"G. d'Annunzio"
A sound familiarity with undergraduate statistics.
Have a good knowledge of mathematical, statistical and computational tools to solve financial problems with an emphasis on pricing and risk management. The ability to estimate and use financial time series models with the R software.
1. Review of basic concepts of statistical inference. Review of the linear regression model. 2. Introduction to R 3. Stochastic processes. Correlogram. Random walk. Brownian motion. 4. Stationarity. White noise. The autocorrelation function. Autoregressive Moving Averages Models. 5. Modelling of volatility with conditional heteroschedastic models: ARCH and GARCH.
1. Review of basic concepts of statistical inference. Review of the linear regression model. 2. Introduction to R. 3. Stochastic processes. Correlogram. Random walk. Brownian motion. 4. Stationarity. White noise. The autocorrelation function. Autoregressive Moving Averages Models. 5. Modelling of volatility with conditionl heteroschedastic models: ARCH and GARCH.
Gallo, G. M., Pacini, B., Metodi quantitativi per i mercati finanziari, Carocci, Roma, 2013 (VII Ristampa). Di Fonzo, T., Lisi F., Serie storiche economiche, Carocci, 2012.
Classes and recitations R tutorials
Written exam.
Additional material for exam preparation (Slides, recitations, R routines, datasets) is available on the e-learning platform at https://elearning.unich.it/ If Health Laws and University regulations allow, teaching activities, teachers office hours’, and exams may take place online (in whole or in part). For any further information and updates, please refer to the University website.
