COURSE DESCRIPTION:
Overview
The past twenty years have seen extraordinary growth in the use of quantitative methods
in financial markets. Finance professionals now routinely use sophisticated techniques in
portfolio management, proprietary trading and risk management. In India, research based
organizations like GE Capital, American Express, SAS etc are always on look out for
candidates with an understanding of modeling techniques. Good knowledge of finance
coupled with training in financial models and econometrics is considered a definite bonus
in the job market.
Course Objective
The intended audiences are the MBA students who require a broad knowledge of modern
econometric techniques commonly employed in the finance literature. This course would
be of interest to students who are looking for a career in the Analytics division of an
MNC.
Additionally, this course has been designed with to give students hands-on experience in
two econometric packages – EViews & SAS Forecasting Module. The assignments and
projects focus on the application of the techniques on core financial topics.
Learning Outcomes
This course enables students to model financial data efficiently for forecasting purposes
which will be of immense interest to those entering the finance profession especially on
the research side. On completing the course, students will have:
Learned the basic econometric tools & techniques relevant for financial modelling
Acquired an ability to model financial data independently
Developed an aptitude for dealing with forecasting models
Pedagogy
The course will be delivered through a mix of lectures and tutorials (lab sessions).
Learning is expected to happen through assignments and project. Peer group interaction
is also a critical aspect in this course.
Pre-requisites for this Course
Mathematics
Matrix Algebra
Calculus – Differentiation & Integration
Statistics
Probability theory
Introductory Bayesian Analysis
Multivariate Analysis
ANOVA
Finance
Cost of Capital
Mean-Variance Portfolio Theory
Capital Asset Pricing Model (CAPM)
Arbitrage Pricing Theory (APT)
Market Efficiency (EMH)
Option Pricing Theory
Term Structure of Interest Rates
Yield Curve Analysis
Performance Evaluation of Mutual Funds
International Financial Management
Exchange Rate Concepts
Proficiency with functions and macros in MS Excel
Understanding of MS Access (or any RDBMS) & VB (preferably)
MODULE – ONE
Concepts in Finance – An Overview of Recent Developments (3 sessions)
1. Asset Pricing Models
2. Term Structure of Interest Rates
3. Performance Evaluation of Mutual Funds
4. Exchange Rate Forecasting
MODULE – TWO
Overview of CLRM (7 sessions)
1. Introduction to Econometrics, Financial Economics and Financial Econometrics
2. Types of Data
3. Classical Linear Regression Model – Assumptions, Estimation & Inference
4. Implications of Multicollinearity, Heteroskedasticity and Autocorrelation
5. Regression with Categorical / Qualitative Variables
MODULE – TWO
Basic Concepts (6 sessions)
1. Components of a Time Series
2. Deterministic and Stochastic Trends
3. Random Walk Models
4. Stationarity & Unit Root Testing
5. Cointegration – Applications in finance
MODULE – THREE
Univariate Time Series Analysis (5 sessions)
1. Autoregressive processes
2. Moving Average processes
3. ACF & PACF
4. Building ARIMA models – Box Jenkins Methodology
MODULE – FOUR
Multivariate Time Series Analysis (9 sessions)
1. Granger Causality
2. VAR – Vector Auto Regression
3. Modelling Lead-lag relationship
4. Introduction to Volatility Modelling using ARCH / GARCH
MODULE – FIVE
Panel Data Econometrics (3 sessions)
1. Difference between Pooled regression and Panel data regression
2. Issues with Panel Data
3. The Fixed Effects Model
4. The Random Effects Model
