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System Dynamics Modeling of Macroeconomic Determinants of Stock Market Volatility in India with Special Reference to NSEIL


Affiliations
1 Professor of Macroeconomics & Finance, Department of Applied Business Economics, Dayalbagh Educational Institute, Dayalbagh, Agra - 282 005, Uttar Pradesh, India
2 Assistant Professor of Macroeconomics & Finance, Himalayan School of Management, Swami Rama Himalayan University, Dehradun - 248 016, Uttarakhand, India

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Modeling and forecasting stock market returns and volatility is one of the key areas of present financial research because it provides a precise estimate of conditional variance process and makes a good forecast of future volatility that may help the stakeholders in obtaining efficient portfolio and accurate derivative prices of financial instruments. The system dynamics offers a useful approach for tackling environmental problems that can be conceptualized as complex, nonlinear, and multi-feedback dynamic systems. This paper aimed at developing a system dynamic model to predict stock market behavior affected due to variations in the macroeconomic indicators. It considered monthly data of stock market returns (NIFTY) of 12 years and 15 macroeconomic variables from five segments of the economy. The results of simulated model and predictions indicated that the simulated data were closer to actual data, but their behavior was linear, which was not expected in a real and dynamic economic environment.

Keywords

Causal Loop Diagram, Granger Causality, Macroeconomic Variables, Simulation and Prediction, Stock Market Returns.

JEL Classification Codes: C32, C53, G11, G17.

Paper Submission Date: May 10, 2019; Paper Sent Back for Revision: August 10, 2019; Paper Acceptance Date: September 1, 2019.

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  • System Dynamics Modeling of Macroeconomic Determinants of Stock Market Volatility in India with Special Reference to NSEIL

Abstract Views: 255  |  PDF Views: 0

Authors

Swami Prasad Saxena
Professor of Macroeconomics & Finance, Department of Applied Business Economics, Dayalbagh Educational Institute, Dayalbagh, Agra - 282 005, Uttar Pradesh, India
Sonam Bhadauriya
Assistant Professor of Macroeconomics & Finance, Himalayan School of Management, Swami Rama Himalayan University, Dehradun - 248 016, Uttarakhand, India

Abstract


Modeling and forecasting stock market returns and volatility is one of the key areas of present financial research because it provides a precise estimate of conditional variance process and makes a good forecast of future volatility that may help the stakeholders in obtaining efficient portfolio and accurate derivative prices of financial instruments. The system dynamics offers a useful approach for tackling environmental problems that can be conceptualized as complex, nonlinear, and multi-feedback dynamic systems. This paper aimed at developing a system dynamic model to predict stock market behavior affected due to variations in the macroeconomic indicators. It considered monthly data of stock market returns (NIFTY) of 12 years and 15 macroeconomic variables from five segments of the economy. The results of simulated model and predictions indicated that the simulated data were closer to actual data, but their behavior was linear, which was not expected in a real and dynamic economic environment.

Keywords


Causal Loop Diagram, Granger Causality, Macroeconomic Variables, Simulation and Prediction, Stock Market Returns.

JEL Classification Codes: C32, C53, G11, G17.

Paper Submission Date: May 10, 2019; Paper Sent Back for Revision: August 10, 2019; Paper Acceptance Date: September 1, 2019.




DOI: https://doi.org/10.17010/ijrcm%2F2019%2Fv6%2Fi3%2F148879