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Found 12 Skills
Retrieve financial health scores including Altman Z-Score and Piotroski Score for public companies. Use when assessing bankruptcy risk, financial strength, value investing screening, or credit quality analysis.
Statistical arbitrage tool for identifying and analyzing pair trading opportunities. Detects cointegrated stock pairs within sectors, analyzes spread behavior, calculates z-scores, and provides entry/exit recommendations for market-neutral strategies. Use when user requests pair trading opportunities, statistical arbitrage screening, mean-reversion strategies, or market-neutral portfolio construction. Supports correlation analysis, cointegration testing, and spread backtesting.
Calculate Altman Z-Score to predict corporate bankruptcy probability from financial ratios. Use this skill when the user needs to assess a company's financial distress risk, screen for bankruptcy-prone firms, or evaluate credit worthiness — even if they say 'bankruptcy prediction', 'financial distress score', or 'Z-score analysis'.
Generate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction
Perform forensic-level analysis of a single company's financial statements, evaluating earnings quality, financial health, fraud risk, and operational efficiency. Use when the user asks for a deep dive into a company's financials, DuPont analysis, earnings quality check, balance sheet analysis, cash flow analysis, Altman Z-score, Beneish M-score, working capital analysis, or any detailed single-company financial examination.
Statistical scoring with z-scores, percentiles, freshness decay, and cross-category normalization. Rank and compare items with confidence scoring.
Mean-reversion strategy tools including Hurst exponent, half-life estimation, z-score signals, ADF testing, and Ornstein-Uhlenbeck modeling
Detect anomalies in data using statistical and ML methods. Z-score, IQR, Isolation Forest, and time-series anomalies.
Use when hunting for threats in an environment, analyzing IOCs, or detecting behavioral anomalies in telemetry. Covers hypothesis-driven threat hunting, IOC sweep generation, z-score anomaly detection, and MITRE ATT&CK-mapped signal prioritization.
Pairs trading / statistical-arbitrage strategy via Longbridge Securities — tests cointegration between two correlated assets using the Engle-Granger (ADF) method, computes the optimal hedge ratio via OLS, calculates spread Z-score, half-life of mean reversion, and generates entry/exit signals (long spread when Z > 2, short spread when Z < -2, exit when |Z| < 0.5). Triggers: "配对交易", "统计套利", "协整", "价差交易", "对价交易", "双股套利", "配對交易", "統計套利", "協整", "價差交易", "pairs trading", "statistical arbitrage", "cointegration", "spread trading", "mean reversion pairs", "hedge ratio", "half-life", "ADF test", "Kalman filter", "Z-score spread", "spread mean reversion".
Multi-factor cross-sectional stock-selection strategy via Longbridge Securities — scores stocks in an index or candidate pool on value (1/PE, 1/PB), momentum (60-day return), quality (ROE), and low-volatility (60-day HV) factors; standardises to Z-scores; composites with equal or IC-weighted combination; constructs a TopN long portfolio (high-score group) and bottom-N short portfolio. Triggers: "多因子", "因子选股", "量化选股", "多因子模型", "因子投资", "横截面", "TopN组合", "IC权重", "多因子", "因子選股", "量化選股", "多因子模型", "橫截面", "multi-factor", "factor investing", "quantitative stock selection", "cross-sectional factor", "factor model", "IC weighting", "factor composite", "TopN portfolio", "factor score", "Z-score ranking".
Detect and classify telemetry anomalies on Cognitum Seed devices