EC50162 FINANCIAL ECONOMETRICS
Lecturer
Dr Atanu Ghoshray Room:
A.Ghoshray@bath.ac.uk
3E
4.44,
Ext:
6402,
Email:
Dr Bruce Morley
Room:
B.Morley@bath.ac.uk
3E
4.30,
Ext:
6497,
Email:
Aims and Objectives of the course
The aim of this course is to provide students with the knowledge necessary to handle
modern time series techniques. Both univariate and multivariate models are
considered with and without the stationary assumption. The goals of the course are
threefold: (1) develop a comprehensive set of tools and techniques for analysing
various forms of univariate and multivariate time series and for understanding the
current literature in applied time series econometrics in the areas of Accounting and
Finance; (2) survey the current research topics in time series econometrics in the areas
of Accounting and Finance; (3) demonstrate how to use econometric software
EVIEWS for problems in time series econometrics. On this course I will always
attempt to provide simple examples that illustrate how the theoretical results are used
and applied in practice.
Organisation of the course
The theoretical and methodology to be covered in 22 lectures. Additionally there will
be 6 classes where students will apply the econometric theory using econometric
software EVIEWS.
Assessment
2 Hour exam (70%) Coursework (30%)
Submission deadline for coursework is Noon on Friday 12th May.
Content of the course
1. Stationary Univariate Models
 Difference Equations
 ARMA models and Box-Jenkins Methodology,
 Model Selection
 Forecasting Methodology.
Reading:
1
Johnston, J. and J. DiNardo (1997) Econometric Methods 4th Edition, McGraw
Hill International Editions. Chapter 7.
2
Enders, W. (1995) Applied Econometric Time Series. Wiley. Chapters 1 & 2.
3
4
Philip Hans Franses (1998) Time Series Models for Business & Economic
Forecasting Cambridge University Press. Chapter 3.
Brooks, C. (2002) Introductory Econometrics for Finance, 1st Edition,
Cambridge. Chapter 5
2. Non-stationary Univariate Models
 Trend/Cycle Decomposition,
 Deterministic and Stochastic Trend Models
 Unit Root Tests
Reading:
1
Charemza,W., and D. Deadman (1997) New Directions in Econometric
Practice. Edward Elgar Publishing Ltd. Chapter 5 pp 84 - 122.
2
Enders, W. (1995) Applied Econometric Time Series. Wiley. Chapter 4.
3
Harris, R.I.D and R. Sollis (2003) Applied Time Series Modelling and
Forecasting Wiley. Chapter 3.
4
Johnston, J. and J. DiNardo (1997) Econometric Methods 4th Edition, McGraw
Hill International Editions. Chapter 7.
5
Brooks, C. (2002) Introductory Econometrics for Finance, 1st Edition,
Cambridge. Chapter 7
6
Perron P.P. (1988) "Trends and Random Walks in Macroeconomic Time
Series: Further Evidence from a New Approach" Journal of Economic
Dynamics and Control. (12) pp 297 - 332.
7
Phillips, P.C.B. (1987) "Time Series Regression with a Unit Root"
Econometrica, (55) pp 277 - 302.
3. Stationary Multivariate Models
 Vector Autoregression (VAR) Models
 Granger Causality
 Vector Error Correction Models (VECMs)
 Testing for Cointegration using Johansen Methodology
Reading:
1
Enders, W. (1995) Applied Econometric Time Series. Wiley. Chapter 5.
2
Brooks, C. (2002) Introductory Econometrics for Finance, 1st Edition,
Cambridge. Chapter 7
3
Harris, R.I.D and R. Sollis (2003) Applied Time Series Modelling and
Forecasting Wiley. Chapter 5.
4
Judge, G.G., R.C. Hill, W.E. Griffiths, H. Lutkepohl and T.C. Lee (1988)
Introduction to the Theory and Practice of Econometrics, 2nd ed., Wiley.
Chapter 18.
5
Sims, C.A. (1980), "Macroeconomics and Reality" Econometrica, 48, pp 1 48.
6
Friedman, B. and K. Kuttner (1992) “Money, Income, Prices and Interest
Rates” American Economic Review (82) pp 472 – 492.
7
Ericsson, N.R., D.F. Hendry, G.E. Mizon (1998) "Exogeneity, Cointegration
and Economic Policy Analysis" Journal of Business and Economic Statistics.
(16) No.4, pp 370 - 387.
4. Modelling Volatility and Autoregressive Conditional Heteroskedastistic
Models (ARCH)
 Models for Volatility
 ARCH and GARCH Models
 Exponential GARCH Models
 Volatility Forecasting
Reading:
1.
Brooks, C. (2002) Introductory Econometrics for Finance, 1st Edition,
Cambridge. Chapter 8
2.
Enders, W. (1995) Applied Econometric Time Series. Wiley. Chapter 7.
3
Harris, R.I.D and R. Sollis (2003) Applied Time Series Modelling and
Forecasting Wiley. Chapter 5.
4
Chu, S-H and Freund, S. (1996) Volatility Estimation for Stock Index
Options: A GARCH Approach, Quarterly Review of Economics and Finance,
36, pp. 431-50
5
Engle, R.F. (1982) Autoregressive Conditional Heteroskedasticity with
Estimates of the Variance of United Kingdom Inflation, Econometrica 50,
pp.987-1007
6
Engle, R.F., Lilien, D.M. and Robins, R.P. (1987) Estimating Time Varying
Risk Premia in the Term Structure: The ARCH-M Model, Economtrica, 55(2)
pp. 391-407
5. Introduction to Nonlinear Models



Types of Non-Linear Model
Testing for Non-Linearity
Threshold Autoregressive (TAR) Models
Reading:
1
Brooks, C. (2002) Introductory Econometrics for Finance, 1st Edition,
Cambridge. Chapter 8, pp.437-440
2
Enders, W. and C.W.J. Granger (1998) "Unit Root Tests and Asymmetric
Adjustment With an Example Using the Term Structure of Interest Rates"
Journal of Business and Economic Statistics (16) 3 pp 304 – 311.
3
Philip Hans Franses (1998) Time Series Models for Business & Economic
Forecasting Cambridge University Press.