haha, I see. Could you elaborate on what you mean by the 'market-model side?' Like creating actual trading strategies?
I plan to investigate strategies to exploit legitimate economic phenomena as opposed to just throwing darts at the wall.
Trading system performance usually depends on serial correlation and doing k-folds may destroy that resulting in unrealistic results. See trend-following systems for example. It may work for medium frequency but still it is a dubious concept because the problem with trading systems is not validation but non-stationarity.we're learning about k-fold cross validation in my statistical machine learning class, do you think that this technique could be helpful for eliminating some of the random winners that you mentioned?
I mean, what's the alternative to backtesting?
An example of a "legitimate economic phenomenon"?
Trading system performance usually depends on serial correlation and doing k-folds may destroy that resulting in unrealistic results. See trend-following systems for example. It may work for medium frequency but still it is a dubious concept because the problem with trading systems is not validation but non-stationarity.

That being said, I think machine learning probably can be one of the most dangerous approaches to trading in terms of the probability of being "fooled by randomness." Like I said, I think machine learning is cool and applicable, but personally I see it as more of a tool to be used in conjunction with others as you also alluded to.