# Test

## About Course

## Managing your risk

This is the first version of my risk management guide which will be updated and finished in the next few weeks. There is so much I wish to cover but at the same time I want this piece to reach you as soon as possible so you can start implementing the concepts presented in this version. As you might have noticed, there is a Greek mythology character called Caerus on the front page of this PDF. He represents opportunity, luck and favorable moments and this is something we will go through in this book. Trading is not just a random game of pressing buy and sell buttons, at least not in the long run. No matter how good your trading strategy is, your win rate will never be 100%. Losses are a part of the game and your job is to expect them and control them. What you really need is an edge that plays out profitably not over a few trades but over the course of a series of them. The outcome of any trade should either be a big win, small win or a small loss, never a big loss. This is where risk management comes in. You have to study it carefully and apply it to your trading system if you want consistent results and actually become a successful trader in the long run. Trading is a game of probabilities and you have to treat it as such. It is about setting up your game plan and finding ways to gain an edge to put the odds in your favor. Hopefully this article is a good start and it will help you on your journey.

**Risk per trade**

If you want to be a trader (and not a gambler), your number one priority becomes protecting your capital. This is why you have to consider the risk you’re taking when trading. Risk or risk per trade is how much of your capital you’re willing (risking) to lose on a single trade if it goes wrong. Every trader has a different risk appetite so there are different opinions on what is the right amount of risk. Some say below 1%, others say somewhere between 1% and 5%. Let’s say you decide to have a fixed risk of 1% of your account balance on a single trade. This means that if you lose 20 trades in a row, you still have roughly 80% of your capital. Having a fixed risk % also benefits you because of the power of compounding and reverse compounding – on a losing streak, your losses (in $) get smaller and smaller and on a winning streak, your risk and therefore also reward (in dollar value) will get bigger and bigger. Some traders also practice “adjustable risk per trade” which means lowering your risk per trade after each consecutive loss on a losing streak. It is important to understand that risking eg. 1% on a single trade does not mean that your position size is only 1% of your capital. It just means that you will only lose 1% of your account balance in case your stop loss is hit.

<aside> 📌 Risk amount: *CAPITAL SIZE ($) x RISK PER TRADE (%)*

</aside>

*Example: Your capital size is $10,000 and you decide that your risk per trade will be 1%. 1% of $10,000 is $100 ( $10,000 x 0.01). This means that you will only risk $100 per trade.*

**Risk and reward, win rate, expectancy**

**The R:R ratio** is used to evaluate trading decisions based on risk and reward. It represents the ratio between the risk you are taking and the expected return. Or in other words, it compares the potential profit of a specific trade to its potential loss.

RR can be calculated using the “Long position” or “Short position” option in Tradingview or manually with the following formulas:

<aside> 📌 Risk:reward ratio: *(ENTRY PRICE – STOP LOSS PRICE) / (TARGET PRICE – ENTRY PRICE) for longs (STOP LOSS PRICE – ENTRY PRICE) / (ENTRY PRICE – TARGET PRICE) for shorts

or simply

PRICE DISTANCE TO STOP LOSS / PRICE DISTANCE TO TARGET*

</aside>

To put it simply, if you have a R:R ratio of 1:2 (also called 2R), it means you’re risking 1 unit to potentially make 2 units. If you have a R:R of 1:4 (also called 4R), it means you’re risking 1 unit to potentially make 4 units. I’m sure you have seen traders talking about their trades in terms of R, for example a +2R win or -1R loss. It is a fairly simple concept used to look at the trades and their results in terms of R-values and R-multiples. The key idea here is that all of your profits and losses should be related to your initial risk. For example, a +XR multiple is a profit that is X times greater than the initial risk and a -XR multiple is a loss that is X times higher than the initial risk. R-value **–** The initial risk taken in a given position (defined by the initial stop loss) R-multiple **–** Profit or loss expressed as a multiple of the initial risk

*Example. $ETH is trading at $1700 and you want to enter a trade with a target at $1,730 and stop loss at $1,690. The R:R ratio here is 1:3 ($10 / $30). You’re risking $10 (distance to stop loss) to make $30 (distance to target), which means your R-value (initial risk) is $10. Let’s say the trade is successful and you exit at $1,730. Your profit can be expressed as an R-multiple: +3R (3 times the initial risk). Second scenario happens and your stop loss is hit. Your loss can be expresses as an R-multiple: -1R (1 time the initial risk). Now let’s say the price goes down to $1670 and your stop loss isn’t triggered. Your loss as an R-multiple would then be -3R (3 times the initial risk).*

In general, you should be looking for trades where the reward is higher than the risk. If the R:R ratio is worse than 1:1 (eg. 1:0.7), that means that the potential risk is greater than the potential reward. If the R:R ratio is better than 1:1 (eg. 1:2), the potential reward is greater than the potential risk. You want your losses to be -1R or less and your wins to be greater than +1R. Traders usually have a system that often produces similar trade opportunities in terms of R:R which helps them build a consistently profitable system in combination with their win rate.

**Win rate** represents the ratio between your winning and losing trades. Or in other words, it shows how many trades you win out of all your trades. It can be calculated as:

<aside> 📌 Win rate: *NUMBER OF WINNING TRADES / TOTAL NUMBER OF TRADES*

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*Example: You take 25 trades with 14 of them being winners and 11 of them being losers. Your win rate is 14 / 25 = 0.56 = 56%.* It is important to understand that win rate by itself doesn’t mean much. You might have a high WR but if your losses are larger in value than your wins, you are still not profitable. This is why you need to consider both WR and RR. A higher win rate means that your RR can be lower and a lower win rate requires your RR to be higher. Many professional traders have a system with a win rate of 40% which only requires a R:R ratio greater than 1:1.6 to be profitable. The following calculation will tell you what is the required R:R to break even based on your win rate which means you have to get a slightly better RR than the result in order to be profitable.

<aside> 📌 Minimum R:R to break even: *(1-WIN RATE) / WIN RATE*

</aside>

*Example: Your win rate is 60% (0.6). Here is how to calculate your required R:R = (1-0.6) / 0.6 = 0.4 / 0.6 = 0.66667. Your R:R to break even should be around 1:0.66 or better if you want to be profitable.*

This next calculation will tell you about the minimum required win rate to break even, based on your R:R ratio which means you have to get a slightly better win rate than the result to be profitable.

<aside> 📌 Minimum win rate to break even: *1 / (1 + RR)*

</aside>

*Example: Your R:R is 1:2.5. Here is how to calculate your required win rate = 1 / (1 + 2.5) = 1 / 3.5 = 0.286 = 28.6%. Your win rate to break even should be 28.6% or higher if you want to be profitable*

**Expectancy of your system** Calculating the expectancy will tell you whether your trading system is profitable or unprofitable based on the size of wins and losses and the expected return per trade. If the number is positive, your strategy is profitable and if the number is negative, your strategy is not profitable. The result will also tell the average profit/loss per trade.

<aside> 📌 Expectancy: *(WIN RATE x AVERAGE WIN SIZE) – (LOSS RATE x AVERAGE LOSS SIZE)*

</aside>

*Example: Your win rate is 60% and therefore you loss rate is 40%. The average size of your wins is $600 and the average size of your losses is $250. Expectancy = (0.6 x $600) – (0.4 x $250) = 360 – 100 = 260. You strategy is profitable since the result is positive. You are expected to win 6 out of 10 trades, resulting in $3,600 in gains (6 x $600). You are also expected to lose 4 trades out of 10, resulting in losses of $1,000. So, after 10 trades, you’re expected to make $2,600 ($3,600 – $1,000) which is on average +$260 per trade ($2,600 / 10 trades) which is also the result we’ve got from the expectancy formula above.*

**Position size**

Picking a correct position size is probably the most important thing when it comes to managing your risk. This can be done with a very simple position size calculation which will tell you how big of a position you can open in order to only lose the amount you have previously decided on. Keep in mind that leverage does not affect the position size calculation. You can use leverage to reduce the risk on having too much of your capital on exchanges or to increase your positions size if the calculation allows you to. The smaller the distance to stop loss is, the bigger position size you can trade while keeping your risk amount the same. I will help you understand this by using two examples. The data you need: risk amount (risk per trade x capital size) and distance to stop loss (in %)

<aside> 📌 The calculation to get the position size in quote currency (eg. USD): *Position size = RISK AMOUNT / DISTANCE TO STOP LOSS*

The calculation to get the position size in the base currency (eg. BTC): *Position size = RISK AMOUNT / (ENTRY PRICE – STOP LOSS PRICE)*

</aside>

**Example 1:**

Pair: BTC/USD Capital size: $10,000 Risk per trade: 1% Entry price: $20,000 Stop loss price: $19,530

Risk amount: $100(1% of $10k)Distance to stop loss: 2.35%(entry price – stop loss price) / entry price x 100

Calculation to get the position size in base currency (BTC)

Position size = RISK AMOUNT / (ENTRY PRICE – STOP LOSS PRICE) Position size = $100 / ($20,000 – $19,530) = 100 / 470 Position size = 0.2127 BTC

Calculation to get the position size in quote currency (USD) *Position size = RISK AMOUNT / DISTANCE TO STOP LOSS Position size = $100 / 2.35% Position size = $4,255*

**The result tells us that we can open a position in the size of $4,255 (or 0.2127 BTC) to only lose $100 (risk amount) in case our stop loss is hit. Notice how the position size is smaller than your capital size? It is because the distance to stop loss is wider which allows us to only trade with a smaller portion of our capital in order to only lose the risk amount in case of stop loss being hit.

**Example 2:**

Pair: BTC/USD Capital size: $10,000 Risk per trade: 1% Entry price: $20,000 Stop loss price: $19,870

Risk amount: $100(1% of $10k)Distance to stop loss: 0.65%(entry price – stop loss price) / entry price x 100

Calculation to get the position size in base currency (BTC)

Position size = RISK AMOUNT / (ENTRY PRICE – STOP LOSS PRICE) Position size = $100 / ($20,000 – $19,870) = 100 / 130 Position size = 0.7692 BTC

Calculation to get the position size in quote currency (USD) *Position size = RISK AMOUNT / DISTANCE TO STOP LOSS Position size = $100 / 0.65% Position size = $15,384*

The result tells us that we can open a position in the size of $15,384 (or 0.7692 BTC) to only lose $100 (risk amount) in case our stop loss is hit. Notice how the position size is bigger than your capital size? It is because the distance to stop loss is tighter which allows us to enter greater positions in order to only lose the risk amount in case if our stop loss is hit. This means you can now use leverage to increase your position from $10,000 to $15,384.

## Stop loss and take profit

Your decision to enter a trade is based on some set of rules which if fulfilled, give you an idea of where the price could move to (target/take profit) and where the expected scenario is invalidated (stop loss). But as we have learned, our analysis can’t always predict the actual outcome. **Stop loss** We use stop loss orders to terminate our positions to limit the downside. It prevents us from blowing our account or losing too much capital if the trade goes against us. As we know, each trade and each trading day (volatility!) is unique, so having a fixed distance to stop loss doesn’t make much sense because it takes away the needed flexibility of your trading system. There is no universal rule on where to place your stop loss since it’s unique to every trade and trading strategy. My only suggestion is to avoid placing your stop loss at your entry price as soon as a trade is in the green and placing it just above/below obvious levels such as moving averages, swing points, support/resistance levels, equal highs/lows, round numbers, etc because it is very likely they will get triggered with a quick price move, even if the market ends up going in your expected direction. **Take profit** There is also no magic rule about where to take profits since it is all based on your analysis and strategy. Having a fixed percentage target doesn’t make much sense either because of the reasons stated above. Instead, your targets should be relative to your risk. Traders usually target S/R zones, Fibonacci levels, S/D zones, imbalances, break of structure levels, previous swing points, VAHs, VALs, POCs, etc. Something that could improve setting up your SL/TP orders is using Average True Range or trailing stops.

## Elements of risk

Risk is a bit more abstract than just some risk management techniques. It requires knowledge and experience to adjust your risk based on different factors. While there are many more, I will try to introduce you to some of them.

**Correlation** – Here is quote from Bruce Kovner (from the book called Market Wizards): “Through bitter experience, I have learned that a mistake in position correlation is the root of some of the most serious problems in trading. If you have eight highly correlated positions, then you are really trading one position that is eight times as large.” Correlation shows us to which degree two financial instruments move together. It is a figure between -1 and +1 or -100% and +100% with -1 being a perfect negative correlation (if A rises 1%, B falls 1%), +1 being a perfect correlation (if A rises 1%, B also rises 1%) and 0 being no correlation at all. I’m sure you now understand that correlation can highly influence your risk without you even knowing. If you long or short two (or more) assets that are positively correlated, your risk is increased. If you long or short two (or more) assets that are negatively correlated, your risk is decreased because if one of them falls, the other one rises and that serves as some kind of hedge. **Volatility** – Volatility represents how large an asset’s prices swing around the mean price. I’m sure you have noticed that some assets are more volatile than others (eg. stocks compared to bonds or altcoins compared to Bitcoin or Apple stock compared to penny stocks), so we can logically assume that the risk of being exposed to assets with higher volatility is greater than the risk of being exposed to assets with lower volatility. Time is also an important factor that influences volatility in the markets (trading sessions, daily close/open, weekly close/open, monthly close/open, etc) along with news (geopolitical events, economic data releases, politics, etc). This is all why you should adjust your risk based on expected volatility. **Exposure risk** – This one is a bit more abstract since it requires experience and intuition but the general idea is pretty simple. Risk of being long / short / flat is not always equal. For example: Shorting in an up trend is far more risky than longing and longing in a down trend is riskier than shorting. The risk of longing/shorting a range break out/break down is higher than entering longs at range lows and entering short at range highs. Staying flat at S/R levels in the times of important news is less risky than trying to trade it. We could also say that staying flat during QE is riskier than being exposed to the market and vice versa in QT. There are countless examples I could list but I hope you get the point.

Thank you for reading this PDF. I hope you found it useful and learned something new. If that wasn’t the case, don’t worry! I will add more topics in the coming weeks. Stay tuned and join my community on Twitter, Telegram and Discord.

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