Made to Measure: The complete performance review
Introduction
When reviewing your trading performance, most people only consider their P&L.
The belief is that the snapshot of how much you are winning or losing is the most essential information you should be dissecting.
In reality, looking at just your P&L is zooming into one aspect of your trading, and greying out the rest. You need the full picture to accurately understand your trading behaviour.
In this blog we will touch on
1. The key metrics we believe are the best way to analyse your trading,
2. The reasons why metrics are important, and
3. The key actions that all traders should focus on to improve their metrics, and hence their performance.
Key Metrics
Metrics help to give you a deeper understanding of your trading.
There are three simple metrics you need to be looking at in order to get a holistic and complete understanding of your trading.
1. Expectancy: This is a risk adjusted measurement of your returns.
2. Win Rate: This is your percentage of trades that are profitable.
3. Risk Reward: This tells you how large your winning trades are compared to your losing trades.
These metrics are interrelated. An expectancy of 0% means that you overall have a trading strategy that is break-even. You could achieve this with a win rate of 50% and a risk reward of 1. That is, if half your trades are winners, and the average P&L of your winners is the same as the average P&L of losing trades.
An expectancy of 0% could also be achieved with a win rate of 33% and a risk reward of 2:1, as well as many other combinations.
The lower your win rate, the higher the risk reward required to be successful, and any win rate below 50% will mean that your winning trades will need to be larger than your losing trades to achieve profitability.
Why metrics are important
There are three reasons that expanding your analysis to include these key performance indicators is essential practice.
The luck factor
The anchoring effect
Comparing like with like
1. The luck factor
You can do everything wrong and have a winning trade. You can also do everything right and have a losing trade. Sometimes, your profit or loss on a trade is down to sheer good or bad luck. What is important is that you do not change your strategy or behaviour based on these outlier trades. Doing that can cause long term negative results.
So don’t give yourself credit and create overconfidence in your abilities if you get a big winner, and don’t beat yourself up and create uncertainty in your decision making if you get a big loser. Luck can be a playing factor in these trades. Check out your metrics on your trading day to see if there’s a pattern of behaviour, and find the areas you can improve on.
2. The anchoring effect
The anchoring effect refers to a behavioural economics term, where we rely too heavily on the first piece of information offered (the “anchor”) when making decisions. Anchoring can occur if you focus on your daily P&L, and subconsciously use that number to influence your next trades. For example, if you look at a daily P&L loss, it changes your risk appetite and you will make different decisions than if you look at a daily P&L profit. Our brains are designed to increase risk when we are losing. It is known as loss aversion, and it makes us take larger risks when we lose.
By mapping your historical trades to key performance metrics like win rate, and risk reward, no single trade really moves the needle, so you are less likely to exhibit biased behaviour due to your recent trade outcomes.
3. Comparing like with like
Suppose two traders each make a profit of $1,000. Who is the better trader?
One of them might have made a huge profit on a lucky outlier trade!
One of them may have an account balance that is 100 times larger than the other.
By converting their performance into metrics - you can compare like for like, and predict which trader is on the path to long term success.
Key Actions
Once you convert to a metrics driven approach, it’s easier to make improvements in your trading, and this is the real strength of using metrics.
For example, if you win 50% of trades and your risk reward is less than 1 for example, you work on increasing either of these metrics.
Look at risk reward over a series of scenarios:
Is your risk reward higher or lower for specific products or strategies
Does it change for different timing – say evening trading
Does it change in winning / losing streaks, when volatility is high or when you trade too fast
Understanding your own personal biases will assist you in finding the pockets of strength and weakness in your trading. Use these to focus clearly on improvements in these areas.
With a deeper knowledge of your strengths and weaknesses you can adapt your money management strategy to support your trading. For example:
If you are stronger in the morning, your trade size in the morning should be larger.
If you have a weakness in a specific product, you can trade much smaller size while to learn to trade this product better.
If speed, size, volatility or streaks impact your performance you can set specific goals to help through these trades.
Conclusion
P&L is important, but focusing on just this will give you skewered results. By focusing on just P&L, you are:
At risk of over or under playing your trading abilities
Susceptible to the anchoring effect
Unable to compare like to like
You need to analyse key trading metrics along with your P&L, so that you can see where your systemic strengths and weaknesses lie. Expectancy, win rate and risk reward are all important. By analysing these metrics, you can:
Get key insights into your trading behaviour and strategy
See where you are going wrong
See where you can improve
Once you start thinking in terms of your metrics, you are more likely to think strategically about your trading, and less likely to over-react to one good or bad trade.