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Department of Mathematicscoretheory

TIME SERIES ANALYSIS

MAT 3232

Syllabus

  • 01Introduction to Time series - Trend, Seasonality, Cyclic and Irregular variations, Time series plots, Method of semi averages, Method of Curve fitting by the principles of least squares, Conversion of Trend equation, Ratio to trend method, Ratio to moving average method, Method of link relatives.
  • 02Measurement of cyclical variations, Measurement of irregular variation.
  • 03Introduction to Univariate time series modelling and forecasting: Time series as a discrete parameter stochastic process (A strictly stationary process, A weakly stationary process, A white noise process), Moving average processes, Autoregressive processes, the partial autocorrelation function, ARMA & ARIMA processes, Box–Jenkins approach, Exponential smoothing, in-sample and out-of-sample forecasts, Forecasting with time series versus structural models, Determining whether a forecast is accurate or not.
  • 04Introduction to Multivariate time series modelling and forecasting: Vector autoregressive models - VAR with contemporaneous terms- Block significance and causality tests - VARs with exogenous variables - Impulse responses and variance decompositions - Forecasting with VARs.
  • 05Modelling long-run relationships: Stationarity and unit root testing – Cointegration - Equilibrium correction or error correction models (Engle and Granger, 1987) - Testing for and estimating cointegrating systems using the Johansen technique based on VARs.
  • 06Introduction to Financial Time Series: Basic concepts of financial markets and financial systems, Financial time series and their characteristics: Assets and Markets, Asset Returns, Distribution of returns, Basic difference between Time Series and Financial Time Series, Modelling with Financial Time Series Data (stationarity checking, cointegration, error correction model, causality etc.).
  • 07Modelling volatility and correlation: Volatility modelling, Introduction to Conditional Heteroscedastic models: ARCH and GARCH Models, Properties of ARCH and GARCH models, Limitations, Order determination and model building.

References

  • Spyros Makridakis, Steven C Wheelwright, Rob J Hyndman, Forecasting Methods and Applications, 3rd Edition, John Wiley & Sons Publication, 2005, ISBN: 978-81-265-1852-
  • Walter Enders, Applied Econometric Time Series, 3rd Edition, John Wiley & Sons Publication, 2015 ISBN: 978-81-265-4391-5.
  • Gujarati, N.D., Basic Econometrics, Fifth Edition, McGraw Hill, 2012 ISBN: 978-0-07-133345-0
  • G.S. Maddala, Introduction to Econometrics, Third Edition, John Wiley & Sons Publication, 2005, ISBN: 978-81-265-1095-5
  • Montgomery D C, Jennings C L, Kulahci M. Introduction to time series analysis and forecasting. John Wiley & Sons; 2015.
  • Brockwell P J, Davis R A. Introduction to time series and forecasting. Springer; 2016.
  • Box G E, Jenkins G M, Reinsel G C, Ljung G M. Time series analysis: forecasting and control. John Wiley & Sons; 2015.
Credits Structure
3Lecture
1Tutorial
0Practical
4Total