The study of time series is concerned with time correlation structures. It has diverse applications ranging from oceanography to finance. The celebrated CAPM model and the stochastic volatility model are examples of financial models that contain a time series component. Time series analysis can be useful to see how a given asset, security or economic variable changes over time or how it changes compared to other variables over the same time period. The Financial Time Series applications provide a convenient interface for creating, managing, and manipulating financial time series objects. In the past few years there have been several changes in the financial landscape as well as developments in using time series techniques for financial modelling. The book aims to highlight several of these standard as well as non-standard techniques applied in finance using S-Plus and R as statistical analysis tools. The book covers practical aspects of these models including estimation and testing of the models and shows practical examples. This book is designed to help readers grasp the conceptual underpinnings of time series modelling in order to gain a deeper understanding of the ever-changing dynamics of the financial world. It covers theory and application equally for readers from both financial and mathematical backgrounds.