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Found 59 Skills
Build forecasting models with Meta's Prophet for business time series with holidays and changepoints. Use this skill when the user needs user-friendly time series forecasting, handling of missing data and holidays, or automatic changepoint detection — even if they say 'forecast with Prophet', 'business forecast', or 'easy time series model'.
When the user wants to forecast using deep learning, LSTMs, transformers, or neural networks. Also use when the user mentions "neural network forecasting," "LSTM," "GRU," "transformer forecasting," "attention mechanisms," "seq2seq," "temporal convolution," "deep learning time series," or complex non-linear patterns. For traditional forecasting, see demand-forecasting. For general ML, see ml-supply-chain.
Cointegration testing for pairs trading using Engle-Granger, Johansen, and rolling stability analysis
Datos macro y sociales de Argentina via la API oficial Series de Tiempo del Estado (apis.datos.gob.ar/series). ~4250 series del INDEC + BCRA + Min Economia + Sec Trabajo. Sin auth, sin API key. IPC nacional, EMAE, IPI, ISAC, EPH (desempleo), pobreza, comercio exterior, salarios (RIPTE, SMVM), tipo de cambio, reservas, REM expectativas. Transformaciones builtin (% YoY, % YTD, change) y agregacion temporal (daily→monthly→yearly) server-side. La API mas estable y mejor documentada del repo.
Expert-level data science, analytics, visualization, and statistical modeling
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
InfluxDB Cloud integration. Manage data, records, and automate workflows. Use when the user wants to interact with InfluxDB Cloud data.
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).
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data. Use for CSV/JSON/Parquet processing, statistical analysis, time series, and creating charts.
Combine multiple forecasting models into ensemble predictions for improved accuracy. Use this skill when the user needs to improve forecast reliability, combine ARIMA/Prophet/ETS outputs, or build a robust forecasting pipeline — even if they say 'combine forecasts', 'model averaging', or 'which forecast should I trust'.