Abstract
The India VIX represents the sentiment of traders in the Indian market, so by forecasting the future value of India VIX, we get a feel for investor sentiment in future. The objective of this study is to fit a forecasting model on India VIX using auto regressive integrated moving average (ARIMA). The model would be useful in having a glimpse of investor mood in near future. This is probably the first of its kind study based on Indian market. The motivation of this study lies not only on the pervasive agreement that the VIX is a barograph of the general marketplace sentiment as to what concerns investors' risk appetite, but also on the fact that there are many trading strategies that depend on the VIX index for speculative and hedging determinations. The study found ARIMA (1-0-2) forecasting model on VIX produces better forecasting result. We also validated the model with an out-of-sample dataset and found the model reliable.Keywords: VIX, India, Sentiment, Forecasting, ARIMAJEL Classifications: C53, G17DOI: https://doi.org/10.32479/ijefi.8046
Highlights
Volatility index or VIX captures the investors’ expectation about volatility
This paper develops a analytical model for forecasting of India VIX in the auto-regressive integrated moving average (ARIMA) framework for the period March 2009 until October 2016
Since the India VIX represents the sentiment of traders in the Indian market, so by forecasting the future value of India VIX, we get a feel for investor sentiment in future
Summary
Volatility index or VIX captures the investors’ expectation about volatility. Often termed as “investor fear gauge,” VIX is always been considered as a strong indicator of investors’ fear and emotions (Durand et al, 2011; Whaley, 2009). India Volatility Index i.e., India VIX was launched by National Stock Exchange (NSE) of India in 2009 It measures investors’ view of the market’s volatility in the immediate term. The India VIX is a good pointer of whether the market players are feeling complacent or fearful about near future It reflects the behaviour of traders from the representativeness, affect, and extrapolation bias concepts of behavioural finance (Hibbert, et al 2008). This paper develops a analytical model for forecasting of India VIX in the auto-regressive integrated moving average (ARIMA) framework for the period March 2009 until October 2016. In this context, our first contribution to the literature is methodology. To prove the robustness of our model, it is validated by using daily data from November 2016 to October 2017
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