Author Description

<b>Fundamental topics and new methods in time series analysis</b><p><b><i>Analysis of Financial Time Series</i></b> provides a comprehensive and systematic introduction to financial econometric models and their application to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described.<p>The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods. Timely topics and recent results include:<ul><li>Value at Risk (VaR)<li>High-frequency financial data analysis<li>Markov Chain Monte Carlo (MCMC) methods<li>Derivative pricing using jump diffusion with closed-form formulas<li>VaR calculation using extreme value theory based on a non-homogeneous two-dimensional Poisson process<li>Multivariate volatility models with time-varying correlations</ul><p>Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance, Analysis of Financial Time Series offers an in-depth and up-to-date account of these vital methods.