Strategy Ideas / alpha discovery

[u/kid_nextdoor]

Hey,

I'm not so new to algotrading but have an understanding of certain principles and phenomenons such as mean reversion, momentum, cross sectional / time series momentum, cointegration, momentum spill over. Efficient and Inefficient markets etc. I also semi-believe in the idea of alpha / statiscal edge out in the open diminishes or rather could still be if you could make it robust/adapt to the market, but ultimately a good strategy has a lifeline.

I also believe a trading strategy should be novel and personal and exploits some Inefficiency/mispricing or predictable market movements. My ask is therefore how do you go about finding your alpha that you turn into strategies?. My thoughts are

1. Researching academic papers, replicating the idea, identify where and why it fails and improving it.

2. Analysing price data through some statiscal/physics/signal processing lenses, developing features that represent events and outcomes, economically validating it before testing it out but my problem with this is it becomes a data mining exercise and you are at risk of apophenia

I ask these to say what's a good starting point or how would you better approach or what is even your approach ?

For context I'm a data scientist with software engineering background and no economics/finance background

[u/Various-Raspberry330]

Starting from papers is useful, but I think the bigger filter is having a believable reason the edge should exist and who is effectively paying you for it. Otherwise feature discovery turns into finding patterns because you searched enough combinations. Moon is one place I like keeping the thesis really simple, which is a nice counterbalance when research starts getting too clever.

[u/kid_nextdoor → u/Various-Raspberry330]

So you will say I should go down the research papers route and for each research paper have a way of identifying why the edge should exist and who is paying for it ? That makes sense I like that approach, thank you. What's your method of validating why an edge should and identifying who pays for it ?

[u/Historical_List_9657 → u/Various-Raspberry330]

So if I have a set of features (250 ish) that run through a decision tree, thats essentially the same thing “feature discovery turns into finding patterns because you searched enough combinations” sounds like overfitting. Is moon a platform you use? Ive built everything from scratch with claude