Course Code DECS622
Course Title Risk Analytics
Course Objectives The course concerns itself with the quantification of risk, the modeling of identified risks and how to make decisions from those models.
Probability mathematics and simulation: Probability distribution equations; probability rules; statistical measures Building and running a model: Model design and scope; Building models that are efficient; most common modeling errors Basic Random Processes: Binomial process, Poisson process, Hypergeometric process, Central limit theorem, Renewal processes Fitting Distributions to data: Analysing properties of the observed data, Fitting a nonparametric distribution to the observed data, Fitting a first-order parametric distribution to the observed data, Fitting a second-order parametric distribution to the observed data Forecasting with uncertainty: Common Financial Time Series models, Autoregressive models, Markov chain models, Time series models with leading indicators, Long-term forecasting Modelling correlation and dependencies: Rank-order correlation, The Envelope method, Multiple correlation using look-up table Testing and modeling causal relationships: Types of model to analyze data, From risk factors to causes, Evaluating evidence, The limits of causal arguments, Is causal analysis essential? Checking and validating a model: Spreadsheet model errors, checking model behavior, comparing predictions against reality Insurance and finance risk analysis modeling: operational risk modeling, credit risk, credit ratings and Markov chain models, measures of risk, modeling a correlated insurance portfolio Project Risk Analysis: Cost risk analysis, scheduled risk analysis, portfolio of risks.
Course Delivery The course places a lot of emphasis on modeling and hands-on assignments. A series of class room exercises and/or assignments will enable students to model problems and use appropriate tools for the same. The entire course will have substantial emphasis on problem solving using SAS EG and/or IBM SPSS. Around 25-30% of the course is proposed to be delivered by practitioners from the industry.
Vose David, Risk Analysis: A Quantitative Guide, John Wiley & Sons; 3rd Edition
Reference Books & Additional Reading Material
Coleman Thomas S.,Quantitative Risk Management + Website: A Practical Guide to Financial Risk, John Wiley & Sons Inc LaursenGert H. N. and ThorlundJesper, Business Analytics for Managers: Taking Business Intelligence Beyond Reporting, John Wiley & Sons, I Ed, 2010 http://www.nedarc.org/tutorials/utilizingData/communicateNumbersEffectively/communi catingStatistics.html