5349 - FINANCIAL MODELLING (CEU)
DIEM
Department of Finance
Course taught in English
Insegnamento riservato agli studenti CEU
PAOLO COLLA
Course Objectives
The course provides the technical skills for implementing financial models with Excel and Matlab using real data obtained from Datastream. Students are equipped with the basic operational tools to understand financial markets and are able to employ the modelling abilities developed via sample applications to build their own models. Coursework mainly focuses on functions already embedded in the worksheet as well as on procedures designed to solve specific problems. The course concentrates on the application of several theoretical models for financial valuation, optimal portfolio choice and financial risk evaluation.
Course Content Summary
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Tools: introduction to Matlab and Datastream; data analysis (descriptive statistics, return distribution, sample analysis, measures of variation)
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Mean-variance portfolio choice: efficient frontier with and without shortselling constraints; parameter uncertainty and advanced optimization methods (resampling, bayesian and heuristic methods)
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Bonds: duration, convexity and the term structure of interest rates
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Stocks: CAPM, beta estimation and the security market line; introduction to APT and multi-factor models
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Options: binomial model, lognormal distribution and Black-Scholes model
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Value-at-risk: parametric and historic approach; introduction to Montecarlo, bootstrapping and mixed methods
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Style analysis
Detailed Description of Assessment Methods
Written exam.Textbooks
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S. Benninga, Financial Modeling, 3rd Edition, MIT Press
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Further selected readings are made available via Course Reserve
Prerequisites
An intermediate level of Excel knowledge is assumed, without any previous exposure to programming. Students with a basic knowledge are expected to fill their gaps before starting the course. Several Excel user manuals can come handy, for instance G. Hart-Davis, How to do everything in Microsoft Office Excel 2003, McGraw Hill. No previous exposure to either Matlab or Datastream is required: students will be introduced to both of them in the first part of the course.