The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
From the reviews:
“Academic researchers and graduate students in statistics, economics and financial engineering, Industry banking, investments and insurance. … The handbook is clearly written and provides a broad and detailed overview of the major topics within financial time series. … serves as a good reference for the financial time series methods and will be invaluable to many researchers. It also excels in giving very clear and concise description of a number of important methodologies.” (Lasse Koskinen, International Statistical Review, Vol. 78 (1), 2010)
From the Back Cover
This handbook presents a collection of survey articles from a statistical as well as an econometric point of view on the broad and still rapidly developing field of financial time series. It includes most of the relevant topics in the field, from fundamental probabilistic properties of financial time series models to estimation, forecasting, model fitting, extreme value behavior and multivariate modeling for a wide range of GARCH, stochastic volatility, and continuous-time models. The latter are especially important for modeling high frequency and irregularly observed financial time series and provide the foundation for estimating realized volatility. Cointegration and unit roots, which are extremely important concepts for understanding and modeling nonstationary time series, and several further relevant topics in the field of financial time series (i.e. nonparametric methods, copulas, structural breaks, high frequency data, resampling and bootstrap methods, and model selection for financial time series among others) are included in detail. All contributions are clearly written and provide, in a pedagogical manner, a broad and detailed overview of the major topics within financial time series.
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