I'd like to introduce you to an advanced way of measuring performance. It's nothing new in the world of trading, and has become a standard in the industry for many years now. I think the first time it became popular was when Richard Dennis and his turtle traders started to talk about it back in the 80’s; later on Van Tharp made it even more popular.
The idea is to measure performance in relation to the expected risk of a trade instead of simply looking at the results in Dollars or Points/Ticks/Pips, etc. This allows you to normalize the performance of different markets and trading methods to get a better idea of the actual performance.
This has been such a helpful concept for me that I'm very happy to share it with you. If used in the right way, this can bring your trading to a new level.
The most common way to look at the results of a trade in a specific market is by simply showing its results in USD (or the currency it trades in) for a fixed number of contracts or a fixed number of shares.
But this makes it almost impossible to compare the performance of different markets or trading styles. Let's have a quick look at an example.
Now, was the DAX trade actually "better" than the trade in the E-Mini Dow just because the profit in USD was higher? Was the E-Mini S&P 500 two times better than the DAX trade?
We have two problems here. The first is the contract value. It simply doesn't make much sense to compare a trade in the E-Mini Dow with a trade in the DAX in that way. The reason is that the DAX is a much bigger contract, more than 3 times the size of the E-Mini Dow! So it doesn't make too much sense to compare the USD results of the two markets side by side using the same number of contracts. The same is true for ETFs and Stocks, if you use 1000 shares, whether the equity you're looking at is trading at $50 or $500, you're in trouble!
The second problem is volatility. Right now the DAX moves about 250 points per day, while the S&P 500 moves about 25 points a day. In other words, a 10-point profit in the S&P is a much bigger move than a 10-point move in the DAX. So a 10-point S&P move is about equal to a 100 point move in the DAX. Of course, volatility changes, and at the same time the price of the markets change. A 100 point move is a huge move in a market that trades at 5000, and much less significant in a market that trades at 25000.
Another issue with measuring in absolute terms is that market volatility often changes dramatically. During the financial crisis in 2008, the S&P moved about 5 times as much per day as it does right now. That's why looking at USD performance you'll often see big moves (in either direction) in an equity curve during that time, but in reality you'd probably not have traded the same number of contracts as before!
Now another aspect, of course, is what kind of trading style you've used to achieve those 10-points. Was it a position trade entered due to a signal on a weekly chart, or was it a daytrade you entered on basis of a 5 minute chart? There are worlds between those two, and the question is how to get the results of both worlds together.
The question is how to normalize the performance considering the huge differences in contract sizes, market volatility, and trading styles. One option would be to simply measure the results in % moves instead of Dollars. But again, this wouldn't consider changes in volatility, which is a problem because that's how we set our risk per trade in the real world. It also wouldn't consider different trading styles.
What actually makes sense is to measure the performance related to our expected risk.
Let's look at an example:
Here we've spotted a trade setup (in this case, a Traders Trick Entry in front of a Ross Hook) on the daily chart of the Euro Futures. We know our entry-point at 1.1224, and where we want to get out of the trade, our expected risk, placing a stop-loss at 1.1144. This gives us an expected Initial Risk (1R) of 0.0080 or 80 ticks, which are worth $1000.
The idea is to simply measure the result of the trade against that expected Risk (1R) of 80 ticks. If we get stopped out at 1.1144, we lost 1 time the Initial Risk: -1R. If we can move our stop higher and get stopped out with a loss of 40 ticks, we lose half of the Initial Risk: -0.5R.
Should our Profit Target at 1.1410 get hit, we'd have made 2.32 times the Initial Risk: +2.32R.
Imagine this trade happening in a totally different market: the E-Mini S&P 500. If we'd get the very same setup, our measured results of the trade in Rs would still be about the same!
Or imagine this is a 5-minute chart, and our stop-loss is just 8 ticks instead of 80 ticks, and we'd have a profit-target of 19 ticks. Again, we'd have about the same results in Rs!
The calculated Risk is also the basis of our position-sizing. So if our Risk (1R) equals $1,000 and we want to have an expected risk of $11,000 per trade, we'd trade 11 contracts ($11,000 / $1,000 = 11).
Let's take this a step further, and try to have about the same risk on all trades independent of the trade setup. To do this, we need to measure volatility, and one of the best ways of doing this is to use the ATR (Average True Range) indicator. The ATR measures the Average Trading Range (in our example of the daily price moves) of the last N periods (we use 20 periods in this example). For all the details, consult this Wikipedia Article.
If we now use the ATR to set our position size instead of the actual stop-loss, we can normalize our risk not only over different markets and timeframes, but also over different trade setups. Let's say you're trading the TTE as in our example. Now the trigger-bar can be very small or very big - and this could be a problem. Does it make sense to risk $500 on both the small and the big bar in the same way? Aren't the odds of getting stopped out with a full loss (-1R) much higher on the small bar? Instead, wouldn't it make more sense to use market volatility to define the position size?
Let's review the same example using the ATR:
We're looking at the same trade setup, but this time we plugged in the ATR (see bottom of the chart) to use market volatility to set our position size. We determined that a move of 1 x ATR (141 ticks) equals 1R.
Now this changes our calculations slightly. We'll leave our stop-loss at the same place, but if it gets hit now, we'd lose on 0.57R instead of 1R as before. On another trade this might be different, of course, on some trades you'll risk more than 1R if it's a huge TTE bar you're dealing with. On another bar, you might have an even smaller risk. But it will always be adjusted to the current market volatility, giving you even more comparable results all over the place.
Using the ATR to determine 1R, we'd also use the ATR now to determine our position size for the trade. If our Risk (1R) equals $1,762.50, and we want to have an expected risk of $11,000 per trade, we'd trade 6 contracts ($11,000 / $1,762.50 = 6.24 = 6).
Let's go back to our example from above, but using the ATR (1 x ATR= 1 R) to measure performance:
We can immediately see that on the S&P trade we made about 10 times as much as on the other two trades, measured against our calculated risk. The beauty of this is that it's easy to figure out the percentage that would be on your account. If you're risking 2.5% on a single trade, you'd have made 1% (2.5% * 0.4) on your account.