This is a great book for someone—academic or practitioner—who is new to financial time series analysis and needs an accessible introduction. The book is actually a wide-ranging survey of topics in financial econometrics. It is much like an updated version of Campbell, Lo and MacKinlay (1997) with excellent information on ARCH and stochastic volatility models. It will appeal to quantitative professionals but is primarily targeted towards researchers.

Opening chapters describe what might be called classical financial econometrics. They introduce time series analysis, explain constant volatility AR, MA and ARMA models, and explore market efficiency in light of market anomalies such as the January effect. Most of the important literature cited comes from before 1980, so you know this is no longer a mainstream topic.

Next, there are three chapters that look at using time series analysis to predict future prices. The author comments that these chapters "can be skipped by anyone who considers all nontrivial point forecasts are futile." I took his advice.

The second half of the book is excellent. The author introduces ARCH and stochastic volatility models. The treatment is accessible but still rigorous. He actually walks readers through basic spreadsheet calculations. For anyone implementing one of these models for the first time, I can't think of a better resource. The book's last four chapters apply the theory to high frequency data and options pricing.