Agentic Multi-Strategy Trading System

I built a multi-strategy US equities research system to test a narrow thesis: LLMs are useful in the creative research loop, but the money path should remain deterministic, replayable, and pitfall-aware. The system separates proposal and critique from execution, risk, and verification.

The final result is intentionally honest. In the 2013-2015 bull window, the system did not beat either benchmark on a risk-adjusted basis. What it demonstrates is a disciplined agentic workflow with gates that can say no, point-in-time data handling, and a zero-LLM deterministic path for portfolio construction, allocation, and PnL.

Locked OOS result

Annual walk-forward, 2013-2015

The system

-0.083

Sharpe

Total return
-2.01%
MaxDD
-9.66%

Equal-weight universe

0.879

Sharpe

Total return
41.65%
MaxDD
-15.29%

Cap-weighted universe

1.012

Sharpe

Total return
43.63%
MaxDD
-12.43%

The spread is the point: over this window, broad-market beta won. The system is lower-beta and includes market-neutral exposure, so the verification result reads as beta versus alpha rather than a victory lap.

Equity curve

The current image artifact is synced from the results directory. The final sync before deploy should regenerate this chart from the locked result bundle.

Open verification details
Equity curve for the system against the equal-weight benchmark over the 2013-2015 out-of-sample window

See the substrate

Policy population

as of 2012

PM2006200720082009201020112012Mandate
long_onlyACTIVEACTIVEACTIVEACTIVEACTIVEACTIVEACTIVE50L/0S / vol n/a
market_neutralACTIVEACTIVEACTIVEACTIVEACTIVEACTIVEACTIVE50L/50S / vol n/a
low_volACTIVEACTIVEACTIVEACTIVEACTIVEACTIVEACTIVE50L/0S / vol 8%

Market-neutral entered probation after the structural decay decision; the other PM mandates remained active.