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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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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

The Basel II Accord requires that banks and other authorized deposit‐taking institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models to measure value‐at‐risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realized losses exceed the estimated VaR. The purpose of this paper is to address the question of risk management of risk, namely VaR of VIX futures prices.

The authors examine how different risk management strategies performed before, during and after the 2008‐2009 global financial crisis (GFC).

The authors find that an aggressive strategy of choosing the supremum of the univariate model forecasts is preferred to the other alternatives, and is robust during the GFC.

The paper examines how different risk management strategies performed before, during and after the 2008‐2009 GFC, and finds that an aggressive strategy of choosing the supremum of the univariate model forecasts is preferred to the other alternatives, and is robust during the GFC.

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.

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 R_m–R_f, 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.

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 R_m–R_f 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.

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.

The purpose of this paper is to illustrate a profitable and original index options trading strategy.

The methodology is based on auto regressive integrated moving average (ARIMA) forecasting of the S&P 500 index and the strategy is tested on a large database of S&P 500 Composite index options and benchmarked to the generalized auto regressive conditional heteroscedastic (GARCH) model. The forecasts validate a set of criteria as follows: the first criterion checks if the forecasted index is greater or lower than the option strike price and the second criterion if the option premium is underpriced or overpriced. A buy or sell and hold strategy is finally implemented.

The paper demonstrates the valuable contribution of this option trading strategy when trading call and put index options. It especially demonstrates that the ARIMA forecasting method is a valid method for forecasting the S&P 500 Composite index and is superior to the GARCH model in the context of an application to index options trading.

The strategy was applied in the aftermath of the 2008 credit crisis over 60 months when the volatility index (VIX) was experiencing a downtrend. The strategy was successful with puts and calls traded on the USA market. The strategy may have a different outcome in a different economic and regional context.

This chapter examines the relationship between directors and officers (D&O) liability insurance and stock-price synchronicity by testing competing corporate governance-related monitoring and moral hazard-related agency conflict hypotheses. Testing a sample of stocks listed on the Taiwan Stock Exchange and the Taipei Exchange for 2008–2020, the empirical results of this study indicate that D&O insurance in Taiwan is negatively correlated to stock-price synchronicity. This negative relation is robust to a battery of tests, including those of fixed-effects regression models, alternative sample periods, alternative synchronicity measures, and alternative insurance measures. Further evidence indicates that this negative relationship is more pronounced among firms with greater agency problems, especially during periods of high market uncertainty. Overall, these findings support the corporate governance-related monitoring hypothesis, which posits that firms with greater D&O insurance are likelier to be characterized by better governance structures and information transparency. Additionally, their stock prices are more likely to reflect firm-specific information in a timely and precise manner, and they are more likely to have lower synchronicity with the industry and market.