Introduction to Computational Finance and Financial Econometrics

Résumé

This book presents mathematical, programming and statistical tools used in the real world analysis and modeling of financial data. The tools are used to model asset returns, measure risk, and construct optimized portfolios using the open source R programming language and Microsoft Excel. The author explains how to build probability models for asset returns, to apply statistical techniques to evaluate if asset returns are normally distributed, to use Monte Carlo simulation and bootstrapping techniques to evaluate statistical models, and to use optimization methods to construct efficient portfolios.

Contenu

Computing asset returns. Univariate random variables and distributions. Bivariate distributions. Time series concepts. Matrix algebra. Descriptive statistics. The constant expected return model. Introduction to portfolio theory. Portfolio theory with matrix algebra. Statistical analysis of efficient portfolios. Risk budgeting. The single index model.