name: credit-relative-value description: "Credit Relative Value workflows for quantitative research, implementation, and production controls. use when tasks involve credit and relative workflows in production trading systems."
Credit Relative Value
objective
Execute credit relative value work with reproducible research, explicit controls, and deployable outputs.
workflow
- define hypothesis, trade horizon, and capital-allocation constraints.
- build leak-safe features and align targets to executable decision times.
- estimate signal edge, turnover impact, and capacity limits.
- stress performance across volatility, liquidity, and crowding regimes.
- promote only when net performance remains robust after full trading costs.
required diagnostics
- signal monotonicity, decay profile, and hit-rate stability.
- capacity stress from participation growth and liquidity depletion.
- regime dependency and edge persistence after parameter shifts.
- cost-adjusted performance versus naive and benchmark alternatives.
risk controls
- enforce gross and net exposure ceilings by strategy and instrument.
- enforce concentration and turnover caps to prevent capacity overload.
- enforce deactivation triggers for edge decay and drawdown breaches.
outputs
- run
python scripts/credit_relative_value_diagnostics.py input.csv --output diagnostics.jsonand keep the json artifact. - write an implementation memo using
references/credit-relative-value-playbook.mdwith assumptions, tests, limits, and rollout plan.
resources
- use
scripts/credit_relative_value_diagnostics.pyfor deterministic diagnostics. - use
references/credit-relative-value-playbook.mdfor the domain-specific checklist and delivery structure.