151 Estrategias de Trading (151 Trading Strategies)

TL;DR

This comprehensive Spanish book details over 150 trading strategies across various asset classes, including mathematical formulas, source code, and machine learning techniques, serving as an educational resource for traders and researchers.

Contribution

It provides an extensive, detailed compilation of trading strategies with formulas, source code, and pedagogical explanations, covering a wide range of assets and styles, including machine learning approaches.

Findings

Includes over 550 mathematical formulas for trading strategies.

Provides source code for out-of-sample backtesting.

Covers a broad spectrum of asset classes and trading styles.

Abstract

This book, which is in Spanish, provides detailed descriptions, including over 550 mathematical formulas, for over 150 trading strategies across a host of asset classes (and trading styles). This includes stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility (as an asset class), real estate, distressed assets, cash, cryptocurrencies, miscellany (such as weather, energy, inflation), global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms (such as artificial neural networks, Bayes, k-nearest neighbors). We also give: source code for illustrating out-of-sample backtesting with explanatory notes; around 2,000 bibliographic references; and over 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical. ----- Este libro proporciona descripciones detalladas, que incluyen m\'as de 550 f\'ormulas matem\'aticas, para m\'as de 150 estrategias de trading para una gran cantidad de clases de activos y estilos de trading. Esto incluye acciones, opciones, bonos (renta fija), futuros, ETFs, \'indices, commodities, divisas, bonos convertibles, activos estructurados, volatilidad (como clase de activos), bienes inmuebles, activos en distress, efectivo, criptomonedas, miscel\'aneos (como clima, energ\'ia, inflaci\'on), macro global, infraestructura y arbitraje impositivo. Algunas estrategias se basan en algoritmos de aprendizaje autom\'atico (como redes neuronales artificiales, Bayes, k vecinos m\'as cercanos). El libro tambi\'en incluye c\'odigo para backtesting fuera de la muestra con notas explicativas; cerca de 2,000 referencias bibliogr\'aficas; m\'as de 900 t\'erminos que comprenden el glosario, acr\'onimos y definiciones matem\'aticas. La presentaci\'on pretende ser descriptiva y pedag\'ogica.