ABSTRACT
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book provides a comprehensive integration of statistical inference for portfolios and its applications. It explains the foundation of stochastic processes, because a great deal of data in economics, finance, engineering and the natural sciences occur in the form of time series where observations are dependent and where the nature of this dependence is of interest in itself. The book introduces the modern portfolio theory of Markowitz, the capital asset pricing model of Sharpe and the arbitrage pricing theory of Ross. By using dynamic programming, a secence of portfolio weights is obtained in the discrete time case. The book addresses the foregoing models for financial multivariate time series. It discusses Independent component analysis modeling in both the time domain and the frequency domain.
