Reward and Risk in Stock Trading: R-Multiple and Expectancy

In this article I am going to introduce 2 terms in my stock trading routines that I use a lot: R-Multiple and Expectancy. These theory was introduced by van Tharp in many of his books.

Most traders, be it the professionals or novices ones, have some sort of exit criteria that they like. Some use a fixed percentage drop from the initial buying price, some prefer to use chart and graph to tell them to get out of the market. I am personally using the fixed percentage stop loss. In different markets, I will use different stop loss percentage as the volatility levels are different. When profit taking, I trust my system (I use algorithm to give me sell signal when the indicators indicating the market has reached the top) to tell me when is right time to get out.

So what is R-Multiples and Expectancy?

1R defines your initial risk. For example, for a $40 stock, my initial risk (my stop loss percentage) is 10% or 4 dollars. This means that I will need to get out of the market if it drops to $36. This also means that your initial risk of $4 is 1R. So if you have lost $2, your R-multiple is -0.5R. Easy?

So, the first two steps you need to ask yourself:

1. Define your 1R - initial risk. For me, I use 8-10% depending on the market I am trading in.
2. For every trade you do, write it in a journal (Excel template is sufficient), and include a column titled "R-Multiples". The formula to calculate it is Profit(Loss) divided by Initial Risk.

So, what is the big deal about this R-Multiples? 

"When you have a complete R-multiple distribution for you trading system (remember, you need to have a system first, and all your trades are strictly following your system), there are a lot of things you can do with it." - van Tharp

One benefit is that the MEAN of R-Multiple, called EXPECTANCY, tells you what you can expect from your system on the average over many trades in terms of R.

Consider the following tables:

Here the expectancy tells you that the average you will make is 0.2R per trade. Therefore, over many trades, say 100 trades, you will make about 20R. 

The standard deviation tells you how much variability you can expect from your system performance. In the sample above, the standard deviation was 0.97R. Typically you can determine the quality of your system by ration of expectancy to the standard deviation. In this example the ration is 0.2, which according to van Tharp, is not good enough. If the ratio remains above 0.25 over many trades, the system can be taken as acceptable.

If you are interested to get the excel file for the above table, get it here.