Loading...
Loading...
Found 4 Skills
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.
8 finance skills. Trigger: financial modeling, market data, risk analysis, quantitative finance. Design: data sources, quantitative methods, and regulatory frameworks.
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.
Implements algorithmic trading strategies using quantitative models and financial APIs for automated trading.