VrotteOtter

A brief introduction to RISK MANAGEMENT:

Education
BINANCE:ETHBTC   Ethereum / Bitcoin
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As I tend to get a lot of questions about this topic, most traders don’t seem to understand basic risk management in trading! From my experience capital protection and risk management are probably the most important part of any trader's skillset. So that is why I wanted to address this in a more elaborate educational Idea.

The kind of questions I get:

- I’ve got half my portfolio in this coin and the other in this do you think I need to sell.
- Do you think I need to sell my … and buy …
- I've been holding this since it was at that price do you think it will go down more ...


I know these don't necessarily seem like bad questions to most people, but that is not actually how you should be trading.

Note: In crypto trading lots of people (myself included) keep their portfolio in BTC or ETH. Now in doing this, you should not look at the dollar amount of the asset, but the goal should be to increase the amount of the asset you hold. If you are going to switch every five minutes because you think about the dollar amount of said asset, I would advise you to stay in dollar and trade from there.

Now with that little particularity out of the way, we can look at how trading should be done.

It is known most retail traders take positions with their entire capital and then when it drops they get scared and don’t want to sell because psychologically they can’t handle the risk. Now, this is the best way to blow up your entire portfolio in the shortest amount of time.

In trading, you can never be sure a trade will be a winner so you should always make sure you can handle a string of losers without it affecting the bottom line too much.

Example of how human psychology works in regards to this is a study done around the Kelly Criterion formula: ( This example is from the Wikipedia page of the Kelly Criterion )

Each participant in this study was given $25 and asked to bet on a coin that would land heads 60% of the time. Participants had 30 minutes to play, so could place about 300 bets, and the prizes were capped at $250. The behavior of the test subjects was far from optimal:

Remarkably, 28% of the participants went bust, and the average payout was just $91. Only 21% of the participants reached the maximum. 18 of the 61 participants bet everything on one toss, while two-thirds gambled on tails at some stage in the experiment.

Using the Kelly criterion and based on the odds in the experiment (ignoring the cap of $250 and the finite duration of the test), the right approach would be to bet 20% of one's bankroll on each toss of the coin. If losing, the size of the next bet gets cut; if winning, the stake increases. If the bettors had followed this rule (assuming that bets have infinite granularity and there are up to 300 coin tosses per game and that a player who reaches the cap would stop betting after that), an average of 94% of them would have reached the cap, and the average payout would be $237.36.


In this particular game, because of the cap, a strategy of betting only 12% of the pot on each toss would have even better results (a 95% probability of reaching the cap and an average payout of $242.03).
Now, this is why we do not want to trade like this. We should choose a risk level we are comfortable with per trade and keep this consistent. You can use the Kelly Criterion which can be difficult to do because it requires the win probability per trade for the calculation. Now you could get this by trading a certain trade setup you like to trade, let’s keep it simple, a 100 times.
By doing this, you could gage the probability of this setup being a winner and that would allow you to use the Kelly Criterion formula.

For beginners, a simpler way of doing this is the 1 percent rule. This means you risk 1% of your portfolio per trade. Simple example:

You have a risk-reward per trade of 1/1.5 and your strategy has a win rate of 50% of the time and you make 100 trades on a 10000 dollar portfolio. You would end up with a 25% gain after 100 trades even though the 50 losing trades lost you a total of 5000 dollars. Because of the risk-reward the winners got you 7500 dollars which brings you to 12500 dollars in the end.

This is a simple example but it shows the importance of both risk/reward and position size.
Of course in reality it would play out slightly different. You would recalculate after every trade if your portfolio decreases due to a loss, which means you reduce your positions to make sure your risk stays at 1% of your portfolio and if you win you increase your positions to do the same.

Another thing people get wrong with this rule is they start just betting the same position on each trade of let's say 5% and think they will get out when they lose 1%. This does not work!!!

You should look at your setup and where you want to place your stop and look at the percentage between your stop and your entry. If this is for example 20%, you take your 1% risk tolerance and divide it by 20, then multiply it by 100 and that will be your position size. If you are using leverage you will need to divide this position size by the amount of leverage used.

An example of risk-reward is shown above.

From my experience, some general rules I use which tend to improve your results on top of a risk management system as described above:

1. Cut your losers quickly and keep your winners.
2. Don't change your stop unless you take profit and move it above break even.
3. Always place your stop at a technical level and not a random percentage, for example, the last highest low.


Of course, you can adapt this to fit your trading strategy and style but the basics will be the same.

I hope this was helpful and if anything is unclear feel free to ask me a question through chat.
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