Trading System Development 101 (Part 6)

Today I want to tie up some remaining loose ends.

Performance report details need to be carefully considered because subtle interactions may not give us what we want.

I’d kill (figuratively speaking) for a profit factor (PF) of 2.0, for example, but before confirmation bias sweeps me away I need to look closer. Both of these will get me PF = 2.0: $100K profit + $50K loss and $200K profit + $100K loss. Assuming this is trading one contract with a $100K account, I now know the former, unlike the latter, will not be interesting to me. The latter has a good chance to meet my criteria and be viable.

As another example, I need to look closer before getting overly excited about a strategy that generates an average trade of +$1,000. This is much more attractive for an average trade duration of five days than it is 50-100. The latter will have far fewer trades and less overall profitability. This is worthy of note even though most backtesting platforms I have seen do not display average trade per day (as mentioned in third-to-last paragraph here).

Finally, the interaction between trade duration and sample size was discussed in the third-to-last paragraph here. In Part 4, I mentioned some people would be happy with a longer duration strategy. Of important statistical note is the fact that trade duration and sample size are inversely related.

One advantage to longer duration is lower transaction fees (slippage and commission). Transaction fees (TF) are an enormous enemy of net profits. For every trade, TF is constant while longer trades allow for more market movement and potentially larger profits. The adverse impact of TF is therefore inversely related to trade duration. I have to laugh when I think about all the intraday systems I have seen discussed online. I already know the difficulty of finding viable strategies on the daily time frame; viable intraday strategies are probably much harder to find! Combining this rationale with the frequent footnote that so many studies don’t include TF helps this all to make sense.

Until your testing proves otherwise, let this be the one takeaway with regard to TF: many strategies that fail on a short time frame have a much better chance to work if trades are held much longer because average trade may then be large enough to more than offset multiple commissions.

Is anyone still enamored with day trading? I hope not.

Next time, I will begin discussion of a different approach to system development.