Module Directory


Module Description

Module Name
Module Code
Lecture Hrs
Practical Hrs
Time Series Analysis and Risk Modelling

Examples of time series. Objectives of time series analysis. Time series plot. Additive and multiplicative models. Decomposition. Moving Averages and Filtering. Exponential smoothing and Holt-Winters forecasting. Autocovariance function. White Noise. Stationarity. MA processes. AR processes. Random walk models. Discrete and continuous. Random walk with drift. Univariate time series models with the Markov property. Multivariate Markov model. Introduction to Box-Jenkins methods. Simple ARIMA processes. Model specification, estimation & diagnostics. Applications of time series analysis using R. Introduction to multivariate autoregressive models. Simple VAR model. Cointegration. 8 University of Mauritius 2015, 2018, 2019 Statistical distributions for modelling individual and aggregate losses. Deductibles and Retention limits. Proportional and excess of loss reinsurance. Estimation of parameters for loss distributions. Calculation of goodness of fit measures. Compound distributions: the derivation of mean, variance and coefficient of skewness, compound binomial, compound Poisson and compound negative binomial random variables. Introduction to copulas: characterisation as a multivariate distribution function, tail dependence, Gaussian copula and the Archimedean family of copulas. Introduction to extreme value theory: extreme value distributions, modelling severity of loss, measures of tail weight.
Faculty Department
FACULTY OF SOCIAL SCIENCES AND HUMANITIES Department of Economics and Statistics
Contact Details
Administrative assistant: DILMAHOMED BOCUS Bibi Swaleha
Telephone: 4037400


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