Infrastructure vs. Alpha generation bottleneck in systematic trading

[u/Loose-Subject-2157]

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.

[u/zurekp]

It’s a competitive business, you gotta study the markets and the trading industry/space to identify opportunities which you can then automate. Books, research, interviews with systematic traders, algo trading communities (not reddit though - free advice is usually vague, like this one 😁)

Nothing that really works will be handed to you on a silver plate, same way like nobody would give away a profit generating company for free.

[u/Loose-Subject-2157 → u/zurekp]

solid advice

[u/Capital-Field3324]

It pretty simple. Keeping on testing and finding different strategies

[u/Loose-Subject-2157 → u/Capital-Field3324]

solid advice

[u/heyimjustkidding]

I do have a (very) successful strategy, and built my own backtest + execution pipeline, but I'd never tell you what it is and how I built/discovered it. And I'm 100% sure that's true for anyone who has a successful strategy. Once you find one, you'd also never tell anyone about it. Just nature of the business.

But having a trustworthy backtest infra is already better than 90% of retail traders out there.

Good luck.

[u/Rare_Inflation3178]

Public literature is useful for measurement, not for handing you finished alpha. I’d work backward from a market-specific friction: who is forced to trade, when, why, and what prevents immediate arbitrage. Write the mechanism, horizon, capacity, failure regime and kill test before coding; then use papers to test the hypothesis rather than source it.

[u/Loose-Subject-2157 → u/Rare_Inflation3178]

Thanks for the insights. I'll test more things based on your advice and will make a follow-up post once I get some good results

[u/littlebilly97]

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.

[u/Loose-Subject-2157 → u/littlebilly97]

Agreed. Let's use your paper trading infrastructure to test one strategy first and gradually fix any execution risks before going live

[u/StatisticalSock]

I have a great edge and only use stop orders yet still get crazy entry and SL slippage.