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Nonparametric Finance

ISBN: 978-1-119-40910-6
744 pages
March 2018
Nonparametric Finance (1119409101) cover image


This book examines the applications of nonparametric prediction methods in portfolio selection. The first chapter introduces basic financial assets and is useful for people with a background solely in mathematics and statistics. Next, the book is divided into four main parts: statistical finance, risk management, portfolio management, and pricing of securities. Part I on statistical finance introduces basic concepts, techniques, and methods, such as univariate data analysis, multivariate data analysis, time series analysis, and prediction. Part II covers volatility prediction and quantile estimation. Next, Part III on portfolio management examines basic concepts of portfolio theory, performance measurement, Markowitz portfolios, dynamic portfolio selection, and option portfolios. Finally, Part IV on pricing of securities discusses principles of asset pricing, Black-Scholes pricing and hedging, quadratic pricing and hedging, as well as interest rate derivatives. Throughout the book, the author emphasizes economic significance more than statistical significance. For example, there is more emphasis on the Sharpe ratios of portfolios, than on the predictability of asset returns in terms of the mean squared prediction error. This book contains a strong graphical component. The author applies various visualization techniques to present the results and to describe the methods.

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