Course unit content
1) An Overview of the empirical regularities observed in the series of financial returns
Form of distribution, time dependence and volatility clustering.
2) Stochastic processes for financial returns series
Overview of the concept of the stochastic process. Moments of stochastic process and their estimation. Some types of stochastic process: white noise, random walk, autoregressive, moving average. Various phases of the Box-Jenkins method: preliminary treatment, identification, estimation, validation
3) Models for the analysis and forecasting volatility of financial returns series
Concept of volatility. Volatility models. ARCH and GARCH models.
4) Some additions
Work to assess the smoothing goodness of prediction and assessment of market risk (Value at Risk). The exponential
A number of sessions will be held in the computer lab on real financial time series using the Eviews program
Bibliography
Recommended texts : Handouts on all topics covered in the course (available at the Faculty photocopy centre). Further reading: BUZZIGOLI L., Modelli di analisi delle serie temporali finanziarie. Rassegna ed applicazioni di modelli di tipo ARCH, Dipartimento Statistico, Università di Firenze, 1994.DI FONZO T., LISI F., Complementi di statistica economica. Analisi delle serie storiche univariate, Cleup, Padova, 2000. FRANSES P. H., VAN DIJK D., Non linear time series models in empirical finance, Cambridge University Press, Cambridge, 2000. HAMILTON J., Econometria delle serie storiche, Translation by Sitzia B., Monduzzi Editore, 1995. MILLS T. C., The econometric modelling of financial time series, Cambridge University Press, Cambridge, 1999