| name | simons-quant |
| description | Use when evaluating Jim Simons / Renaissance-style quantitative strategies: many weak signals, statistical validation, signal decay, portfolio construction, execution cost, and model risk. |
| invest | ./invest.md |
Simons Quant
Use this skill to apply a Renaissance-style quantitative lens: convert market intuition into testable signals, combine many small edges, validate statistically, control execution costs, and monitor signal decay.
When To Use
- Quant strategy design or review
- Signal research, factor testing, and backtest critique
- Statistical arbitrage and many-small-edges portfolio thinking
- Whether a trading rule is robust or overfit
Trigger phrases include Simons, Renaissance, Medallion, quant, stat arb, backtest, signal, alpha decay, and overfit.
Process
- Translate the hypothesis into measurable signals.
- Define universe, holding period, costs, and data availability.
- Test out-of-sample and across regimes.
- Combine weak signals into a portfolio rather than relying on one story.
- Model execution cost, capacity, turnover, and slippage.
- Monitor decay and shut down signals that stop working.
Output Format
# Simons Quant View: [Strategy]
## Verdict
Research / Paper Trade / Deploy Small / Reject / Overfit
## Hypothesis
## Signal Definitions
## Validation Plan
## Portfolio Construction
## Execution And Capacity
## Failure Modes
Guardrails
- Do not trust in-sample backtests.
- Do not ignore transaction costs.
- Do not confuse correlation with durable edge.
- Do not deploy before data leakage checks.
Questflow Use
In Questflow, this skill is best used as a signal-research and systematic-strategy review module.
