TSM-EMBA-BA-19

TSM-EMBA-BA-19
MBA(Exe.)-BA-2019-20: Term-III

Time Series Analysis

Prof. Ameet Kumar Banerjee
Credit-3
Executive MBA-Business Analytics-2019-20

1. Course description

Time Series Analysis (Master level) is an elective course designed for Master students of “Business Management” Program. This is an intermediate level course of Time Series Theory for the students majorly specializing in the field of Finance, Economics, Data Analytics and Banking. The prerequisites for this course require foundation knowledge of Statistics, Econometrics, and computer- information systems. The focus of the course is on the methods and application of time series analysis. Conclusions and proofs of some basic formulas and models are discussed enabling the students to understand the economic sense of the principles behind the theory. The main stress is made on the economic interpretation and applications of considered various time series models.

2. Learning objectives:

The students will be made acquainted with the concepts of Time Series theory and methods of analysis which will be used to examine different types of data set, analyze and interpret results and present conclusions. This course, is intended for students to master traditional methods of Time Series analysis, working with time series data. Further, students should be able understand the differences between cross-sections and time series, and those specific economic problems, which occur while working with data of these types.

3. Learning outcomes

Students can skillfully analyze and model stochastic processes of

ARMA

(

), get acquainted with co-integration and error correction models, autoregressive models with distributed lags, understand their application in finance and economics. Given methods and models should be mastered by practice using real economic data and modern economic software like Econometric views (E Views) and R.

4. Methodology

The following methods and forms would be adopted for the course:

- Lectures;

- practices in computer;

- self-study in computer class (doing home assignments using R and Econometric views, work with financial data, appliances in Internet);

In total the course includes 20 sessions of the lectures and practices classes.

5. Main reading:
1. Enders W. Applied Econometric Time Series. John Wiley & Sons Indian Edition.
2. Tsay R. Analysis of Financial Time Series. John Wiley & Sons Indian Edition.
3. Mills, T.C. The Econometric Modelling of Financial Time Series. Cambridge University Press.
6. Session - Schedule

Session 1 & 2

Introduction to Time Series Analysis. Nature of time series data, properties and difference equations. Stochastic process: Stationary versus Non-stationary Stochastic Process.

Session 3 & 4: Tests of Stationarity: Correlogram, Unit Root Tests. Random Walk Models.

Session 5, 6 & 7: Modeling Volatility: • Time varying volatility model: ARCH, GARCH models and its extension •

Session 8: Additional properties of Forecasting volatility and Other Volatility models.

Session 9 & 10: Multivariate Times Series Analysis • Vector Autoregression Model (VAR): Estimation and Identification, •

Session 11 & 12: Variance decomposition and Impulse response functions, • Causality applying Granger Causality Tests and VAR model, • Forecasting using a VAR model.

Session 13, 14 & 15: Modeling Short Run and Long Run Relationships • Cointegration: Cointegration and common trends, • Tests of cointegration: Engle-Granger Two Step Procedure, the Johansen-Juselius Multivariate Test,

Session 16 & 17: Error Correction Models • Estimation and interpretation off an Error Correction Model • Forecasting Using an Error Correction Model.

Session 18 & 19: Modeling Non-linear Time Series • Simple nonlinear models • Threshold Autoregressive Model (TAR), The Smooth Transition Autoregressive (STAR) model etc. • Unit roots and Nonlinearity etc.

Session 20: Discussion on finer issues.

7. Evaluation Process

Class participation: 20%

Quiz 1: 20%

Quiz 2: 20%

End-term: 40%

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Created By: Alora Kar on 11/25/2019 at 04:08 PM
Category: MBA(Exe.)BA-2019-20 T-III Doctype: Document

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