# Test

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Share On Social Media <aside> 📌 Risk amount: CAPITAL SIZE (\$) x RISK PER TRADE (%)

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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*

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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

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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)

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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)

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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)

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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.

## 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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