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Found 6 Skills
Using palladium's leading trend reversal as a confirmation condition, verify whether silver's short-term price movements are supported by both industrial sentiment and risk sentiment, and mark failed trends that lack palladium participation.
Cross-asset correlation analysis including rolling correlation, hierarchical clustering, tail dependence, and regime-dependent correlation
Construcción y optimización cuantitativa de portafolios: Markowitz (scipy.optimize + Monte Carlo), Black-Litterman (prior CAPM, views absolutas/relativas, posterior bayesiano), HRP/HERC/NCO (clustering jerárquico, risk parity, NCO con restricciones). Todo flat numpy + scipy, sin Riskfolio-Lib ni PyPortfolioOpt.
Implements algorithmic trading strategies using quantitative models and financial APIs for automated trading.
8 finance skills. Trigger: financial modeling, market data, risk analysis, quantitative finance. Design: data sources, quantitative methods, and regulatory frameworks.
Volatility estimation, forecasting, and regime classification using GARCH, EWMA, realized volatility, and volatility cones