Forecasting and asymmetric volatility modeling of sustainability indexes in India

Abstract

Sustainability is the new approach of corporations of the world over which is catching a lot of attention due to its divergence from the short-term approach to the long-term horizon. Sustainability indexes, that represent a set of companies for being socially responsible in terms of its corporate approach, need to be assessed in terms of forecasting the return as well as volatility of these returns. Autoregressive nature of three sustainability indexes, viz, Greenex, Carbonex and ESG index has been captured using autoregressive integrated moving averages method. The residuals of the model are subjected to generalized autoregressive conditional heteroscedasticity modeling to address volatility clustering. ARIMA results of three indices specify AR (1) for forecasting Carbonex is AR (1), MA (3) for forecasting ESG and AR (3) MA (3) for forecasting Greenex. Variances are changing as well as are a function of its past behavior, as shown by GARCH (1,1) process in the case of Carbonex and Greenex. Whereas in the case of ESG GARCH (1,1) does not explain such variance in residuals which could possibly be due to the presence of other exogenous factors in the time series. These results find place in the area of asset pricing and risk management of sustainability indexes in India. The research is based on the works of Joshi, Pandey, and Ross (2017), and it contributes to findings of Makridakis, Wheelwright, and Hyndman (1998).