Cipra T. Time Series in Economics and Finance

Springer, 2020. — 409 p. — ISBN: 978-3-030-46346-5.This book presents the principles and methods for the practical analysis and prediction of economic and financial time series. It covers decomposition methods, autocorrelation methods for univariate time series, volatility and duration modeling for financial time series, and multivariate time series methods, such as cointegration and recursive state space modeling. It also includes numerous practical examples to demonstrate the theory using real-world data, as well as exercises at the end of each chapter to aid understanding. This book serves as a reference text for researchers, students and practitioners interested in time series, and can also be used for university courses on econometrics or computational finance.Random Processes
Trend
Seasonality and Periodicity
Residual Component
Box–Jenkins Methodology
Autocorrelation Methods in Regression Models
Volatility of Financial Time Series
Other Methods for Financial Time Series
Models of Development of Financial Assets
Value at Risk
Methods for Multivariate Time Series
Multivariate Volatility Modeling
State Space Models of Time Series