Most of the newcomers to the cryptocurrency space have a “get rich quick” mentality which contradicts basic trading strategies. It’s understandable given the “homeruns” of 50x or more that happen constantly, but it’s not for everyone and can be a recipe for disaster in the long run.
Traders seem to ignore the fact that crypto markets are very volatile in both ways – for every coin which goes on the mythical moon mission, there is a coin which retraced 95% from the last high. So what is a disciplined trader to do?
Risk management helps you to have a fixed risk on the downside of your trade so that you are not that influenced by harsh drawdowns, but also have unlimited upside. You can set your targets as high as you wish – as long as you are in profit.
Do you really need it?
Imagine this scenario: you have a solid trading strategy which produces profits 70% of the time but you are still hardly in profit. How can it happen and why is it such a common situation?
This table shows how much gain you need to make to get to the break even level after a loss. The main takeaway is: the bigger the loss you take, the harder it is to make up for it, exponentially.
If you find yourself in the situation explained above it means that you have a tendency to take small gains on the winners and let losers run. It happens because of a natural mental bias that we all have. People generally don’t like to accept that they are wrong and as a result let losers run until they are eventually right (or at least at breakeven). This approach to the market is toxic because some of the losers will never recover and ones which recover tend to lock your funds in a losing trade for a long time.
Let’s imagine another common scenario: you are killing it at the moment and you’ve quadrupled your capital with a few quick trades. Thinking too highly of yourself, you enter the next trade with an unusually large position and the trade goes south. Your ego doesn’t allow you to exit that loser and by the time you exit, you’ve lost half of your stack. You still have more than you started with, but you begin to wonder if you should sell right now – the worst part of all of this is that there is no right answer to that question.
Both scenarios have two things in common – psychological mistakes and lack of the downside protection of the deployed capital.
The main rule of risk management
To survive in the markets as a trader, each trade needs to have a fixed % risk of your total portfolio. This % may vary depending on the size of your capital – it makes sense to risk more if you have less funds, then decrease risk as you approach your wealth target.
The golden rule is risking about 1-2% per trade.
Risking 5% or more is suicide because even good traders have bad days – if you have 10 open positions at the same time, one bad day in the market might wipe out 50% of your total capital. Otherwise, if you had a fixed risk at 1% or 2% you would lose 10% and 20% respectively. Obviously it still sucks, but you at least survive to trade another day.
How to calculate risk of the trade
Risk is defined as the loss you will take if price reaches stop-loss price, relative to your total budget. We want to have it fixed, so let’s use as an example the risk of 2%.
To enter a trade with a fixed risk we need to calculate a position size. It’s based on the four variables: entry price, stop-loss price, risk % and total capital. Yeah, in order to implement risk management as a part of your trading strategy you need to utilize a little bit of math.
Let’s imagine that we have an account with 1 BTC and we are looking to enter this MTLBTC trade. Our entry price was around 52380 satoshi and we set our stop-loss below the last local low – at 45860 satoshi. Also we decided that we want to take a 2% risk.
2% of the 1 BTC is 0.02 BTC – maximum potential loss in the case of triggering our predefined stop-loss.
Our stoploss is 12.4% below the entry price, it means that this potential loss of 12.4% should be equivalent to 0.02 BTC.
Now, let’s calculate our position size. If 0.02 BTC is 12.4% of allowed position size, then 0.02 / 0.124 = 0.161 BTC is the final amount we are willing to spend.
To convert it in MTL we need to divide this amount by the price of MTL, in this case
0.161 / 0.0005238 = 307.4 MTL
The exact formula looks like this:
Position size (in BTC) = (total budget * fixed risk) / (1 – (stop-loss price / entry price))
To calculate position size in altcoin terms you need to divide your BTC position size by the price of the coin
Position size (in # of coins) = Position size (in BTC) / entry price
What if we were to move our stops down a bit? For example, to the 40100 sats, below the previous low.
Position size (in BTC) = (1 BTC * 0.02) / (1 – (0.0004010 / 0.0005238)) = 0.085 BTC
Position size (in MTL) = 0.085 BTC / 0.0005238 = 162.9 MTL
Let’s check if our results are correct – imagine that the price went down and triggered our stops. We would lose 23.4% of our position size since our stop is 23.4% lower than the entry point.
Total balance after loss (in BTC) = total budget – position size + result of the trade = 1 BTC – 0.085 BTC + 0.085 * (1 – 0.234) BTC = 1 BTC – 0.085 BTC + 0.0065 BTC = 0.98 BTC
As you can see we’ve stayed within our predefined risk %.
Myth: stop-losses are unprofitable in the volatile markets
The whole point of risk management is survival in any market conditions, including high volatility. Having a stop-loss (at least a mental one) is a must if you are trying to build a systematic approach to the market.
Learning how to properly place stop-losses requires a lot of effort – you need to know basic TA tools and have discipline to accept the loss at the chosen price.
It makes sense to place much wider stop-losses in volatile markets.
Obviously, the wider stop-loss you use the smaller position you can afford to buy. It means that volatility of the market doesn’t really matter – if we are trading something stable we enter in a size, if the market is volatile – we take a small position. The end result of both trades will be the same – either price touches stop-loss and we lose the same amount of money, or it hits the target and profits are comparable.
Where there is risk there is reward
Every risk you take comes with a reward. Reward is defined as the difference between target price and entry price multiplied by the position size.
Reward (in % relative to trade) = (target price / entry price) – 1
Reward (in % relative to budget) = Reward in % relative to trade * position size
The rule of thumb for reward is to enter a trade if and only if reward is greater than risk.
Reward is usually calculated relative to the risk. If your target price is 30% higher than entry price and stop-loss is 15% below the entry price, then your Risk/Reward ratio is 15:30 or 1:2. To make profit from a trades with this R/R ratio it’s enough to have a win rate higher than 33%.
It might seem strange – how does one profit from strategy with such a low win rate? But you gotta trust the numbers – the math checks out. The moral of the story is to look for trades with very asymmetric R/R ratio – even if the majority of the trades go the wrong way you will still be in profit with a good R/R.
Let’s come back to our MTL example and calculate Risk/Reward ratio to make a decision – should we enter this trade?
As we calculated above our stop-loss is 23.4% below the entry price. Our take profit price is 166530 sats (retest of the multi-month high).
Reward (%) = (take profit price / entry price) – 1 = 0,00166530 / 0,00052380 – 1 = 2,179 = 217,9%
So our final R/R is 23.4:217.9 or 1:9.3 if we divide both sides by 23.4 (don’t freak out, dividing both sides of the equation is a basic algebra property). It’s a very asymmetrical R/R ratio and according to the table we need to have a ~10% win rate with such a setup to be profitable.
Do you think that there is at least a 10% chance that this MTL trade will work out? I for sure do. It’s a great trade from the Risk/Reward perspective.
Risk management is a very powerful tool in the hands of disciplined trader. It is based on statistics so this methodology removes subjectivity from your trading strategy. But everything has its cost – following rules of the system is hard, both mentally and physically.
As for me, I might have up to 20 opened trades at any given moment. Tracking a lot of positions is very time consuming. Luckily I have background in CS – I’ve managed to write a Python script which tracks my current positions relative to my predefined stop-loss and take-profit prices. Otherwise I would probably use some kind of a spreadsheet.
The mental game is even more complicated – you first need to accept that you will lose some money learning how to place stop-losses, and then you will need to learn how to follow your plan in any market conditions.
If following risk management is so hard, why do I continue to do it? I simply want to survive long enough to see the market really thrive. And I think you should want it too. This market is very new and will offer a lot for those who stick around long enough!