TERM - 4
SIMULATION ASSIGNMENT - VII
MODELLING FINANCIAL MARKETS

Simulation Training Objective:

• To expose students to advanced techniques applied in modeling financial time series data.

Simulation Training Outline:

1. Univariate Time Series Modeling and Forecasting: Introduction, ARMA process, Building ARMA models: the Box Jenkins approach, exponential smoothing, Forecasting in econometrics.
2. Multivariate Models: Introduction, Simultaneous equations in finance, estimation procedures for simultaneous Equations, Hausman test, vector auto regressive models, Block significance and causality test, Impulse responses and variance decompositions.
3. Modeling Long Run Relationships in Finance: Introduction, stationarity and unit root testing, cointegration, tests for cointegration, lead - lag and long term relationships between spot and future markets.
4. Modeling Volatility: Introduction, models for volatility, ARCH models, GARCH models, asymmetric GARCH models, uses of GARCH type models in volatility forecasting, multivariate GARCH models.
5. Switching models: Introduction, Seasonalities in financial markets, modeling seasonality in financial data, estimating simple piecewise linear function – Markov switching models, threshold autoregressive models, regime switching models and forecasting.

Suggested Readings:

1. Chris Brooks - Introductory Econometrics for Finance - Cambridge University Press, 2/e
2. Ruey S. Tsay - Analysis of Financial Time Series - Wiley 2/e 2005
3. Terence C Mills - The Econometric Modeling of Financial Time Series, second edition - Cambridge University Press, 1999
4. Campbell, J Y., LO, A W and MacKinlay, A C - The Econometrics of Financial Markets - Princeton University Press, 1997