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Course 2008-2009 a.y.

6144 - FINANCIAL MODELLING


CLEAM - CLES - CLEF - BIEM - CLEACC
Department of Finance

Course taught in English


Go to class group/s: 31

CLEAM (6 credits - II sem. - AI) - CLES (6 credits - II sem. - AI) - CLEF (6 credits - II sem. - AI) - BIEM (6 credits - II sem. - AI) - CLEACC (6 credits - II sem. - AI)
Course Director:
PAOLO COLLA

Classes: 31 (II sem.)
Instructors:
Class 31: 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
  • Tools: introduction to Matlab and Datastream; data analysis (descriptive statistics, return distribution, sample analysis, measures of variation)
  • Mean-variance portfolio choice: efficient frontier with and without shortselling constraints; parameter uncertainty and advanced optimization methods (resampling, bayesian and heuristic methods)
  • Bonds: duration, convexity and the term structure of interest rates
  • Stocks: CAPM, beta estimation and the security market line; introduction to APT and multi-factor models
  • Options: binomial model, lognormal distribution and Black-Scholes model
  • Value-at-risk: parametric and historic approach; introduction to Montecarlo, bootstrapping and mixed methods
  • Style analysis

Detailed Description of Assessment Methods

Written exam.

 


Textbooks
  • S. Benninga, Financial Modeling, 3rd Edition, MIT Press
  • 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.

Last change 26/05/2008 10:18