Money Markets Repo Stock Lending
objective
Execute funding and borrow workflows with reproducible analytics, explicit controls, and production-ready monitoring.
workflow
- •define instrument universe, funding horizon, and financing benchmark assumptions.
- •ingest repo, borrow, inventory, haircut, and settlement-fail data with point-in-time alignment.
- •decompose financing costs into gc, specialness, borrow fees, and collateral frictions.
- •stress liquidity using utilization spikes, fail-rate jumps, and collateral concentration shocks.
- •release only when funding metrics are stable, explainable, and within risk limits.
required diagnostics
- •specialness behavior by instrument, tenor, and venue.
- •all-in financing cost stability versus benchmark funding curves.
- •borrow utilization pressure and inventory-depletion risk.
- •settlement-fail clusters and carry impact.
- •collateral concentration and haircut sensitivity.
risk controls
- •enforce counterparty, collateral, and tenor concentration limits.
- •enforce hard alerts on fail-rate and utilization breaches.
- •enforce fallback assumptions for stale or missing borrow data.
outputs
- •run
python scripts/money_markets_repo_stock_lending_diagnostics.py input.csv --output diagnostics.jsonand keep the json artifact. - •write an implementation memo using
references/money-markets-repo-stock-lending-playbook.mdwith assumptions, tests, limits, and rollout plan.
resources
- •use
scripts/money_markets_repo_stock_lending_diagnostics.pyfor deterministic diagnostics. - •use
references/money-markets-repo-stock-lending-playbook.mdfor the domain checklist and delivery structure.