What the book actually asks is much more interesting: how should machine learning change when the thing being predicted is an asset price?
What I find interesting in this book is that Nagel does not treat finance as just another machine learning problem. In many ML applications, the objective seems fairly straightforward: feed a model enough information, identify patterns, minimize prediction error, and test whether the model works on new data. Nice and tidy.
Bad news is investors do not simply sit there while an algorithm discovers a profitable pattern. They trade on it. Their trades move prices. Those price changes can then weaken the exact relationship the model just discovered.