I mostly agree with this. Treating markets as an exercise purely in data science is a _bad idea_. Risking money without a solid understanding of market mechanics and trading conventions is a recipe for disaster. Taking a Bayesian view won't save you either - this is a land where some new "six sigma" event happens every six months.

That said, the same logic that holds for identifying profitable strategies within an institution holds for individuals: unless you have better gear, don't fish a crowded pond. As an individual, your small size is, in some regards, an advantage. Institutions routinely pass on strategies that don't have capacity (there's not enough liquidity to make the strategy's returns worthwhile relative to their trading level) or strategies that aren't quite up to their standards (but might be up to yours). There's also a huge class of strategies that have somewhat choppy but long run consistent returns. Traders and funds worried about MoM track records won't touch those.

Fees are the biggest barrier to entry. Institutions enjoy substantial discounts and an ability to amortize costs across a much wider base, making the strategy performance hurdle rate proportionally higher for smaller traders.