# Calculating basic win% of simple trend-following strategy?

I apologize if this isn't the correct place to post this. I'm not quite sure where else I should post on stackexchange.

I'd like to preface this by saying I'm not actually planning on trading. This is more of a thought experiment carried out in my own free time. I have a very basic trend-following model that looks at several technical indicators. The model returns signals that indicate whether to take a long (1) or short position (-1). I'm interested in calculating some sort of simple win% to see how many times this model has potentially made a good trade signal.

   Position    High    Low   Close     Open
1           3.375   3.3545  3.375   3.355   3.3985

0
0
0
1          3.4075    3.3935  3.397   3.4065  3.4134


Would I then look at prices (3.375 close) at the first signal and prices when at the signal changed (3.3935 close)? Since prices increase on a long signal, then this would count as a win. Let's call this $W_1$. If I repeated the same calculation throughout my series and got the number of wins $\sum_{i=1}^{n} W_i$, would it then make sense to divide this by number of long signals to get a win% $\frac{\sum_{i=1}^{n} W_i}{\text{# long signals}}$.

This seems a little silly and naive to me, so I'm open to feedback!

• I think you will find that for these trend following models the Win% is actually below 50%. But the claim is that once in a while you get a big win which will more than compensate for several small losses. So you should look at Expected Win (in dollars, or points) which could of course be positive or negative, in addition to (or in place of) the win%. In addition you should try to estimate the statistical significance of the result. – Alex C Apr 1 '17 at 4:27
• @AlexC Thanks! It definitely makes sense to look at the expected value + significance. Does my way of calculating win% make sense at all? – Nikitau Apr 1 '17 at 16:45
• Yes, if the price goes up on a long position you count it as 1 win and then you find the frequency of wins by taking a ratio "number of favorable outcomes over number of cases" as usual in statistics. – Alex C Apr 1 '17 at 16:48
• @Alex C A quick follow-up question, is it then possible for loss % to not be exactly 100 - win %`? I tried calculating loss % out of curiosity in the opposite manner of win (i.e: prices going down on long positions) and both win % and loss % don't exactly add up to 100%. – Nikitau Apr 1 '17 at 22:42
• You need to include "unchanged" in one of the two categories: for example "win or tie" vs "not win", x >= 0 vs x<0, so hey do add up to 100%. – Alex C Apr 2 '17 at 14:52