.

If you're interested, it's worth checking it out. One of the fatal flaws of the Kelly criterion is that it assumes that win rate and average riskreward are constant, which simply doesn't happen in real life.

For instance, if your win rate is even slightly overestimated, you can suffer catastrophic drawdowns.

The volatility of your equity curve meaning the standard deviation of returns, is huge using this model.

For this reason, it is recommended to use what is called half kelly or fractional kelly, where only a fraction of the full kelly number is used to decrease the massive risk.

The Cali criterion is a datadriven position sizing model meaning that you need a sample of trades first to calculate your win rate and average riskreward ratio.

Ralph Fins also proposes other datadriven methods such as optimal F and secure F.

Optimal F is calculated directly from your historical trade results to find a fraction of capital that would have maximized the geometric growth if those results repeated.

Secure F also uses the same historical data, but it applies an additional constraint, essentially adjusting the fraction downward to account for risk tolerance, draw downs or capital preservation objectives.

These are more advanced methods, so we're not going to look into them in this guide.

If you want to investigate them, you can find more about them in Ralph Vince's books.

Andrea, a systematic trader and four-time Robin's Cup champion, also has a good book about money management.

There's no single best method for every trader.

The choice depends largely on your risk tolerance. What matters most is being honest about your own risk appetite and understanding the strengths and weaknesses of each model.

Risk sizing and consequently position sizing compose the bulk of passive management.

But there are other important matters to address such as this type of stop-loss you're going to use according to the ones we already listed and also the fact that you can use riskreward as a technical filter.

Let's move on to a more complex matter which is dynamic management meaning the management of risk after the trade is opened.

The first aspect of dynamic management is to maximize the number of open trades without increasing the overall risk exposure which is something that can only be done with special risk transformation techniques we're going to talk about later. The second aspect is the minimization of risk and maximization of reward and therefore maximization of the final riskreward ratio according to the market scenario or strategy being traded.

It's not always optimal to shoot for the highest riskreward ratio.

it's not realistic.

You must tailor it according to the type of strategy you trade and the market context.

The third aspect is the management of realized profits, meaning how the trader is going to reinvest the profits.

The decision to reinvest the profits you've made and how you're going to risk those profits again can have a huge impact on your equity curve.

Recall that to enjoy the wonders of compound interest, you must reinvest your profits at least partially.

Most traders only think about withdrawing money from the account for obvious reasons.

But the possibility of reinvesting profits and even adding capital periodically can also have a dramatic effect on the equity curve.

Before we move on to risk transformation techniques, we need to grasp the different types of risk and the concept of risk conservation. Let's begin by defining the different types of risk.

The first one is capital risk.

This is the most obvious risk of all, which is the amount of capital you are prepared to lose if the market goes against you and your stop-loss is triggered.

The second type is positional risk.

This is a slightly less obvious type of risk but a very important one.

Positional risk is the risk of a stop-loss being triggered.

The closer the stop is to the entry, the higher the positional risk because market noise can end up triggering the stop- loss, even if the trader is correct about the future market direction.

Positional risk represents how bad management can spoil a good entry.

Imagine being right about the direction of the market, but being stopped because you placed the stop- loss in the wrong place.

Positional risk can also be understood from the point of view of the target.

The farther away the target is from the entry, the less likely it is from being triggered. This is mainly why strategies that use a higher riskreward ratio tend to have smaller win rates.

If the target is too far away from the entry, for example, you can have periods where the trade has significant profits but then the market can turn against you and you will miss that profit.

In other words, if the target is too far away you can spoil a perfectly valid trade as well.

Another important point here is that scalping strategies that use a tight take-profit target can create the illusion of skill because market noise can end up triggering the small target in the same way that it can trigger a tight stop even if the trader is correct about market direction.

That will generate an illusory high win rate.

The third type was called target risk.

This is the risk of making a smaller profit than would be optimal.

It happens when you scale out of a position in order to lock in some profit.

For example, by locking the profit, you are accepting to make a lower profit in the case the market hits your target.

The key to understand risk conservation relies on the concepts of opportunity cost and trade-off in economics.

Opportunity cost is the value of the best alternative you give up when you choose one option over another.

This idea is closely related to the concept of trade-off which is the idea that you must sacrifice one aspect to gain in another.

The economist Thomas Soul states that in economics there are no solutions only trade-offs.

So for example, if you use some technique to reduce capital risk in a trade, you will end up increasing positional risk or target risk depending on how you do it.

In other words, you cannot eliminate risk.

You can only transform it.

That's the idea of risk conservation.

Some kinds of risk are more desirable than others depending on the situation.

So that's why you want to engage in risk transformation despite the fact that risk is conserved. For example, whenever you change one of the risks, you are impacting the others. So you should be able to understand what that impact is.

There are many ways the three different kinds of risks interact.

For example imagine you are along five lots and your stop size is 10 pips. That gives you a total capital risk of $500.

You want to reduce capital risk, so you decrease your stop size to five pips.

Your capital risk is now half, but your positional risk is double since the stop loss is closer to the entry.

In other words, you transformed capital risk into positional risk.

Let's now imagine a different scenario where instead of moving the stop to decrease capital risk, you scale out of the position to do so.

Imagine that you are in a profitable trade and you scale out of it in the sufficient amount to cancel out the stop- loss in case it happens.

In that case, you decrease capital risk by increasing target risk.

Positional risk stays the same. We're going to see how to scale out of a trade in a moment.

The point of these examples is to show you how risk is conserved.

You cannot decrease one type of risk without increasing another.

The reason you want to engage in risk transformation despite the fact the risk is conserved is because by eliminating capital risk in a trade, you can open another trade simultaneously without increasing overall account exposure.

For example let's say you have one open position with capital risk of $1,000.

Your total account exposure is $1,000.

Imagine now that you eliminate the capital risk by transforming it into target, risk,, for example., Now, your, total capital risk became zero, but you still have the chance of making a profit in the trade.

At the same time, you can open another trade, which will bring the overall account exposure to the same $1,000.

The benefit is that now you have two different opportunities to make a profit because you have two open trades, but your exposure did not increase.

In that sense, positional and target risk are preferable to capital risk because they represent the possibility of breaking even or making a smaller profit rather than losing money. That is a smart way of using chance to your advantage in trading.

The idea is to free a trade from capital risk while you attempt to maximize its final riskreward ratio. With that said let's study the different risk transformation techniques more carefully.

We have four main risk transformation techniques.

Roll to break even, scaling out, double stop collapse and break even and scale out.

The first and simplest technique is to move the stop-loss to break even once price has sufficiently moved into profitable territory.

In other words, you are eliminating capital risk by increasing positional risk.

This does not work if you move the stop to break even as soon as the trade becomes profitable.

You need margin of error and a good reason to do that which will be grounded on trading technique.

If your stop is too close to the current price, this technique will work against you rather than for you. Recall that the closer the current price is to the stop, the higher the positional risk. So for example let's say you are currently in a 30 pips of profit and your stop is 10 pips.

You will simply bring the stop loss to the entry point.

If the market goes against you, you will break even.

In other words, you will either get out of the trade with a profit or you will break even.

The second technique allows you to eliminate capital risk without moving the stop- loss. It consists in partially closing the trade in the sufficient amount that will neutralize the stop-loss in case it happens.

This eliminates capital risk by increasing target risk.

If the trade hits your target after scaling out, you will make a smaller profit in comparison to the same trade without scaling out.

To know how much of the trade you need to liquidate, we need a formula.

Let's call the distance from the entry to the stop S and the distance from the entry to the current price P. The amount to liquidate will be given by S / S + P * your original position size. In this case you will scale out of the trade using 1.25 lots, which will lock a profit of $375.

The open trade now remains with 3.75 lots rather than the initial five.

If your stop is triggered, you will have a loss of $375.

In other words, if you are stopped out your locked profit will neutralize the amount lost.

The third way of transforming risk is the double stop collapse.

For this, you will need two open trades.

This technique consists in moving both stop-loss orders to the midpoint between the two entries.

If the market goes back and triggers both stop-loss orders, they will cancel each other out.

This is one situation where averaging up leads to the elimination of capital risk.

For example, let's say you are long in two trades, one lot each and 10 pips stop-loss each. Like so.

The double stop collapse consists in moving both stop-loss orders to the midpoint of the two entries. Let's say that the market turns against you and hits that stop.

you'll make a loss in the upper trade and a profit in the lower trade.

And since they are equal, you will break even.

So you are eliminating capital risk by increasing target risk in the lower trade, making a smaller profit than optimal, and increasing the positional risk in the upper trade by getting stopped out prematurely.

This technique also requires that both trades are in decent profit first.

The fourth way of transforming risk is a combination of the first two.

You will move the stop loss to break even and then you will scale out in order to lock in some profit. The amount of profit you will lock is arbitrary since the stop- loss is already collapsed. This not only eliminates capital risk, but it puts you in a position where you can only get out of the trade with a profit.

It's a question of how much profit will be.

These are the main ways of eliminating capital risk in the trade. But we still need to maximize riskreward in the trade as much as possible through trailing stops and dynamic targets.

Let's now talk about a risk control technique that can enhance the entry price of a trade called averaging.

Averaging consists in splitting a trade into multiple price levels.

The average entry price of the trade will change depending on how the positions are executed.

For example, let's say you want to execute a trade of 200 shares.

You have two alternatives. You can trade all 200 shares at the current price.

Or you can split this trade in order to alter the average entry price.

For instance, let's say you execute 100 shares at $50 and the other 100 shares at $40.

By doing that, you are lowering the average entry price of the position.

In this case, to calculate the average entry price, you need to sum the capital risk of all splits and then divide by the total number of shares executed.

In this case, the average entry price is $45, which is exactly halfway between 50 and 40.

This is an example of linear averaging where the position is split into equal parts. We can also engage in nonlinear averaging, which is when the position is split into unequal parts.

That can alter the average entry price in useful ways.

Let's take the same example, but instead of splitting 200 shares in two trades of 100 shares each, we'll execute 50 shares at 50 and 150 shares at 40.

Notice that the average entry price is much closer to the lower position due to its heavier position size.

You can use averaging to enhance the entry price of a trade.

Instead of executing a whole position you can test the waters, so to speak.

For example, imagine that you want to go long because you think the market has bottomed out.

You decided to split your trade two positions based on the fact that the market often misleads you and continues going down. The total position is 400 shares and you're going to use nonlinear averaging to get a better price.

You first execute a long position of 100 shares at $100. The market then creates another leg down and then you execute another long position of 300 shares down.

By calculating the average entry price, you can see that in this case, it is as if you had entered the 400 shares long position at $92.5 which is much better than $100.

Needless to say, you need to establish limits for this. You want to decide the total position size beforehand and then split the number. You cannot simply keep averaging because if the market doesn't turn, you're going to face a massive draw down.

Since this is a riskmanagement course, we need to talk about the famous Martingale approach.

In theory, the martingale is a foolproof way of always making our profit regardless of losing streaks.

But in practice, it's a surefire way of losing all you have because it overlooks a simple limitation every trader has which is capital. I do not recommend you engage in Martingale. I'm just going to demonstrate it so you can understand its fatal flaw.

Imagine this. Every time you have a losing trade, you double the position size in the next trade.

Eventually, when a winning trade happens, you will recover from the losing streak and then make some additional profit.

That is a mathematical guarantee.

However, people who advocate for Martingale approaches forget, ignore, or are not aware of the gamblers's fallacy and the fact that you can run out of margin before that winning trade comes to save your equity.

So in summary, Martingale works, but only if you have infinite money, which you don't.

So it doesn't work at all.

It's a mathematical trick that only works in theory. To counteract the stupidity of the Martingale approach let's now talk about something extremely powerful.

One thing that I have talked about a lot in the past is the idea of antifragility in trading, which is a concept outlined by the mathematician Nasim Nicholas Tale.

This is perhaps one of the most sophisticated concepts in risk management.

To understand what interfragility is, we need to grasp the difference between fragility robustness, and antifragility.

Something fragile is something that is easily destroyed by volatility in chaos.

The best example of this is a high leverage scalping strategy in the middle of a volatile market. It is extremely fragile and susceptible to failure.

Something robust is something that survives volatility and chaos.

An example here is a good trading strategy with sound risk management principles that is able to survive in the long term despite market turbulence.

Something antifragile is something that not only survives but thrives on volatility and chaos. In trading there are antifragile strategies in the realm of derivatives trading.

Such strategies are designed to profit when black swan events, chaos, and volatility hits the market.

The great thing about this is that there's always some bad news happening.

There's always a war going on.

The president of some country says something stupid, natural disasters, and so on.

There's a saying in trading that the only certainty in the financial markets is that there is going to be uncertainty.

Antifragile trading strategies capitalize on the one certainty about trading which is uncertainty itself.

A great analogy here is that wind quickly extinguishes a candle but it only energizes a forest fire.

A high leverage speculative trading strategy is like a candle in the wind very vulnerable.

An antifragile trading strategy is like a blazing fire.

Wind only makes it stronger.

Retail traders are used to trading the direction of price.

This is called directional risk and, it's, one, of the, greatest, challenges in the financial market. It's the good old buy low and sell high paradigm.

Antifragile strategies step away from their problem and instead of trading market direction, they trade market volatility, which is a much easier problem to deal with. It just requires some mathematical knowledge that allows derivatives traders to profit regardless of market direction. Imagine opening a trade and being able to make a profit regardless of where the market goes next.

That is possible due to the mathematics of derivatives.

By the way, this is the type of trading that large banks engage in. They are not worried about speculation because they have a much better way of making money which is credit and interest.

Their goal in the financial markets is to mitigate some of the credit risk of their large operations.

In other words, large banks could not care less about your stop-loss orders.

They are interested in hedging the risk.

Let me quickly demonstrate how it's possible to make money regardless of market direction. This is only possible due to a very famous formula in the world of finance which is a black trolls formula.

The 1997 Nobel Prize in economics was given to the men who came up with this formula Scholes and Robert Martin.

Fisher Black passed away before the Nobel.

I have a video here in the channel explaining the formula more carefully.

I'll leave it in the cards.

To quickly demonstrate how it's possible to make money regardless of market direction using derivatives, I'll insert a video I made in the past called this is how banks actually trade.

In today's video, I want to show you how banks really trade in the financial markets.

I see a lot of people on YouTube talking about institutional trading, smart money concepts, and things like that as if they knew how institutions actually work. And the very next thing they do is to pull up a price chart.

What they fail to realize is that institutional traders, like bank traders,, for example,, don't, use, price charts at all. The reason why bank traders don't use price charts is because they don't care about what direction price will go next.

They care about volatility. Just imagine being able to generate profits regardless of what direction the price will go.

This is an idea that retail traders can only dream about.

In fact, those great trading systems that you see on trading forums are an attempt of doing precisely that.

They don't work, of course because you don't do that with price charts.

You need the elegant mathematics of derivatives in order to profit regardless of price direction.

And that's what I'm going to show you in this video.

Before we move on, consider clicking the like button and subscribing to the channel because this helps support the ongoing creation of free videos like this one.

Without further ado, let's begin with a simple demonstration of what happens on a bank trading desk.

Instead of price charts bank traders use something like this.

This is called an outcome matrix.

Bank traders have automatic systems for this but we as retail traders can play around with it with an Excel spreadsheet like this one.

If you're interested, please buy this spreadsheet from the original source at macro option.com.

It's an extremely well-made spreadsheet, and trust me, you don't want to spend the time to build this yourself, as there is a lot of mathematics behind the curtains here.

As you can see, there are a lot of parameters in here. I'm not going to cover all of this in this video, of course.

If you want to learn this, you can check my ebook, Volatility Trading in the video description. I just want to show you how it's possible to profit regardless of price direction with the derivatives market, more specifically the stock options market.

Bank traders do this with volatility trading.

And one of the prerequisites for a volatility trading strategy is something called delta hedge.

A lot of people believe that delta hedge is a strategy, but that's not true. Delta hedge is a prerequisite for a volatility trading strategy.

A delta hedge can be done in different ways, but today I want to show you a way of doing that using a combination of call options and stocks.

A hedge implies that a trade has two simultaneous trades.

One is long and the other is short. This must be done in such a way that the delta risk is hedged, hence the name delta hedge.

The delta risk is the directional risk of the market.

So when we hedge the delta we can make money regardless of price direction.

Just as a side note, delta is one of the partial derivatives of the black shores model, the famous option pricing model that won the Nobel Prize in 1997.

As you can see in the outcome matrix there are other partial derivatives of the model you need to worry about.

These partial derivatives are also known as the option Greeks, but that's a subject for another video. I will begin simulating a delta hedge by going long on 30 stock option contracts.

As you can see, this is an at the money call option.

The strike is 100 and the underlying price is also 100.

This option contract is 36 days away from expiration.

The current implied volatility is 25%. This generates a delta equal to 1540.

Since this is a delta hedge, we need to do something in order to neutralize it and avoid the directional risk of the market.

By the way, a positive delta means that we are long, which makes sense since we bought call options.

One of the alternatives to neutralize the delta and create a delta hedge is to short sell the underlying stock.

So that's exactly what we're going to do here.

We need to know the exact number of shares to short sell in order to neutralize the portfolio delta.

So we can go in the data tab in Excel.

Then we go to the what if analysis option.

Then we choose the goalsek option.

A small window with three parameters will open.

The small window will allow you to know how many shares of the underlying stock you'll need to sell in order to neutralize the portfolio delta.

So we're going to put the portfolio delta cell in the first row because that's the cell we want to neutralize.

In the second row, we'll put the number zero because we want the portfolio delta cell to become zero. And in the third row we're going to choose which cell we want to change in order to achieve that.

In this case, we want to neutralize the delta by changing the number of stock shares to short sell. By clicking okay Excel will start calculating how many stock shares you need to short sell in order to neutralize the portfolio delta.

Notice here that now the delta is equal to zero.

And we needed to short sell 1540 shares of the underlying stock in order to neutralize the positive delta generated when we bought 30 call option contracts.

Keep in mind that a change in any of these other variables will alter this equilibrium.

Now we have created a delta hedge.

This is where it starts to become interesting.

Keep in mind that the delta hedge was created when the stock price is at $100.

This is the anchoring point, so to speak.

We want to analyze now what happens with the P&L of our position as price moves away from the $100 anchoring point.

Notice that our P&L is zero because the market hasn't moved up or down away from the $100 anchoring point yet.

Let's now imagine that some time passes by and the market rises from 100 to 105.

That produces a profit equal to $1,793 in our position.

The long side of our hedge is winning $9,495 and the short side of our hedge is losing $7,71.

In other words, a profit is being generated because the winning side is winning more than what the losing side is losing.

You might think that this is only happening because price is rising but that's not the case. A profit will also occur if price goes down from 100.

Let's go back to the anchoring position first to neutralize the P&L.

Watch carefully what happens with the P&L when the price goes down from $100 to let's say $95.

We begin to generate a profit of $1,877.

The long side of our hedge is losing $5,825 and the short side of our hedge is winning $7,71.

In other words, the winning side is winning more than what the losing side is losing.

This is how bank traders profit regardless of price direction.

We can see that geometrically by looking at the graph below. On the x-axis, we have the stock price and on the y-axis we have the P&L. We created the delta hedge at $100.

If price goes up, the P&L increases and if price goes down, the P&L also increases.

For the option traders, this is different than a straddle because we are looking at the position continuously.

You might be wondering what's the catch here.

There must be a way of losing money with this and there is.

In fact there are a few ways of losing money with this.

Remember that I said that bank traders trade volatility instead of price direction.

If volatility goes down with all else maintained equal, the P&L will generate a loss. For example, let's say that the implied volatility goes from 25% to 20%.

The P&L generates a loss of $1,880.

On the other hand, if volatility rises from 25 to 30%, for example, a profit of $1,879 emerges.

In other words, we are not exposed to the market direction, but we are exposed to market volatility. There are other ways of losing money here, but I will leave that for another time. The point I want to make here is that if you want to make money with this, you need to know when volatility is low and when it's high.

And that's a lot easier than knowing what direction price will go next.

That's why bank traders use this instead of using price charts.

Even though this seems more complicated than a price chart, in reality, it's easier.

However, this doesn't mean you cannot make money with speculation, which can only be robust at best. It means you need to make sure you use sound risk management principles like the ones you are learning here. Otherwise, you are bound to fail. Chaos always finds a way of getting you in your most vulnerable moment.

If you want to learn more about interfragile strategies, I have a series of ebooks showing different strategies.

These three strategies are in the realm of hedging as it was just demonstrated.

I also offer an additional strategy but in the realm of arbitrage which is statistical arbitrage by co-integration.

This type of strategy is widely used by funds for example and it is based on another famous Nobel Prize in economics awarded to Clive Granger in 2003.

Speculation bets on one thing going right.

Statistical arbitrage bets on many small things behaving normally and interfragile strategies bet on things going wrong.

Hopefully this video gives you a better understanding of risk management.

If you want to learn more about advanced trading ideas, I offer several courses in ebooks.

You can check them out in my website fractalflowpro.com or you can send me an email at support@froflowpro.

com.

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Thank you very much for watching, and I hope to see you in the next videos. Take care.