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Found 38 Skills
Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP). Identifies Stage 2 uptrend stocks forming tight bases with contracting volatility near breakout pivot points. Use when user requests VCP screening, Minervini-style setups, tight base patterns, volatility contraction breakout candidates, or Stage 2 momentum stock scanning.
Calculate risk-based position sizes for long stock trades. Use when user asks about position sizing, how many shares to buy, risk per trade, Kelly criterion, ATR-based sizing, or portfolio risk allocation. Supports stop-loss distance calculation, volatility scaling, and sector concentration checks.
Analyzes coupling between modules using the three-dimensional model (strength, distance, volatility) from "Balancing Coupling in Software Design". Use when asking "are these modules too coupled?", "show me dependencies", "analyze integration quality", "which modules should I decouple?", "coupling report", or evaluating architectural health. Do NOT use for domain boundary analysis (use domain-analysis) or component sizing (use component-identification-sizing).
Apply statistical methods to financial data including descriptive statistics, covariance estimation, regression, hypothesis testing, and resampling. Use when the user asks about return distributions, correlation between assets, building a covariance matrix, running a CAPM regression, testing whether alpha is significant, checking if returns are normal, or estimating confidence intervals. Also trigger when users mention 'volatility', 'how correlated are these', 'fat tails', 'skewness', 'R-squared', 'beta of a fund', 'bootstrap a Sharpe ratio', 'shrinkage estimator', 'Ledoit-Wolf', or ask why their optimizer produces unstable weights.
Provides domain knowledge and guidance for the Flare Time Series Oracle (FTSO)—block-latency feeds, Scaling anchor feeds, feed IDs, onchain and offchain consumption, fee calculation, delegation, and smart contract integration. Use when working with FTSO, price feeds, oracle data, feed consumption, volatility incentives, or Flare Developer Hub FTSO guides and starter repos.
FX carry-trade analysis via Longbridge Securities — combines spot rates, interest-rate differentials (high-yield vs low-yield currencies), volatility, and historical price trends to assess carry opportunities. Analyses common carry pairs (AUD/JPY, NZD/USD, MXN/JPY) and outputs carry yield, drawdown risk, and Sharpe ratio. Triggers: "外汇套息", "套息交易", "carry trade", "利差交易", "高息货币", "低息货币", "汇率套利", "外汇策略", "外匯套息", "套息交易", "利差交易", "高息貨幣", "低息貨幣", "匯率套利", "FX carry trade", "carry strategy", "interest rate differential", "high yield currency", "currency carry", "AUD JPY", "NZD USD".
Quantitative statistics framework for time-series analysis using Longbridge price data — ADF unit root test (stationarity), cointegration (Engle-Granger / Johansen), GARCH volatility modelling (conditional heteroskedasticity), regression diagnostics (Durbin-Watson / Breusch-Pagan), bootstrap confidence intervals, hypothesis tests (t-test / F-test). Requires statsmodels and scipy. Triggers: "量化统计", "ADF检验", "单位根", "协整检验", "GARCH", "自相关", "异方差", "Bootstrap", "假设检验", "量化統計", "ADF檢驗", "單位根", "協整檢驗", "異方差", "假設檢驗", "quantitative statistics", "ADF test", "unit root", "cointegration", "GARCH", "autocorrelation", "heteroskedasticity", "bootstrap", "hypothesis test", "statsmodels".
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".
Maintain portfolio allocations over time using calendar-based, threshold-based, and tax-efficient rebalancing strategies. Use when the user asks about when to rebalance, rebalancing bands, transaction cost trade-offs, tax-efficient rebalancing, or the rebalancing premium. Also trigger when users mention 'my portfolio drifted', 'how often should I rebalance', 'rebalancing across taxable and IRA accounts', 'volatility harvesting', 'buy low sell high automatically', or ask whether to use cash flows to rebalance.
Guides quantitative research for markets and finance—research question framing, data sourcing and quality checks, descriptive and inferential statistics, time series and panel methods (high level), factor and signal research, backtest design and pitfalls (lookahead, survivorship), risk metrics (volatility, drawdown, Sharpe limitations), regime and stress analysis, and reproducible notebooks or reports with explicit limitations and uncertainty communication. Use when the user mentions "quantitative research", "quant researcher", "factor research", "signal backtest", "time series analysis", "panel regression", "alpha research", "Sharpe ratio analysis", "survivorship bias", "lookahead bias", "econometric analysis", or "risk factor model". Not for production ML pipelines (data-scientist, ml-research-engineer), equity narrative reports (equity-research skills), SOX accounting (financial-statements), legal investment advice, or trading execution systems (senior-software-engineer).
Guides authoring, review, optimization, and false-positive debugging of YARA-X detection rules for malware identification across PE, script, npm, Office, Chrome extensions (crx module), and Android DEX (dex module). Covers string and atom quality, condition short-circuiting, legacy YARA migration, yarGen/FLOSS workflows, goodware validation, and production deployment—not full malware reverse engineering, network IDS (Suricata/Snort), or memory forensics (Volatility). Use when the user asks to write YARA rule, YARA-X, yr check, yr scan, false positive YARA, yarGen, malware detection rule, crx module, dex module, optimize YARA performance, or migrate legacy YARA.
Comprehensive techniques for acquiring, analyzing, and extracting artifacts from memory dumps for incident response and malware analysis.