VIX Futures Market Research Articles

Intraday momentum in the VIX futures market

This study examines intraday momentum in the unexplored VIX futures market and verifies its existence through various empirical tests. The intraday momentum of VIX futures appears to be robust across contracts with different expirations, intraday returns with different time intervals, different trading sessions, and multiple sub-periods. We propose that the hedging demand of VIX option market makers may contribute to the intraday momentum. Our empirical evidence shows that intraday momentum persists only when the net gamma exposure of VIX options is negative and the effect weakens when European investors are away from the market, supporting our proposed explanation. Strikingly, we also find that trading strategies based on intraday momentum can generate an average annualized return of up to nearly 18%.

Dynamics of information leadership in the volatility complex with trading time changes: Evidence from VIX futures and VIX ETPs

We examine the effect of VIX futures’ new trading hours on price discovery as these causal relations have not been investigated before and are consequential for regulators and practitioners involved in the VIX futures market. Our data include VIX futures and VIX ETPs for four different periods in which trading hours were changed. Employing three different measures of information share, we find that VXX ETN leads VIX futures in 2009 and 2010, while in 2011 and 2013, the ETPs’ leadership varies depending on the exchange-traded product under consideration. Furthermore, in 2013 before the change of trading hours, the VIX futures contribute more to price discovery than they do after trading hours expansion. Less of the price discovery occurs from the exchange-traded products in the latter half of the trading period in 2010. OLS regression results of the determinants of price discovery as well as panel regression results show that the effect of volume and spread, which are the main determinants of price discovery in the prior literature, change significantly before and after futures trading hour expansions, for both VIX futures and ETPs.

Measuring Information Effects of Monetary Policy: New Evidence from the VIX Futures Market

Measuring Information Effects of Monetary Policy: New Evidence from the VIX Futures Market

Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators

Previous work has highlighted the difficulty of obtaining accurate and economically significant predictions of VIX futures prices. We show that both low prediction errors and a significant amount of profitability can be obtained by using a neural network model to predict VIX futures returns. In particular, we focus on open-to-close returns (OTCRs) and consider intraday trading strategies, taking into account non-lagged exogenous variables that closely reflect the information possessed by traders at the time when they decide to invest. The neural network model with only the most recent exogenous variables (namely, the return on the Indian BSESN index) is superior to an unconstrained specification with ten lagged and coincident regressors, which is actually a form of weak efficiency involving markets of different countries. Moreover, the neural network turns out to be more profitable than either a logistic specification or heterogeneous autoregressive models.

Forecasting returns in the VIX futures market

This paper introduces a new forecasting model for VIX futures returns. The model is structural in nature and parsimonious, and contains parameters that are relatively easy to estimate. The forecasts of next day VIX futures returns based on this model are superior to those produced by a linear forecasting model that uses the same set of predictors. Moreover, the profits to a market-timing model based on the proposed forecasts are statistically and economically significant, and are robust to both the method used for adjusting for risk and transaction costs (up to around 15 basis points). In contrast, the forecasts generated by the linear forecasting model are not.

The Market Impact of Uninformed Flows: Evidence from the VIX Futures Market

What is the market impact of predictable order flow? Leveraged exchange-traded products are useful for answering this question because they generate daily rebalancing flows whose size, sign and timing are predictable. This paper presents new evidence from the market for leveraged volatility (VIX) products. I find that the daily rebalancing imposes a substantial implicit cost on investors, but there is no evidence that the impact is driven by predatory trading. On the contrary, I show that larger and more predictable flows have smaller price impact coeffcients, and that trading ahead of rebalancing flows is not profitable after transaction costs.

Consistency between S&P500 and VIX derivatives: Insights from model‐free VIX futures pricing

AbstractThis paper studies the interdependencies between the VIX futures market and the S&P500 and VIX options markets using a model‐free pricing method for VIX futures. We show that the replication strategy for the VIX futures greatly deviates from observed prices. Limited strike ranges do not suffice to explain these deviations, whereas the options’ bid–ask spreads can explain most of it. After controlling for the spreads, we find a lead–lag structure between markets segmented by product, not by its underlying. If options markets imply higher volatility risks than VIX futures, options prices in both markets adjust and vice versa.

Determinants of price discovery in the VIX futures market

Abstract We utilize the respective information share and common factor component weight approaches of Hasbrouck (1995) and Gonzalo and Granger (1995) to examine price discovery competition between the VIX and VIX futures. Our results show that VIX futures prices play a dominant role in the overall process of price discovery. An increase in the price difference between the VIX and VIX futures, commonly referred to as the futures basis, causes a corresponding increase in the contribution to price discovery made by VIX futures. Our empirical results also show that news announcements on macro-economic issues in the United States increase the dominant role of VIX futures in the overall process of price discovery. This dominant role remains unchanged when compared to VIX exchange-traded products and the volatility indices on non-US equity exchange-traded funds.

Two Order Books are Better than One? Trading at Settlement (TAS) in VIX Futures

We examine the effects from the Trading At Settlement (TAS) introduction on VIX futures market quality. We find that the VIX futures market exhibits higher trading activity and better liquidity after the TAS introduction. VIX futures traders use the TAS limit order book to execute large transactions, and TAS helps limit order traders from being picked off by informed traders when the VIX futures price volatility is high. The TAS introduction has created a highly liquid, low‐cost, trading venue. Although the TAS introduction fragments VIX futures trading into two order books, liquidity in the regular order book is not hurt. © 2014 The Authors. Journal of Futures Markets published by Wiley Periodicals, Inc. Jrl Fut Mark 35:506–521, 2015

Two Order Books Are Better than One? Trading at Settlement (TAS) in VIX Futures

We examine the effects from the Trading At Settlement (TAS) introduction on VIX futures market quality. We find that the VIX futures market exhibits higher trading activity and better liquidity after the TAS introduction. VIX futures traders use the TAS limit order book to execute large transactions, and TAS helps limit order traders from being picked off by informed traders when the VIX futures price volatility is high. The TAS introduction has created a highly liquid, low-cost, trading venue. Although the TAS introduction fragments VIX futures trading into two order books, liquidity in the regular order book is not hurt.

The Efficiency of the VIX Futures Market:A Panel Data Approach

This study examines whether VIX futures prices are unbiased and efficient predictors of the VIX index. The particular empirical analysis differs from the usually applied tests in that it uses a panel estimation approach. Panel regression has several advantages as it offers more flexibility in modelling the efficiency of several futures contract with overlapping dataset. As a result, this methodology enables us to include all daily closing prices of VIX futures contracts that expired between May 2004 and December 2009, a total of 64 contracts. The empirical findings support the hypothesis that VIX futures are good predictors of spot VIX values. The tests show that the VIX futures with a forecast horizon up to 23 days do not incorporate a significant risk premium and thus, can be considered as unbiased and efficient estimators of the relevant spot VIX levels.

The Efficiency of the VIX Futures Market:A Panel Data Approach

The Efficiency of the VIX Futures Market:<i>A Panel Data Approach</i>

Causality in the VIX futures market

AbstractThis study examines the price‐discovery function and information efficiency of a fast growing volatility futures market: the Chicago Board of Option Exchange VIX futures market. A linear Engle–Granger cointegration test with an error correction mechanism (ECM) shows that during the full sample period, VIX futures prices lead spot VIX index, which implies that the VIX futures market has some price‐discovery function. But a modified Baek and Brock nonlinear Granger test detects bi‐directional causality between VIX and VIX futures prices, suggesting that both spot and futures prices react simultaneously to new information. Quarter‐by‐quarter investigations show that, on average, the estimated parameters are not significantly different from zero, thus providing further evidence supporting information efficiency in the VIX futures market. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark

Market Efficiency Test in the VIX Futures Market

This paper tests the random walk hypothesis and weak form market efficiency in the VIX futures market using a variety of tests. A unit root in the aggregated market price series suggests that the VIX futures market is efficient. For the individual VIX futures price series, 51 of 54 futures contracts meet the sufficient condition for an efficient market: the prices are found to follow a random walk either because there is a unit root or because the increments are not correlated. Overall, the market for VIX futures has been efficient since the first day of trading.

Are VIX futures prices predictable? An empirical investigation

Abstract This paper investigates whether volatility futures prices per se can be forecasted by studying the fast-growing VIX futures market. To this end, alternative model specifications are employed. Point and interval out-of-sample forecasts are constructed and evaluated under various statistical metrics. Next, the economic significance of the forecasts obtained is also assessed by performing trading strategies. Only weak evidence of statistically predictable patterns in the evolution of volatility futures prices is found. No trading strategy yields economically significant profits. Hence, the hypothesis that the VIX volatility futures market is informationally efficient cannot be rejected.

Is the VIX Futures Market Able to Predict the VIX Index? A Test of the Expectation Hypothesis

Is the VIX Futures Market Able to Predict the VIX Index? A Test of the Expectation Hypothesis

Is the VIX Futures Market Able to Predict the VIX Index? A Test of the Expectation Hypothesis

This article tests the expectation hypothesis by using the volatility index VIX and futures contracts written on that index. Because the VIX index is negatively correlated with the S&amp;P 500 index returns the VIX futures price should contain a negative risk premium, which is confirmed in this study. When the futures price is not adjusted with the risk premium, the expectation hypothesis is rejected at the 5% significance level for 20 of 21 forecast horizons. However when the futures price is adjusted with the risk premium, obtained from a stochastic volatility model, the expectation hypothesis cannot be rejected. Further, the results show that the risk premium adjusted futures price forecasts the direction of the VIX index well. The one day ahead forecast predicts the direction correctly 73% of the time. <b>TOPICS:</b>Mutual funds/passive investing/indexing, futures and forward contracts, statistical methods, performance measurement

Volatility Components: Evidence from VIX Futures Market

In this paper we analyze CBOE VIX futures price time series data from Mar. 2004 to Feb. 2008. We derive a new pricing framework for VIX futures that is convenient to study variance term structure dynamics. Our main contribution to existing literature is the identification of the number of factors implicit in VIX futures term structure. We find that three-factor model is ideal to characterize the variance term structure. We further construct and estimate structured two- and three-factor models to identify the components and find similar results.

VARIANCE TERM STRUCTURE AND VIX FUTURES PRICING

Using no arbitrage principle, we derive a relation between the drift term of risk-neutral dynamics for instantaneous variance and the term structure of forward variance. We show that the forward variance curve can be derived from options market. Based on the variance term structure, we derive a no arbitrage pricing model for VIX futures pricing. The model is the first no arbitrage model combining options market and VIX futures market. The model can be easily generalized to price other volatility derivatives.

Variance Term Structure and VIX Futures Pricing

Using no arbitrage principle, we derive a relationship between the drift term of risk-neutral dynamics for instantaneous variance and the term structure of forward variance curve. We show that the forward variance curve can be derived from options market. Based on the variance term structure, we derive a no arbitrage pricing model for VIX futures pricing. The model is the first no arbitrage model combining options market and VIX futures market. The model can be easily generalized to price other volatility derivatives.