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

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.