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Module Title |
Time Series
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Module Code |
MS447
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School |
School of Mathematical Sciences
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Online Module Resources
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| Module Co-ordinator | Professor John Appleby | Office Number | X133 |
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Level |
4
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Credit Rating |
7.5
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Pre-requisite |
None
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Co-requisite |
None
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Module Aims
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The module aims to explain fundamental concepts of a generalised linear model (GLM) and explain the situations in which such a model will apply. It also seeks to introduce the main conceptsunderlying the analysis of Time Series models. It aims to cover the syllabus of the Time Series part of the Institute and Faculty of Actuaries Core Technical subject CT6.
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Learning Outcomes
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On completion of this model students should be able to:
1. Understand the role and scope of the General Linear Model;
2. Apply time series models to problems in insurance and finance;
3. Diagnose the type of a time series from data;
4. Be able to apply Monte-Carlo simulation techniques to problems in non-life insurance mathematics.
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Indicative Time Allowances
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Hours
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Lectures |
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Tutorials |
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Laboratories |
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Seminars |
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Independent Learning Time |
112.5
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Total |
112.5
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Placements |
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Assignments |
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NOTE
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Assume that a 7.5 credit module load represents approximately 112.5 hours' work, which includes all teaching, in-course assignments, laboratory work or other specialised training and an estimated private learning time associated with the module.
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Indicative Syllabus
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Generalised Linear Model: exponential family of distributions, link function. Prediction. Parameter estimation in a GLM. Deviance and deviance residuals.
Time Series: Stationary, integrated time series. Filtering. Linear time series: AR, ARMA, ARIMA. Random walk theory applied to time series. Multivariate autoregression. Cointegration. Introductionto nonlinear time series.
Applications of Time Series: Diagnostics of time series. Applications of theory to investment variables and financial time series. Deterministic forecasts.
Monte Carlo simulation: Pseudo-random number generation. Generation of random variates. Variance reduction. Simulation of time series. Reliability of simulation.
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| Assessment | | Continuous Assessment | 25% | Examination Weight | 75% |
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Indicative Reading List
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J. Franke, W. Hardle, C. Hafner. Statistics of Financial Markets, Springer, 2003.
P. Brockwell, R. Davis. Time Series: Theory and Methods, Springer, 1991.
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Programme or List of Programmes
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| BSSA | Study Abroad (DCU Business School) |
| BSSAO | Study Abroad (DCU Business School) |
| ECSA | Study Abroad (Engineering & Computing) |
| ECSAO | Study Abroad (Engineering & Computing) |
| FM | BSc in Financial & Actuarial Mathematics |
| HMSA | Study Abroad (Humanities & Soc Science) |
| HMSAO | Study Abroad (Humanities & Soc Science) |
| SHSA | Study Abroad (Science & Health) |
| SHSAO | Study Abroad (Science & Health) |
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