Chapter 1
Financial Time Series and Their Characteristics
Financial time series analysis is concerned with the theory and practice of asset valuation over time. It is a highly empirical discipline, but like other scientific fields theory forms the foundation for making inference. There is, however, a key feature that distinguishes financial time series analysis from other time series analysis. Both financial theory and its empirical time series contain an element of uncertainty. For example, there are various definitions of asset volatility, and for a stock return series, the volatility is not directly observable. As a result of the added uncertainty, statistical theory and methods play an important role in financial time series analysis.
The objective of this book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series, and gain experience in financial applications of various econometric methods. We begin with the basic concepts of asset returns and a brief introduction to the processes to be discussed throughout the book. Chapter 2 reviews basic concepts of linear time series analysis such as stationarity and autocorrelation function, introduces simple linear models for handling serial dependence of the series, and discusses regression models with time series errors, seasonality, unit-root nonstationarity, and long-memory processes. The chapter also provides methods for consistent estimation of the covariance ...
