This chapter provides an overview of the statistical modelling of financial asset returns, beginning with return definitions and ending with the statstical properties exhibited by equity returns, interest rates and exchange rates. The strengths and weakness of competing return definitions and distribtuional assumptions are clearly illustrated. Chapter ending review ... click here for more details.
This chapter is intended for applied researchers wishing to develop time series models. Model properties for autoregressive, moving average ARMA, seasonal, unit root, regression models with autocorrelated errors and fractionally differenced series are developed. The properties of forecasts are clearly illustrated. The presentation focuses on the practical aspects of ... click here for more details.
This chapter is intended for practitioners and researchers who are in need of developing conditional volatility models for forecasting, risk measurement or derivative pricing purposes. The modeling benefits and deficiencies of each model are clearly illustrated focusing on the strengths and weakness in financial applications. For every model the ... click here for more details.
This chapter contains an overview of non-linear in mean models and provides rationale for their use in financial applications. The structure of each model is presented with an application contrasting the fit of an ARMA-GARCH model with the non-linear model under consideration. Application of non-linear models including non-parametric kernel regression, ... click here for more details.
Very informative insight into the unique challenges of modeling high frequency financial time series. The chapter contains a particularly good presentation of how market micro-structure features, non-synchronous trading and the bid-ask spread, impart autocorrelation to high frequency price series. Equity trade data obtained from Trades, Order Reports and Quotes ... click here for more details.
This chapter provides an overview of the properties of continuous time stochastic processes built from the Wiener increments and their application as models for the price of the underlying asset in derivative valuation. Kou (2002) option pricing model for an underlying price characterized by a jump diffusion process is ... click here for more details.
The intended audience for this chapter includes risk managers seeking to improve methods for determining the likelihood of extreme price changes and researchers seeking insight to the phenomena that affect extreme outcomes. In this chapter conditional value at risk implies modeling extreme changes with additional explanatory variables. The ... click here for more details.
This chapter is useful for researchers and investment managers seeking to identify relationships between related time series. The author emphasizes intuition relevant for application rather than theoretical development. Interpretations of fitted models provide useful guides to implementation for other series. Model properties, methods of model selection and estimation ... click here for more details.
Material presented in this chapter is useful for financial researchers seeking an introduction to current methods used in modeling the expected return and risk tradeoff. The market model of Sharpe serves as the introduction to factor models with extensions to the macroeconomic factor model of Chen, Roll and Ross ... click here for more details.
This chapter is useful for a portfolio/risk manager seeking to examine the dynamic properties of portfolio risk. The "curse of dimensionality" has motivated development of many techniques to parsimoniously model the variance-covariance matrix of a large portfolio. Techniques for estimating multivariate GARCH models under restrictive assumptions are illustrated ... click here for more details.