Good sharing and your list of factors to consider is excellent. Reading your posts is a sure way to shorten my learning curve!
Since higher trade count is the way to go, does it go without saying that a stock universe with more candidates is generally preferred (Russell 3000 better than SP500, which in turn is better than Nasdaq 100)?
Good points from Mickey, that is certainly a voice of experience speaking.
The bigger the better, in general. Unless you are specifically designing a system for some index.
With bigger universe you will start seeing bigger outliers and more vicious DD, so your position sizes will likely need to be smaller to mitigate. Which is actually a good thing. It is better to get used to large DD in your backtest and suspect something is wrong if they don't ever happen. Over the time you will get a sense on what DD should look like for what position sizes / hold periods / exposure. With Nasdaq 100, tickets sample is quite small, so you will see more systems looking like they have small DD and it is easier to overfit. If something is built just based on NS100, I suspect you real life expected DD will probably be 3-4 times of what backtest showed. It all depends, but the more filtered, the less trade count, the more deviation from backtest you need to expect in the future.
RealTest supports breaking test results into baskets (bins), which is amazing for slicing/dicing your universe and seeing if there are clusters / tendencies you can take advantage of or filter out. It takes some time to understand how that works, but it is totally worth it.
Here is an example. I grouped 3k trades from one system into equal range bins using some measurement of stocks' liquidity. Y-axis is that "bin"'s average trade's PL in %, X-axis - different ranges of liquidity. First bin is for liquidity <0.48, average trade PL is ~0.6%, second 0.48-0.73 with avg. PL ~0.25% etc. You can clearly see that edge deteriorates with a greater stock's liquidity. Which highlights, why, in general, a successful individual retail trading is possible.
Val
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