The euro and pound volatility dynamics: An investigation from conditional jump process

This paper investigates the variations of the volatility of euro and pound after the introduction of euro. A GARJI model is employed to analyze the impact of the news arrivals on the exchange rate volatility. The results are robust to the data-splitting schemes and indicate: (1) the conditional variance of euro is larger than that of pound. (2) The stability of euro exchange rates has made progress in recent years, which is accomplished by the decreases in the jump innovations. This paper supports the arguments on the determinants of exchange rate stability claimed by Mundell (1998) and Mussa (2000).     

The world price of jump and volatility risk

We study international integration of markets for jump and volatility risk, using index option data for the main global markets. To explain the cross-section of expected option returns we focus on return-based multi-factor models. For each market separately, we provide evidence that volatility and jump risk are priced risk factors. There is little evidence, however, of global unconditional pricing of these risks. We show that UK and US option markets have become increasingly interrelated, and using conditional pricing models generates some evidence of international pricing. Finally, the benefits of diversifying jump and volatility risk internationally are substantial, but declining.     

Macroeconomic fundamentals,jump dynamics and expected volatility

In this paper, we develop a new volatility model capturing the effects of macroeconomic variables and jump dynamics on the stock volatility. The proposed GARCH-Jump-MIDAS model is applied to the S&P 500 index. Our in-sample results indicate that macroeconomic activities have important impacts on aggregate market volatility. Out-of-sample evidence suggests that our model with macroeconomic variables significantly outperform a wide range of competitors including the original GARCH(1,1), GARCH-MIDAS and GJR-A-MIDAS models. The volatility timing results also show that the information from jumps and macroeconomic activity is helpful for improving the portfolio performance.     

Trading volume,time-varying conditional volatility,and asymmetric volatility spillover in the Saudi stock market

Despite the well known importance of volatility–volume relationship, there is a paucity of research on this topic in emerging markets. We attempt to partially fill this gap by investigating volatility–volume relationship in the most important exchange market in the Middle East. We test the effect of trading volume on the persistence of the time-varying conditional volatility of returns in the Saudi stock market. Overall our results support the mixture of distribution hypothesis at the firm level. We also use two different proxies for information arrival, intra-day volatility, and overnight indicators. We find that these are good proxies for information and are important as contemporaneous volume in explaining conditional volatility. We also test for the volatility spillover direction between large- and small-cap portfolios. Our results show that the spillover effect is larger and statistically significant from large to small companies.     

The cross-sectional relation between conditional heteroskedasticity,the implied volatility smile,and the variance risk premium

This paper estimates how the shape of the implied volatility smile and the size of the variance risk premium relate to parameters of GARCH-type time-series models measuring how conditional volatility responds to return shocks. Markets in which return shocks lead to large increases in conditional volatility tend to have larger variance risk premia than markets in which the impact on conditional volatility is slight. Markets in which negative (positive) return shocks lead to larger increases in future volatility than positive (negative) return shocks tend to have downward (upward) sloping implied volatility smiles. Also, differences in how volatility responds to return shocks as measured by GARCH-type models explain much, but not all, of the variations in excess kurtosis and multi-period skewness across different markets.     

A jump diffusion model for VIX volatility options and futures

Volatility indices are becoming increasingly popular as a measure of market uncertainty and as a new asset class for developing derivative instruments. Although jumps are widely considered as a salient feature of volatility, their implications for pricing volatility options and futures are not yet fully understood. This paper provides evidence indicating that the time series behaviour of the VIX index is well approximated by a mean reverting logarithmic diffusion with jumps. This process is capable of capturing stylized facts of VIX dynamics such as fast mean-reversion at higher levels, level effects of volatility and large upward movements during times of market stress. Based on the empirical results, we provide closed-form valuation models for European options written on the spot and forward VIX, respectively.     

Robust estimation of intraweek periodicity in volatility and jump detection

Opening, lunch and closing of financial markets induce a periodic component in the volatility of high-frequency returns. We show that price jumps cause a large bias in the classical periodicity estimators and propose robust alternatives. We find that accounting for periodicity greatly improves the accuracy of intraday jump detection methods. It increases the power to detect the relatively small jumps occurring at times for which volatility is periodically low and reduces the number of spurious jump detections at times of periodically high volatility. We use the series of detected jumps to estimate robustly the long memory parameter of the squared EUR/USD, GBP/USD and YEN/USD returns.     

Surprising information,the MDH,and the relationship between volatility and trading volume

This paper explains the concept of surprising information with a sign effect. Employing the mixture of distribution hypothesis (MDH), this paper also theoretically demonstrates that the effect of surprising information on the relationship between volatility and trading volume contrasts with that of general information, and proposes a method to detect the unobservable surprising information. Furthermore, incorporating surprising information with a sign effect, this paper suggests an information-type switching GARCH-V model. Strong evidence in favor of the model specification over the standard GARCH models is based on empirical application with high frequency data, supporting the dependence of the relationship between volatility and trading volume on the type of information.     

Modelling return and conditional volatility exposures in global stock markets

This article empirically investigates the exposure of country-level conditional stock return volatilities to conditional global stock return volatility. It provides evidence that conditional stock market return volatilities have a contemporaneous association with global return volatilities. While all the countries included in the study exhibited a significant and positive relationship to global volatility, emerging market volatility exposures were considerably higher than developed market exposures. JEL Classification G12     

Correlated implied volatility with jump and cross section of stock returns

I derive the option‐implied volatility allowing for nonzero correlation between price jump and diffusive risk to examine the information content of implied diffusive, jump risks and their implied covariance in the cross‐sectional variation of future returns. This study documents a strong predictive power of realized volatility and correlated implied volatility spread (RV ? IV_C) in the cross section of stock returns. The difference of realized volatility with the implied diffusive volatility (RV ? σ_C), jump risk (RV ? γ_C) and covariance (RV ? ICov) can forecast future returns. These RV ? σ_C and RV ? γ_C anomalies are robustly persistent even after controlling for market, size, book‐to‐market value, momentum and liquidity factors.     

Empirical study on relationship between persistence-free trading volume and stock return volatility

A large body of literature finds that the unexpected trading volume, which is obtained by filtering out time trend, autocorrelation, can be used as a proxy of the information flow and can explain the heteroskedasticity of stock return in some degrees. In this paper, we find that the heteroskedasticity exists in the unexpected trading volume, and we further generate a new information proxy by filtering out the heteroskedasticity from the unexpected trading volume, termed “persistence-free trading volume”. Our empirical results indicate that the persistence-free trading volume can explain the heteroskedasticity of the return better than the unexpected trading volume; moreover, the explanatory power of the persistence-free trading volume is positively related to market maturity.     

The jump component of S&P 500 volatility and the VIX index

Much research has investigated the differences between option implied volatilities and econometric model-based forecasts. Implied volatility is a market determined forecast, in contrast to model-based forecasts that employ some degree of smoothing of past volatility to generate forecasts. Implied volatility has the potential to reflect information that a model-based forecast could not. This paper considers two issues relating to the informational content of the S&P 500 VIX implied volatility index. First, whether it subsumes information on how historical jump activity contributed to the price volatility, followed by whether the VIX reflects any incremental information pertaining to future jump activity relative to model-based forecasts. It is found that the VIX index both subsumes information relating to past jump contributions to total volatility and reflects incremental information pertaining to future jump activity. This issue has not been examined previously and expands our understanding of how option markets form their volatility forecasts.     

An empirical analysis of the dynamic relationship between mutual fund flow and market return volatility

We study the dynamic relation between aggregate mutual fund flow and market-wide volatility. Using daily flow data and a VAR approach, we find that market volatility is negatively related to concurrent and lagged flow. A structural VAR impulse response analysis suggests that shock in flow has a negative impact on market volatility: An inflow (outflow) shock predicts a decline (an increase) in volatility. From the perspective of volatility–flow relation, we find evidence of volatility timing for recent period of 1998–2003. Finally, we document a differential impact of daily inflow versus outflow on intraday volatility. The relation between intraday volatility and inflow (outflow) becomes weaker (stronger) from morning to afternoon.     

The relationship between implied and realized volatility: evidence from the Australian stock index option market

This paper examines the relationship between the volatility implied in option prices and the subsequently realized volatility by using the S&P/ASX 200 index options (XJO) traded on the Australian Stock Exchange (ASX) during a period of 5 years. Unlike stock index options such as the S&P 100 index options in the US market, the S&P/ASX 200 index options are traded infrequently and in low volumes, and have a long maturity cycle. Thus an errors-in-variables problem for measurement of implied volatility is more likely to exist. After accounting for this problem by instrumental variable method, it is found that both call and put implied volatilities are superior to historical volatility in forecasting future realized volatility. Moreover, implied call volatility is nearly an unbiased forecast of future volatility.

Empirical relationship between macroeconomic volatility and stock returns: Evidence from Latin American markets

Emerging market stock returns have been characterized as having higher volatility than returns in the more developed markets. But previous studies give little attention to the fundamentals driving the reported levels of volatility. This paper investigates whether dynamics in key macroeconomic indicators like exchange rates, interest rates, industrial production and money supply in four Latin American countries significantly explain market returns. The MSCI world index and the U.S. 3-month T-bill yield are also included to proxy the effects of global variables. Using a six-variable vector autoregressive (VAR) model, the study finds that the global factors are consistently significant in explaining returns in all the markets. The country variables are found to impact the markets at varying significance and magnitudes. These findings may have important implications for decision-making by investors and national policymakers.     

Macroeconomic news, announcements, and stock market jump intensity dynamics

This paper examines the effect of macroeconomic releases on stock market volatility through a Poisson-Gaussian-GARCH process with time-varying jump intensity, which is allowed to respond to such information. The day of the announcement, per se, is found to have little impact on jump intensities. Employment releases are an exception. However, when macroeconomic surprises are considered, inflation shocks show persistent effects while monetary policy and employment shocks reveal only short-lived effects. Also, the jump intensity responds asymmetrically to macroeconomic shocks. Evidence on macroeconomic variables relevance in explaining jump dynamics and improving volatility forecasts on event days is provided.     

Combining conditional volatility forecasts using neural networks: an application to the EMS exchange rates

The present paper examines the out-of-sample forecasting performance of four conditional volatility models applied to the European Monetary System (EMS) exchange rates. In order to provide improved volatility forecasts, the four models’ forecasts are combined through simple averaging, an ordinary least squares model, and an artificial neural network. The results support the EGARCH specification especially after the foreign exchange crisis of August 1993. The superiority of the EGARCH model is consistent with the nature of the EMS as a managed float regime. The ANN model performed better during the August 1993 crisis especially in terms of root mean absolute prediction error.     

On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility

In this paper we use Malliavin calculus techniques to obtain an expression for the short-time behavior of the at-the-money implied volatility skew for a generalization of the Bates model, where the volatility does not need to be a diffusion or a Markov process, as the examples in Sect. 7 show. This expression depends on the derivative of the volatility in the sense of Malliavin calculus. E. Alòs’ research is supported by grants MEC FEDER MTM 2006 06427 and SEJ2006-13537. J.A. León’s research is partially supported by the CONACyT grant 45684-F. J. Vives’ research is supported by grant MEC FEDER MTM 2006 06427.     

On the systematic volatility of unpriced earnings

Some important puzzles in macro finance can be resolved in a model featuring systematically varying volatility of unpriced shocks to firms? earnings. In the data, the correlation between corporate debt and stock market valuations is low. The model accounts for this via the opposing effect of unpriced earnings risk on levered debt and equity prices. The model also explains the low (or nonexistent) risk-reward relation for the market portfolio of levered equity via the opposing effects of unpriced and priced uncertainty (both components of stock volatility) on the levered equity risk premium. Versions of the model calibrated to empirical measures of both types of fundamental risk can quantitatively substantiate these explanations. Variation in residual earning dispersion accounts for a significant fraction of observed disagreement between debt and equity valuations and of realized stock volatility. The implication that the two components of risk should forecast the levered equity risk premium with opposite signs is also supported in the data. The results are a notable advance for risk-based asset pricing.     

The relative influence of competitive intensity and business strategy on the relationship between financial leverage and performance

This study empirically investigates the effects of competitive intensity and business strategy on the relationship between financial leverage and the performance of firms. Based on a sample of US manufacturing firms, this study confirms the hypothesis that the cost of debt is higher for product differentiation firms than cost leadership firms. Furthermore, the results indicate that competitive intensity has a negative effect on the leverage-performance relationship, suggesting that competition acts as a substitute for debt in limiting manager's opportunistic behavior. These findings reinforce the need to consider moderating factors such as strategic choice and the environment in which a firm operates when investigating the effects of leverage on performance.