I was wondering if anyone knew about a website or any tools that can be used to generate random trades against which to test your own results, to see if they are significantly better than random. I was reading an article a few days ago and the author used the profit factor of a random trade as his benchmark for testing the significance of his own profit factor. He used a PF of 1.2 for long trades and 0.8 for short trades, but he didn't talk about where he got those values or if they were from a specific time period only or if they were the PFs for any random long or short trade on the S&P 500 index for all time periods.

Excel. =IF(NORMSINV(RAND())>=0,1,-1) Run many times will give a sampling distribution of signals to compare. It makes more sense to run against same period as system validation set.

There is absolutely no need for doing that re. intraday trading ... taking random entries & exits will generate about minus 2-ticks (+ commissions) per trade in the long run. You might want to test your trade management against random entries, or your entries against random exits - but what's the heck? The thing about taking random entries, is for long-term trend-following strategies.

In his example above, with the PF 1.2 for random long trades, the price curve he used was probably strongly trending upwards. In such a case a comparison with random trades might make some sense, but it's a better method to just detrend the price curve for the test. Detrended price curves keep all their other characteristics.

Wouldn't the results for intraday trading depend on how long you held? Or are you saying that, on average, for any holding period intraday, price is 2 ticks away from any other time during that day? In any case, thanks for the tip that this shouldn't be a concern for more short-term trading.

Maybe I'm just being dense, but I'm not sure how to go about using that Excel formula output to create trades. Do you add together the resulting 1s and -1s to create a percentage return and then compare that to your percentage return?

The idea is that you are generating sequences of random binary signals over the duration of the asset you want to compare your own signals to. The 1s and -1s represent long and short signals which you can use as random long/short signals. Each time you substitute one of the sequences as your buy short signals, you can derive the corresponding measurement, such as average return per trade to generate a sampling distribution to compare your results to. You can then use something like a t-test to test the hypothesis that your results are better are no better than chance. You can look into "evidence-based TA" by Aronson or "asset price dynamics," S. Taylor to get more trading based insight, but that is a general statistical approach to answer your original question. In fact, Taylor has very good excel based examples you can study.

Is the idea that you generate the entry signal, then manage the trade as if it were an entry signal from your "non-random" method? Otherwise, I don't see how you would get an average return for the sampling distribution trades. Yes, the reason I am asking about this is because I was poking around in Aronson's work last week and it got me to thinking that this was one test I had not done. But now you've got one poster saying that this test isn't necessary for intraday or short-term swing trading, so maybe it isn't a road I want to go down.