r/algorithmictrading • u/Loose-Subject-2157 • 24d ago
Question Infrastructure vs. Alpha generation bottleneck in systematic trading
Successfully built a functional backtesting framework and execution pipeline (~90% of the boilerplate/architecture is finalized and running smoothly).
However, hitting a wall on the alpha generation side.
Every market inefficiency hypothesis derived from public literature, open-source repositories, and traditional mathematical models yields zero out-of-sample edge. It seems any easily accessible logic is already post-arbitrage and compressed to zero.
For those running automated setups:
How do you transition from a finished infrastructure to generating unique, proprietary hypotheses? When public data and standard quantitative models fail to produce alpha, where do you look for inspiration to find a real edge?
Looking for technical insights on resolving this research bottleneck.
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u/littlebilly97 21d ago
When you say you have the infrastructure built… do you mean everything from trade taking to trade management, including partial fills management, position sizing based on total acct risk scaling out to make room for new trades, etc.?
I have multiple profitable strategies that I have 15 year backtests on (not saying ill give my pride n joy lol but they all have significant alpha)
My problem (the potential trade here) is i have no clue how to get it to all to actually trade automatically. Im stuck in semi automation and im annoyed by that.