PatternCatcher MCP skill for similar K-line stock and futures search
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Updated
Jun 22, 2026 - Python
PatternCatcher MCP skill for similar K-line stock and futures search
SSQuant Agent workflow for futures strategies, data_server diagnostics, CTP/SIMNOW runtime checks, and Chinese backtest reporting.
Detect backtest overfitting & multiple testing: Deflated Sharpe Ratio, PBO (CSCV), purged/embargoed CV, Harvey-Liu haircut. Research/education only, not investment advice.
Convex portfolio optimizer: mean-variance / min-variance / max-Sharpe / risk-parity / max-diversification with weight caps, sector & exposure neutrality and turnover limits. Research/education only, not investment advice.
Barra-style multi-factor risk model & risk attribution: cross-sectional WLS factor returns, Ledoit-Wolf shrinkage covariance, factor vs specific risk decomposition. Offline via a panda_data adapter. Research/education only, not investment advice.
Run reproducible index addition, deletion, and weight-change event studies around announcement or effective-date anchors.
Audit normalized intraday OHLCV data for timestamp, gap, price, volume, and trading-date defects before research or backtesting.
Audit split and cash-dividend consistency across raw and adjusted equity prices before research or backtesting.
Audit continuous futures contract selection, roll events, same-day price gaps, and adjustment ledgers before research or backtesting.
Stress portfolio liquidation capacity, pro-rata redemption shortfalls, and spread plus square-root impact costs.
Audit point-in-time universe membership, security lifecycles, stable identities, and missing delisting returns before backtesting.
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