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Article
Publication date: 21 September 2012

Debasis Bagchi

Earlier studies establish a positive relationship between volatility index (VIX) and the stock index returns. These studies are mainly restricted to developed markets and…

Abstract

Purpose

Earlier studies establish a positive relationship between volatility index (VIX) and the stock index returns. These studies are mainly restricted to developed markets and research in this regard in emerging markets is scarce. The purpose of this paper is to fill this gap.

Design/methodology/approach

The paper studies the direct and cross‐sectional relationship of India VIX in relation to three important parameters: viz., stock beta, market to book value of equity and market capitalization. The paper constructs value weighted portfolio sorted on the basis viz., stock beta, market to book value of equity and market capitalization. The paper employs three‐factor multiple regression to find out the results.

Findings

The paper finds that India VIX has a positive and significant relationship with the returns of the value‐weighted high‐low portfolios sorted on the basis of the above parameters. The paper examines the behavior of India VIX in the presence of the above two parameters. The India VIX yields a positive and significant relationship with the above sorted portfolio returns.

Research limitations/implications

India VIX was recently introduced in November, 2007 and therefore the research is expected to suffer from small sample bias.

Practical implications

The findings suggest India VIX is a distinct risk factor capable of predicting the price discovery mechanism of the market.

Originality/value

In the rapidly expanding emerging markets the introduction of Volatility Index is a recent phenomenon. Research in this regard is scarce, particularly in the area of finding predictive ability of the Volatility Index. This research is in this direction and would definitely help the market regulators and policy‐makers with their understanding of the market and market direction. It would help them to correct the market imbalances and avert crisis, which has been recently witnessed.

Details

International Journal of Emerging Markets, vol. 7 no. 4
Type: Research Article
ISSN: 1746-8809

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Book part
Publication date: 1 May 2012

Keith Black

Because VIX has a negative correlation to the S&P 500 index and a number of hedge fund strategies, the literature has suggested that long positions in VIX can reduce the…

Abstract

Because VIX has a negative correlation to the S&P 500 index and a number of hedge fund strategies, the literature has suggested that long positions in VIX can reduce the risk and higher moment exposures of these investments. However, the VIX index is not tradeable. VIX futures are traded, but have materially different performance from the VIX index. The front month futures underperformed by over 4% per month between March 2004 and July 2009. Over this time period, the front month futures had a correlation of 0.84 to, and a volatility 60% of that of, the VIX index. The second month futures contract underperformed by almost 1% per month with a correlation of 0.76 and a standard deviation of only 40% of the VIX index. While a significant negative risk premium exists in VIX futures, the attractive positive skewness and excess kurtosis properties of the futures are similar to those of the index. Both VIX futures and the VIX index are asymmetric, rising more quickly as the S&P 500 index falls and falling more slowly as stock prices rise.

Details

Research in Finance
Type: Book
ISBN: 978-1-78052-752-9

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Article
Publication date: 23 June 2020

Xiaoying Chen and Nicholas Ray-Wang Gao

Since the introduction of VIX to measure the spot volatility in the stock market, VIX and its futures have been widely considered to be the standard of underlying investor…

Abstract

Purpose

Since the introduction of VIX to measure the spot volatility in the stock market, VIX and its futures have been widely considered to be the standard of underlying investor sentiment. This study aims to examine how the magnitude of contango or backwardation (MCB volatility risk factor) derived from VIX and VIX3M may affect the pricing of assets.

Design/methodology/approach

This paper focuses on the statistical inference of three defined MCB risk factors when cross-examined with Fama–French’s five factors: the market factor Rm–Rf, the size factor SMB (small minus big), the value factor HML (high minus low B/M), the profitability factor RMW (robust minus weak) and the investing factor CMA (conservative minus aggressive). Robustness checks are performed with the revised HML-Dev factor, as well as with daily data sets.

Findings

The inclusions of the MCB volatility risk factor, either defined as a spread of monthly VIX3M/VIX and its monthly MA(20), or as a monthly net return of VIX3M/VIX, generally enhance the explanatory power of all factors in the Fama and French’s model, in particular the market factor Rm–Rf and the value factor HML, and the investing factor CMA also displays a significant and positive correlation with the MCB risk factor. When the more in-time adjusted HML-Dev factor, suggested by Asness (2014), replaces the original HML factor, results are generally better and more intuitive, with a higher R2 for the market factor and more explanatory power with HML-Dev.

Originality/value

This paper introduces the term structure of VIX to Fama–French’s asset pricing model. The MCB risk factor identifies underlying configurations of investor sentiment. The sensitivities to this timing indicator will significantly relate to returns across individual stocks or portfolios.

Details

The Journal of Risk Finance, vol. 21 no. 3
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 2 October 2020

Rania Zghal and Ahmed Ghorbel

In this paper, our aim is to estimate the time varying correlations between Bitcoin, VIX futures and CDS indexes and to examine in what ways these assets can act as…

Abstract

Purpose

In this paper, our aim is to estimate the time varying correlations between Bitcoin, VIX futures and CDS indexes and to examine in what ways these assets can act as beneficial hedge and safe haven mechanisms, useful for facing, or attenuating, the major world equity markets related risks and volatilities.

Design/methodology/approach

Our methodology consists to model each pair equity/asset indices by bivariate symmetric and asymmetric dynamic conditional models (A) DCC to evaluate the portfolio design associated implications on both daily and weekly collected data base, with regard to the period ranging from July, 2010 to January 2018. To assess the extent to which the Bitcoin, VIX futures and sovereign CDS may stand as diversifiers, i.e. as hedging or safe haven instruments against the various stock indexes, we adopt the same method applied by Baur and Lucey (2010).

Findings

Empirical results show that the hedging and safe haven roles associated with the three hedging instruments tend to differ noticeably across time horizons and model used. The interest brought about by treating this issue is twofold. On the one hand, it should provide useful guidelines to investors through helping them opt for the most effective and beneficial strategies, whereby they could efficiently hedge the equity markets related extreme risks and volatilities. On the other hand, it is intended to highlight the applied models' specifications associated impacts.

Research limitations/implications

The interest brought about by treating this issue is twofold. On the one hand, it should provide useful guidelines to investors and financial advisors through helping them opt for the most effective and beneficial of the strategies, whereby they could efficiently hedge the equity markets related extreme risks and volatilities. On the other hand, it is intended to highlight the applied models' specifications associated impacts.

Originality/value

Study of Bitcoin can be considered as safe haven or hedge or diversifier instrument. Compare between Bitcoin, VIX and CDs.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

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Article
Publication date: 9 March 2015

Andre Mollick

The purpose of this paper is to examine what happens to the variance of individual stocks forming the Dow Jones Industrial Average (DJIA) allowing for aggregate…

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Abstract

Purpose

The purpose of this paper is to examine what happens to the variance of individual stocks forming the Dow Jones Industrial Average (DJIA) allowing for aggregate uncertainty measured by VIX, the “fear gauge index” of US options contracts. In examining each individual stock belonging to DJIA in 2011, the authors reconsider aggregate market uncertainty (VIX) as the mixing variable. In contrast to studies on the effects of VIX on the aggregate equity market, the data set used in this paper allow a further look at the proposition that market aggregate uncertainty should have varying impact on individual stock variance.

Design/methodology/approach

GARCH-M models estimate individual stock returns belonging to the DJIA in 2011 on its lags and on the ARCH-M term in the mean equation linking stock returns to the variance equation. The longest time span has 5,738 observations for most stocks under daily frequency from January 3, 1990 to December 30, 2011. The authors use one lag for the VIX2 term to address simultaneity problems in the variance equation. In order to allow for interactions between volatility and business cycles, the authors include a dummy variable for the three recessions identified by the NBER over the period.

Findings

Adding the “fear gauge” VIX index and a dummy variable for recessions to the variance equation in GARCH-M models, the VIX coefficient always increases variance and the recession dummy has mixed effects. Overall, VIX acts as expected as mixing variable. Supporting the mixture of distribution hypothesis, the impact of VIX is always positive (1.039 on market variance) and GARCH effects vanish completely for the index and almost as much for 24 stocks.

Research limitations/implications

In theory, the effects of VIX on stock variance should be positive and statistically significant, together with reductions of GARCH persistence. The authors find this to be the case for the aggregate stock market and for 24 out of its 29 DJIA stocks. The authors leave for further work extensions to estimating the variance equation for companies very exposed to idiosyncratic changes, such as oil price fluctuations or stock buybacks. The implication of this research for the academic or financial community relies on the estimation of VIX effects on individual stock variance, controlling for business cycles.

Originality/value

Due to its benchmark in equities, stocks in the Dow Jones Industrials make it a very interesting case study. This paper reconsiders the aggregate uncertainty hypothesis for two main reasons. First, the financial press and traders keep a very close track on the daily evolution of VIX. Second, recent research emphasizes the formal predictive power of VIX in US stock markets. For the variance equation, existing works report positive values for the VIX-coefficient on the S&P 500 index but they have not examined individual stocks as the authors do in this paper.

Details

Managerial Finance, vol. 41 no. 3
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 19 January 2015

Thomas Kokholm and Martin Stisen

This paper studies the performance of commonly employed stochastic volatility and jump models in the consistent pricing of The CBOE Volatility Index (VIX) and The S&P 500…

Abstract

Purpose

This paper studies the performance of commonly employed stochastic volatility and jump models in the consistent pricing of The CBOE Volatility Index (VIX) and The S&P 500 Index (SPX) options. With the existence of active markets for volatility derivatives and options on the underlying instrument, the need for models that are able to price these markets consistently has increased. Although pricing formulas for VIX and vanilla options are now available for commonly used models exhibiting stochastic volatility and/or jumps, it remains to be shown whether these are able to price both markets consistently. This paper fills this vacuum.

Design/methodology/approach

In particular, the Heston model, the Heston model with jumps in returns and the Heston model with simultaneous jumps in returns and variance (SVJJ) are jointly calibrated to market quotes on SPX and VIX options together with VIX futures.

Findings

The full flexibility of having jumps in both returns and volatility added to a stochastic volatility model is essential. Moreover, we find that the SVJJ model with the Feller condition imposed and calibrated jointly to SPX and VIX options fits both markets poorly. Relaxing the Feller condition in the calibration improves the performance considerably. Still, the fit is not satisfactory, and we conclude that one needs more flexibility in the model to jointly fit both option markets.

Originality/value

Compared to existing literature, we derive numerically simpler VIX option and futures pricing formulas in the case of the SVJ model. Moreover, the paper is the first to study the pricing performance of three widely used models to SPX options and VIX derivatives.

Details

The Journal of Risk Finance, vol. 16 no. 1
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 31 October 2018

Philippe Bélanger and Marc-André Picard

Previous studies have shown the VIX futures tend to roll-down the term structure and converge towards the spot as they grow closer to maturity. The purpose of this paper…

Abstract

Purpose

Previous studies have shown the VIX futures tend to roll-down the term structure and converge towards the spot as they grow closer to maturity. The purpose of this paper is to propose an approach to improve the volatility index fear factor-level (VIX-level) prediction.

Design/methodology/approach

First, the authors use a forward-looking technique, the Heath–Jarrow–Morton (HJM) no-arbitrage framework to capture the convergence of the futures contract towards the spot. Second, the authors use principal component analysis (PCA) to reduce dimensionality and save substantial computational time. Third, the authors validate the model with selected VIX futures maturities and test on value-at-risk (VAR) computations.

Findings

The authors show that the use of multiple factors has a significant impact on the simulated VIX futures distribution, as well as the computations of their VAR (gain in accuracy and computing time). This impact becomes much more compelling when analysing a portfolio of VIX futures of multiple maturities.

Research limitations/implications

The authors’ approach assumes the variance to be stationary and ignores the volatility smile. Nevertheless, they offer suggestions for future research.

Practical implications

The VIX-level prediction (the fear factor) is of paramount importance for market makers and participants, as there is no way to replicate the underlying asset of VIX futures. The authors propose a procedure that provides efficiency to both pricing and risk management.

Originality/value

This paper is the first to apply a forward-looking method by way of a HJM framework combined with PCA to VIX-level prediction in a portfolio context.

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Article
Publication date: 11 January 2016

Imlak Shaikh and Puja Padhi

The purpose of this paper is to analyze the asymmetric contemporaneous relationship between implied volatility index (India VIX) and Equity Index (S & P CNX Nifty…

Abstract

Purpose

The purpose of this paper is to analyze the asymmetric contemporaneous relationship between implied volatility index (India VIX) and Equity Index (S & P CNX Nifty Index). In addition, the study also analyzes the seasonality of implied volatility index in the form of day-of-the-week effects and option expiration cycle.

Design/methodology/approach

This study employs simple OLS estimation to analyze the contemporaneous relationship among the volatility index and stock index. In order to obtain robust results, the analysis has been presented for the calendar years and sub-periods. Moreover, the international evidenced presented for other Asian markets (Japan and China).

Findings

The empirical evidences reveal a strong persistence of asymmetry among the India VIX and Nifty stock index, at the same time the magnitude of asymmetry is not identical. The results show that the changes in India VIX occur bigger for the negative return shocks than the positive returns shocks. The similar kinds of results are recorded for the Japan and China volatility index. Particularly, the analysis also supports that India VIX holds seasonality, on the market opening VIX observed to be at its high level, and on the subsequent days it remains low. The results on the options expiration unfold the facts that India VIX remains more normal on the day of expiration.

Practical implications

The asymmetric relation and seasonal patterns are quite useful to the volatility traders to price the financial assets when market trades in the high- and low-volatility periods.

Originality/value

There is a lack of studies of this kind in the context of emerging markets like India; hence, this is an attempt in this direction. The study provides an insight to the NSE to launch some derivative products (i.e. F & Os) on India VIX that can generate more liquidity in the market for the volatility traders.

Details

Journal of Economic Studies, vol. 43 no. 1
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 10 July 2019

Xiaoyu Wang, Jia Zhai, Dejun Xie and Jingjing Jiang

The purpose of this paper is to investigate the impact of Federal Open Market Committee (FOMC) meetings and the changes of the target rates on stock market uncertainty.

Abstract

Purpose

The purpose of this paper is to investigate the impact of Federal Open Market Committee (FOMC) meetings and the changes of the target rates on stock market uncertainty.

Design/methodology/approach

Multivariate regression analysis is applied to the historical data of VIX, FOMC meetings and target rates. Subtle relations are revealed by further categorizing the FOMC meetings into being scheduled and unscheduled and distinguishing the signs of the changes in VIX and target rates. CPI and the prime rate are used for robustness test.

Findings

The authors first examine the relation between FOMC meetings and target surprises; the results indicate that unscheduled FOMC meetings heavily impact the target surprises. Then, the authors investigate the relation between FOMC meetings and VIX changes; the results show that both unscheduled and scheduled FOMC meetings impact VIX, where the impacts of scheduled FOMC meetings are more substantial. The authors also analyze the responses of VIX to the target surprises, and the results reveal that there is an asymmetric effect of target surprises on VIX, where the influences of the scheduled positive target surprises are more significant. Finally, by examining the relation between the FOMC meeting and the risk-neutral density of the VIX option, the authors conclude that both KURT and SKEW are more affected by unscheduled FOMC meetings.

Originality/value

Deeper dimensions of the relations between VIX, FOMC meetings and target rates are analyzed and more insightful understandings of such relations are gained.

Details

China Finance Review International, vol. 10 no. 1
Type: Research Article
ISSN: 2044-1398

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Book part
Publication date: 26 February 2016

John Mark Caruana

This chapter aims to find an optimal way to hedge foreign exchange exposures on three main currency pairs being the EURUSD, EURGBP and EURJPY. Furthermore, it analyses the…

Abstract

Purpose

This chapter aims to find an optimal way to hedge foreign exchange exposures on three main currency pairs being the EURUSD, EURGBP and EURJPY. Furthermore, it analyses the risk level of each portfolio together with its kurtosis level. This chapter also looks into the relationship between the EURUSD portfolios and the VIX level.

Methodology/approach

This study is based on a back-testing analysis over a period of seven years starting in January 2007 and ending in December 2014. Two main Foreign Exchange Premium-Free strategies were structured using the Bloomberg Terminal. These were the ‘At-Expiry Forward Extra’ and the ‘Window Forward Extra’. Portfolios were created using FX options strategies, FX spot and FX forwards. The EURUSD portfolios were also analysed and compared with the VIX level in order to see whether volatility has a direct effect on the outcome of the strategies. The statistical significance of the difference between returns of portfolios was analysed using a paired sample t-test. Finally, the histogram and distribution curve of each portfolio were created and plotted in order to provide a more visual analysis of returns.

Findings

It was found that the optimal strategies in all cases were the FX option strategies. The portfolios’ risk was analysed and indicated that optimal portfolios do not necessarily derive the lowest risk. It was also found that with a high VIX level, the forward contract was the most beneficial whilst the option strategy benefited from a low VIX level. When testing for statistical significance between returns of different portfolios, in most cases, the difference in returns between portfolios resulted to be statistically insignificant. Although some similarities were noticed in distribution curves, these differed from the normal distribution. When analysing the kurtosis levels, it is found that such levels differed from that of a normal distribution which has a kurtosis level of 3. Interpretation of such histograms, distribution curves and the kurtosis analysis was explained.

Details

Contemporary Issues in Bank Financial Management
Type: Book
ISBN: 978-1-78635-000-8

Keywords

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