*Looking at risk management calculations to show it’s effects on returns and drawdown*
Welcome back to the blog! In this blog post I am going to talk to you about what is probably the most important part of trading… risk management. Without risk management you can turn a winning strategy in to a losing strategy without doing anything wrong except risking too much or too little at the wrong time.
The first rule to successfully making money through trading is to not lose money through trading. Any serious trader or hedge fund will focus on risk management before anything else because it is more important. You will notice in every trade breakdown or market analysis blog post I write, I will always show you were I plan to exit a trade if it goes wrong and when I manage my exposure as the trade progresses.
If you haven’t read my previous blog posts on risk management then you can find them by clicking on the links below.
How much risk is too much?
The value of risk and how much you should risk is a very personal question. Every one is different, trading strategies are all different and that is why it is impossible for me to simply tell you how much you should risk on a trade position.
This is also why it is very important for you to fully understand any trading strategy that you intend to use on the live financial markets. You should know everything about trade frequency, average reward:risk ratios, maximum drawdown, maximum losing streak, win rate percentage and more. All of this comes from backtesting strategies or live testing and recording everything in a trade journal. The more data you collect, the more accurate your risk management can be.
In this blog post I will show you how you can find out the optimal level of risk for your own trading strategies using a proven calculation. You can then use this to size positions correctly according to your intended risk per trade position.
The Kelly Criterion is a formula that was adapted for use in casinos. If you know the odds of winning and the expected pay-off, it tells you how much you should bet in each round.
This is harder than it sounds. Let’s say you could bet on a weighted coin flip, where it lands on heads 60% of the time and tails 40% of the time. The pay-out is £2 per £1 bet (2R). The odds are in your favour. But if you have £100 of capital to bet with, it is less obvious how much you should bet to avoid ruin whilst profiting from the odds.
Let’s assume you bet £50 per coin flip, the odds that it could land on tails twice in a row are 16%. You could easily loss all of your capital after the first two flips of the coin. Equally, betting £1 is not going to maximise your advantage. The odds are 60/40 in your favour so only betting £1 is too conservative. The Kelly Criterion is a formula that produces the long- run optimal bet size, given the odds.
Applying the formula to trading looks like this:
Position size % = Winning trade % – ( (1- Winning trade %) / Risk-reward ratio
If you have recorded a large data set of trades in your journal then you can calculate what the calculation is for you specifically. If you don’t have hundreds of trades or back testing data for your strategies then let’s assume some realistic data with Winning trade % being 30% and reward:risk ratio being 3R. The 3R implies your TP is 3x the size of your stop loss from entry e.g. 300 pips take profit and 100 pips stop loss.
So that is 0.3-(1-0.3)/3 = 6.6%.
6.6% of your total trading capital is a LOT to risk per trade. This is the main observation people have on the Kelly Criterion. Whilst it may optimise the long-run results it doesn’t consider the size of maximal drawdowns and a trader’s ability to withstand drawdowns both financially and psychologically. It is better thought of as the rational maximum limit. With a 30% win rate percentage, the odds of you losing on four trades in a row is nearly one in four. That would result in a drawdown of more than 26% of your trading capital and in reality, most traders would not be willing to ride through this much drawdown and continue.
In order to use Kelly Criterion whilst keeping things more realistic, traders tend to reduce the bet size. For example, let’s say you know you would feel emotionally affected by losing 25% of your account, you should then divide the Kelly Criterion output by four. You have effectively hidden 75% of your account balance from the calculation and it is now optimised to avoid a total loss of your trading capital to just the 25% it can see.
This gives you a maximum risk per trade of 1.65% of total trading capital (6.6% / 4 = 1.65%). Different traders have different risk tolerances and different capital growth goals but this is why you will often see traders risking between 1% and 3% per trade. The Kelly Criterion agrees with this.
The need for backtesting/live trading data.
Every trading strategy is different. Trade frequency, win rate %, average reward:risk ratios and losing streaks will all have an effect on your long term profitability and maximum drawdown. Knowing this data is important for you to have confidence in your trading strategies and being able to stick to them in times of tough markets and losing trades.
Win rate % vs average reward:risk ratio.
|Average R:R||Win rate % required to breakeven|
This data is also needed for using the Kelly Criterion calculation shown previously and also for the next step of risk management which is position sizing.
So you have used the Kelly criterion calculation to find out how much you should be risking per trade position. Let’s assume you have the same win rate % and average reward:risk ratio as the example used previously which was 30% and 3:1R. You are also using the 25% ratio of total risk to get a maximum position size of 1.65% of your trading capital.
You now need to know how to size your positions in order to maintain this level of risk.
Sizing your positions correctly is imperative to being in control of your risk and managing exposure to multiple assets. Position sizing is what ensures that a losing streak of trades does not take you out of trading altogether and allows you to play the long game and benefit from a profitable strategy.
To calculate the correct position size of a trade position you need to know your total trading capital, your intended risk as a % of trading capital and the size of your stop loss/where you intend to exit the trade if it goes against you.
Let’s assume you have £100,000 of trading capital at your disposal and your risk model allows you to risk 1% of total trading capital per trade position. The monetary risk of the trade position is to be £1,650 (£100,000 x 1.65%).
Stop loss placement is how you define risk when trading using leverage. It is where you will get out of a trade position if you are wrong and it defines your maximum loss. You therefore also need to know the size of your stop loss in pips to calculate your position size.
Once you know the monetary value of your total risk and the size of the stop loss of the position you plan to enter then you can calculate the position size. Let’s use a EURUSD long trade with a 1.65% risk on a £100,000 trading account with a stop loss of 80 pips. The calculations are as follows:
For FX currencies.
Firstly, you must convert your base account currency into the base currency of the pair you are trading. For example, £1,650 GBP is currently around $2,163 USD.
Total risk value / number of pips in stop loss = value per pip. $2,163/80 = $27.04 per pip risk
The standard FX lot traded is worth 100,000 contracts. It is always worth double checking that your broker offers this and not a different contract size.
1 pip is worth $10 USD for the EURUSD currency pair. So therefore $27.04/$10 = 2.704 lots is your position size for this risk.
The image below shows this.
For Indices and Commodities.
This is slightly easier than FX currencies. Most brokers tell you how many contracts are traded per lot on each Index or Commodity. It is usually 1 for retail brokers which means each point in value is worth $1 per lot traded.
If you know your total risk and size of stop loss in points then you simply divide the total risk value y the number of points of your stop loss. You then divide this by the number of contracts per lot traded to get the required position size.
$2,163/80 = $27.04/1 = 27.04 lots is your position size.
Once again, you should always convert your account base currency to the relevant currency before completing these calculations. For example, US stock indices and commodities like crude oil are priced in US dollar but the FTSE 100 index is priced in GBP.
The good news is that there are plenty of free position sizing calculators available online. I use the position size calculator on the MyFXbook website to quickly calculate my position sizing. You can get to it via the link below.
Limitations of these calculations.
It is very important to factor in carry charges and costs of trading in to your risk calculations. This is made easier if you know the average duration (length of time you hold trade positions) because it means you can multiple this time value by the potential positive or negative carry charges of a trade position and factor that in to your risk.
For example, lets say I know I hold my crude oil trade intraday trade positions for an average of 12 days and crude oil long positions cost £3.50 per day in carry charges. I know that the next intraday long trade I am planning on entering will likely cost me around £42 (12 x £3.50) in fees. If I was to ignore this, place the trade and it eventually stopped me out 12 days later, my total risk would need to include the potential £42 spent on trading costs.
On the flip side, some FX pairs and other products pay positive carry depending on the direction of the trade and interest rate differential at the time. Therefore you can easily benefit from positive carry. Alternatively you can treat costs of trading as purely costs of trading and factor that in to your analysis to only look for positive or low fee carry trades.
You should also remember that backtesting isn’t the same as trading the live markets. Not only is there a lack the psychological effects of trading live capital when backtesting but you are limited by the market data you can trade. This is where tail risks come in to play.
Tail risk is the likely hood of an event occurring that is outside of the normal distribution of data. The chart below shows this.
Your trading data that you are using to calculate your risk is limited by the amount of market data you have access to and there is always a chance of a very rare event occurring in the markets that pushes the boundaries. This can quite easily mean you become over exposed to the markets very quickly.
And finally, unless you trading strategy is 100% mechanical and operated by an algorithm, there is always going to be the added risk of human error. As much as you might like to think that your psychology is 100% and you follow the rules of your strategy perfectly every day, this is not realistic and there is always a chance that you might not enter a potentially winning trade or enter a not so good trade that becomes a losing one.
These will inevitably effect your win rate % and profitability. This is why risk management is so important and not being over exposed or trading too high risk because there is always a chance that you might lose more trades than your trade history data suggests. If your trade positions are sized correctly you can whether these “anomalies” and still remain profitable.
If you are interested in learning my personal trading strategies, please consider my Mastering The Markets – Retail Trading Course. Head over to my Trading Education page to check out all of my education packages and the deals available.
All my technical analysis is done using the TradingView platform. You can get access via the link below.
My preferred broker of choice is IC Markets. Low spreads and trading costs really help long term profitability. A link to their site is below.
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DISCLAIMER: None of the information posted on this site is to be considered investment/financial advice. Trading is high risk and you should only trade with money you can afford to lose.