This applies to trading perfectly as well. It's rare that the true math studs are the rainmakers (though it does happen), and instead the street smart players who just try to reasonable end up dominating. By "street smart", I don't mean people who don't do math though, I'm just talking about people who aren't math olympiads or don't have PhDs in theoretical mathematical fields.
80% models take 20% of the work and are usually more robust during market dislocations and highly resistant to noise and uncertainty compared to very mathematical approaches.
Really good point about verifying a model as well. Once your model is complex enough, it becomes highly probably that much of the model is actually hurting you, but you will have an incredibly hard time determining which part is hurting you. With a simple model, things become a lot easier and as such, the chance of success becomes much higher.
Many people have this misconception that sophisticated players like Citadel or Jane Street are using these complex non-linear models to generate profit. This couldn't be further from the truth: linear models dominate the space at the moment and are the most valuable tool you have.
Of course, linear regression isn't going to do a good job at identifying cat pictures or translating text, but that's because those tasks have relatively high signal to noise ratios. The cleaner the data, the less random the data, the better complex models perform. On the other hand with any kind of financial data, the signal is incredibly weak and a complex non-linear model will most likely get confused by the random patterns in the data.
80% models take 20% of the work and are usually more robust during market dislocations and highly resistant to noise and uncertainty compared to very mathematical approaches.
Really good point about verifying a model as well. Once your model is complex enough, it becomes highly probably that much of the model is actually hurting you, but you will have an incredibly hard time determining which part is hurting you. With a simple model, things become a lot easier and as such, the chance of success becomes much higher.
Many people have this misconception that sophisticated players like Citadel or Jane Street are using these complex non-linear models to generate profit. This couldn't be further from the truth: linear models dominate the space at the moment and are the most valuable tool you have.
Of course, linear regression isn't going to do a good job at identifying cat pictures or translating text, but that's because those tasks have relatively high signal to noise ratios. The cleaner the data, the less random the data, the better complex models perform. On the other hand with any kind of financial data, the signal is incredibly weak and a complex non-linear model will most likely get confused by the random patterns in the data.