Abstract
The Chicago Board Options Exchange Volatility Index (VIX) is considered by many market participants as a common measure of market risk and investors’ sentiment, representing the market’s expectation of the 30-day-ahead looking implied volatility obtained from real-time prices of options on the S&P 500 index. While smaller deviations between implied and realized volatility are a well-known stylized fact of financial markets, large, time-varying differences are also frequently observed throughout the day. Furthermore, substantial deviations between the VIX and its futures might lead to arbitrage opportunities on the VIX market. Arbitrage is hard to exploit as the potential strategy to exploit it requires buying several hundred, mostly illiquid, out-of-the-money (put and call) options on the S&P 500 index. This paper discusses a novel approach to predicting the VIX on an intraday scale by using just a subset of the most liquid options. To the best of the authors’ knowledge, this the first paper, that describes a new methodology on how to predict the VIX (to potentially exploit arbitrage opportunities using VIX futures) using most recently developed machine learning models to intraday data of S&P 500 options and the VIX. The presented results are supposed to shed more light on the underlying dynamics in the options markets, help other investors to better understand the market and support regulators to investigate market inefficiencies.
Highlights
The Volatility Index (VIX) index has been subject to claims of manipulation over the last few years, see, e.g., Griffin and Shams (2017)
To replicate the VIX using the official Chicago Board Options Exchange (CBOE) formula, one needs about 350 out-ofthe money options at any point in time
It has been shown that ten options are sufficient when used as input features for a neural network with one long shortterm memory (LSTM) layer, to predict the VIX with an accuracy of 61.2%, which is slightly larger than using a random forest approach
Summary
The VIX index has been subject to claims of manipulation over the last few years, see, e.g., Griffin and Shams (2017). The VIX sheds light on how investors “feel” about the market, its nickname, the “fear gauge.” Its design is such that it tries to approximate the 30-day implied volatility of at-the-money options on the S&P 500. By just using a small subset of all options for the VIX calculation and knowing their weights, we can predict the VIX with high accuracy over the four quoted time-intervals which are 60 s, beating the trivial approach of using the last observation as a prediction for the future value As another application, knowing the weights for combining the current prices of liquid calls and puts to get a 60 s-ahead forecast of the VIX could be useful for approximately hedging a variance swap entered into 60 s later, since the square of the VIX can be seen as the fair strike of a variance swap.
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