[skip to content]

Centre for Financial and Management Studies (CeFiMS)

Quantitative Methods For Financial Management

Course Code:
C219|C319
Unit value:

Introduction

This course introduces some of the quantitative methods of financial management which are commonly used by financial analysts, firms' managers and individual investors. It examines techniques for the valuation of different classes of securities, analyses criteria for guiding investment decisions, considers the measurement of asset risk and return and discusses statistical techniques of forecasting. It teaches not only the relevant theoretical concepts but, in the belief that quantitative techniques can only be learned by doing, the course gives abundant practice in the manipulation of numerical material with problems and exercises. EViews software is provided for regression analysis and diagnostic procedures.

Resources

Study Guide

You will receive a looseleaf binder containing eight 'course units'. The units are carefully structured to provide the main teaching, defining and exploring the main concepts and issues, locating these within current debate and introducing and linking the further assigned readings. The unit files are also available to download from the Online Study Centre.

Textbooks

Richard Brealey, Stewart Myers and Franklin Allen (2008) Principles of Corporate Finance, Ninth Edition, McGraw-Hill, New York

Damodar N. Gujarati (2009) Essentials of Econometrics, Fourth Edition, McGraw-Hill

Econometric software

You will receive the software package for university econometrics courses, EViews 6, designed for Windows users.

Online Study Centre

You will have access to the OSC, which is a web-accessed learning environment. Via the OSC, you can communicate with your assigned academic tutor, administrators and other students on the course using discussion forums. The OSC also provides access to the course Study Guide and assignments, as well as a selection of electronic journals available on the University of London Online Library.

Objectives and learning outcomes of the course

When you have completed this course, you will be able to do the following:

  • compute the Net Present Value of an investment project and apply the main investment evaluation criteria
  • explain what is meant by probability and show how it can be applied in finance
  • discuss the main concepts of statistical inference (estimation and hypothesis testing)
  • explain and discuss how statistics can be applied to analyse relationships between financial variables
  • apply statistical regression analysis to problems in finance
  • measure the risk of a financial investment portfolio.

Scope and syllabus

Course Content
Unit 1: Financial Arithmetic and Valuation of Bonds and Stocks
  • 1.1 Introduction to Unit 1
  • 1.2 Net Present Value
  • 1.3 Annuities and Perpetuities
  • 1.4 Valuing Bonds
  • 1.5 Valuation of Common Stocks
  • 1.6 Alternative Investment Criteria
Unit 2: Statistical Concepts and Probability Theory
  • 2.1 Introduction
  • 2.2 Moments of a Probability Distribution
  • 2.3 Some Important Probability Distributions
Unit 3: Statistical Inference
  • 3.1 Introduction
  • 3.2 Estimation
  • 3.3 Hypothesis Testing
Unit 4: The Classical Linear Regression Model
  • 4.1 Introduction
  • 4.2 The Meaning of Regression Analysis
  • 4.3 The Regression Model and its Statistical Parameters
  • 4.4 Actual and Fitted Values – the Regression Line and the Error Term
  • 4.5 The Meaning of the Linearity Assumption
  • 4.6 The Method of Ordinary Least Squares (OLS)
  • 4.7 Some Examples
Unit 5: Statistical Inference in the Classical Linear Regression Model
  • 5.1 Introduction
  • 5.2 The Classical Linear Regression Model (CLRM)
  • 5.3 The Variance and the Standard Error of the Parameter Estimators
  • 5.4 Properties of the OLS estimators
  • 5.5 Confidence Intervals and Hypothesis Testing
  • 5.6 Goodness of Fit – the Correlation Coefficient r  and the Coefficient of
    Determination R ²
  • 5.7 Forecasting
Unit 6: The Multiple Linear Regression Model
  • 6.1 Introduction
  • 6.2 The Multiple Linear Regression Model
  • 6.3 OLS Estimation
  • 6.4 The Multiple Coefficient of Determination
  • 6.5 Hypothesis Testing in the Multiple Regression Model
  • 6.6 An Exercise — The Demand for Money
  • 6.7 Model Selection and the Adjusted Coefficient of Determination
  • 6.8 Choice of the Functional Form
Unit 7: Topics in the Multiple Linear Regression Model
  • 7.1 Introduction
  • 7.2 Definition of Dummy Variables
  • 7.3 Use of Dummy Variables to Compare Regressions
  • 7.4 Autocorrelation of the Error Terms
  • 7.5 Tests for Autocorrelation – the Durbin-Watson Test
  • 7.6 Estimation of Models with Autocorrelated Disturbances
  • 7.7 Dynamic Models and the Error Correction Mechanism
  • 7.8 An Example
  • 7.9 Conclusions
Unit 8: Risk Measurement and Investment Decisions
  • 8.1 Introduction
  • 8.2 Risk and Return
  • 8.3 The Capital Asset Pricing Model
  • 8.4 Arbitrage Pricing Theory (APT)
  • 8.5 Estimation of the CAPM

Method of assessment

You will complete two assignments, which will be marked by your course tutor. Assignments are each worth 15% of your total mark. You will be expected to submit your first assignment by the Tuesday of Week 5, and the second assignment at the end of the course, on the Tuesday after Week 8. Assignments are submitted and feedback given online. In addition, queries and problems can be answered through the Online Study Centre. You will also sit a three-hour examination on a specified date in October, worth 70% of your total mark. An up-to-date timetable of examinations is published in April of each year.