Quantitative portfolio management. With applications in Python (Q1986365)

This book presents quantitative methods for modelling the performance of financial assets, deriving from there optimal portfolios and estimating the parameters of the models. It consists of 10 chapters, the titles of which quite eloquently characterize its content. They are: Returns and the Gaussian Hypothesis; Utility Functions and the Theory of Choice; The Markowitz Framework; Markowitz Without a Risk-Free Asset; Markowitz with a Risk-Free Asset; Performance and Diversification Indicators; Risk Measures and Capital Allocation; Factor Models; Identification of the Factors; Exercises and Problems. In more detail, the hypothesis of normality, for the asset returns, and some statistical tests of this assumption are presented in the first chapter. From the second chapter on, every investment strategy is analysed from a risk/return perspective, the risk being defined as the standard deviation of the returns. The book covers the Capital Market Line, the two funds theorem, the Tangent and Market Portfolio and the Security Market Line results. The text aims at demonstrating all the core results, very rigorously with no need for exterior references. The demonstrations are often based on simple algebra, and most of the results can be interpreted geometrically. Since the book contains both rigorously stated theory and practical instructions, up to instructions for programmers, it will be useful for a very wide audience, from students and teachers to experienced professionals in quantitative finance. It is written in clear, simple language and is quite interesting.