Volatility spillover effects and cross hedging in corn and crude oil futures

Using a volatility spillover model, we find evidence of significant spillovers from crude oil prices to corn cash and futures prices, and that these spillover effects are time‐varying. Results reveal that corn markets have become much more connected to crude oil markets after the introduction of the Energy Policy Act of 2005. Furthermore, when the ethanol–gasoline consumption ratio exceeds a critical level, crude oil prices transmit positive volatility spillovers into corn prices and movements in corn prices are more energy‐driven. Based on this strong volatility link between crude oil and corn prices, a new cross‐hedging strategy for managing corn price risk using oil futures is examined and its performance is studied. Results show that this cross‐hedging strategy provides only slightly better hedging performance compared with traditional hedging in corn futures markets alone. The implication is that hedging corn price risk in corn futures markets alone can still provide relatively satisfactory performance in the biofuel era. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark     

Forecasting equity returns: The role of commodity futures along the supply chain

This paper examines equity return predictability using the returns of commodity futures along the supply chain in China's financial market. We find that a considerable number of commodities exhibit significant in‐sample forecasting ability at the daily horizon, especially for supplier‐side equity returns. The macroeconomic risk premium effect, captured by the aggregate commodity prices, is an important source for this predictability. The out‐of‐sample results show that for most commodities, the predictability remains both statistically and economically significant, and the forecasting performance improves substantially during recessions or with economic constraints.     

Intradaily periodicity and volatility spillovers between international stock index futures markets

This paper examines short‐run information transmission between the U.S. and U.K. markets using the S&P 500 and FTSE 100 index futures. Ultrahighfrequency futures data are employed—which have a number of advantages over the low‐frequency spot data commonly used in previous studies—in establishing that volatility spillovers are in fact bidirectional. The generalized autoregressive conditionally heteroskedastic model (GARCH) is employed to estimate the mean and volatility spillovers of intraday returns. A Fourier flexible function is utilized to filter the intradaily periodic patterns that induce serial correlation in return volatility. It was found that estimates of volatility persistence and speed of information transmission are seriously affected by intradaily periodicity. The bias in parameter estimation is removed by filtering out the intradaily periodic component of the transaction data. Contrary to previous findings, there is evidence of spillovers in volatility between the U.S. and U.K. markets. Results indicate that the volatility of the U.S. market is affected by the most recent volatility surprise in the U.K. market. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:553–585, 2005     

Looking for contagion in currency futures markets

This article tests whether there are pure contagion effects in both conditional means and volatilities among British pound, Canadian dollar, Deutsche mark, and Swiss franc futures markets during the 1992 ERM crisis. A conditional version of international capital asset pricing model (ICAPM) in the absence of purchasing power parity (PPP) is used to control for economic fundamentals. The empirical results indicate that overall there are no mean spillovers among those futures markets, but they are detected during the crisis period. That is, past return shocks originating in any one of the four markets have no impact on the other three markets during the entire sample period, suggesting that these markets are weak‐form efficient. However, this weak‐form market efficiency fails to hold during the market turmoil, especially for British pound and Swiss franc, and the sources of contagion‐in‐mean effects are mainly due to the return shocks originating in three European currency futures markets. As for the contagion‐in‐volatility, it is detected for British pound only because its conditional volatility is influenced by the negative volatility shocks from Canadian dollar, Deutsche mark, and Swiss franc, with Deutsche mark playing the dominant role in generating these shocks. JEL Classifications: C32; F31; G12. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:957–988, 2003     

Effects of nondiscretionary trading on futures prices

This paper examines the effects of the nondiscretionary trading demands of volatility index (VIX) exchange-traded products (ETPs) issuers on the prices and volumes in the VIX futures. We find that the ETPs' informationless, mechanical rebalancing of futures positions to maintain the constant maturity of the index and the promised leverage ratios of the VIX ETPs have significantly positive predictive power for end-of-day futures returns. We also show that the impact on price has diminished through time from increased liquidity provided by hedge funds, and the “natural” hedging of the issuers' inverse products.     

VIX futures and its closed‐form pricing through an affine GARCH model with realized variance

This paper studies the forecasting of volatility index (VIX) and the pricing of its futures by a generalized affine realized volatility model proposed by Christoffersen et al. This model is a weighted average of a GARCH and a pure realized variance (RV) model that incorporates each volatility component into the new dynamics. We rewrite the VIX in terms of both volatility components and then derive closed‐form formulas for the VIX forecasting and its futures pricing. Our empirical studies find that a unification of the GARCH and the RV in the modeling substantially improves the forecasting of this index and the pricing of its futures.     

Price discovery and volatility spillovers in the DJIA index and futures markets

The Dow Jones Industrial Average (DJIA) is the most widely quoted stock index worldwide. This article examines the minute-by-minute price discovery process and volatility spillovers between the DJIA index and the index futures recently launched by the CBOT. The Hasbrouck (1995) cointegrating model suggests that most of the price discovery takes place at the futures market. However, by examining the volatility spillovers between the markets based on a bivariate EGARCH model, a significant bidirectional information flow is found. That is, innovations in one market can predict the future volatility in another market, but the futures market volatility-spillovers to the stock market more than vice versa. Both markets also exhibit asymmetric volatility effects, with bad news having a greater impact on volatility than good news. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 911–930, 1999     

Economic uncertainty,trading activity,and commodity futures volatility

This paper investigates the dynamics of commodity futures volatility. I derive the variance decomposition for the futures basis and show unexpected excess returns result from new information about expected future interest rates, convenience yields, and risk premia. Measures of uncertainty in economic conditions have significant predictive power for realized volatility of commodity futures returns, after controlling for lagged volatility, returns, commodity index trading, hedging pressure, and other trading activity, even during the so-called “index financialization” period. During this period, hedge fund performance predicts volatility in grain commodities, which are affected by the US ethanol mandate.     

Impact of bitcoin futures on the informational efficiency of bitcoin spot market

This study examines the informational efficiency of the bitcoin spot market by evaluating the predictive power of mechanical trading rules designed to exploit price continuation. Significant return predictability is found until the introduction of bitcoin futures in December 2017. The forecasting ability of trend‐chasing trading rules declines dramatically afterwards. Although evidence suggests that the introduction of bitcoin futures has increased the informational efficiency of the bitcoin spot market, no signs of improvement in informational efficiency are found in ethereum, the second‐largest cryptocurrency—following the introduction of bitcoin futures.     

Volatility and trading demands in stock index futures

In this study we examine how volatility and the futures risk premium affect trading demands for hedging and speculation in the S&P 500 Stock Index futures contracts. To ascertain if different volatility measures matter in affecting the result, we employ three volatility estimates. Our empirical results show a positive relation between volatility and open interest for both hedgers and speculators, suggesting that an increase in volatility motivates both hedgers and speculators to engage in more trading in futures markets. However, the influence of volatility on futures trading, especially for hedging, is statistically significant only when spot volatility is used. We also find that the demand to trade by speculators is more sensitive to changes in the futures risk premium than is the demand to trade by hedgers. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:399–414, 2003     

Samuelson hypothesis,arbitrage activity,and futures term premiums

The Samuelson hypothesis asserts that futures volatility increases as maturity decreases. On the basis of 10 US commodity futures and by capturing the dynamics of the futures volatility terms structure with three factors, we show that in most markets the slope factor is strongly negative in certain periods and at best only weakly negative in other periods. High inventory levels are found to correspond to flatter volatility term structures in seven futures. This finding is consistent with the linkage between carry arbitrage and the Samuelson hypothesis. We also find that a flatter volatility term structure corresponds to lower absolute futures term premiums.     

Forecasting futures returns in the presence of price limits

In a futures market with a daily price‐limit rule, trading occurs only at prices within limits determined by the previous day's settlement price. Price limits are set in dollars but can be expressed as return limits. When the daily return limit is triggered, the true equilibrium futures return (and price) is unobservable. In such a market, investors may suffer from information loss if the return “moves the limit.” Assuming normally distributed futures returns with unknown means but known volatilities, we develop a Bayesian forecasting model in the presence of return limits and provide some numerical predictions. Our innovation is the derivation of the predictive density for futures returns in the presence of return limits. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:199–210, 2005     

Return distributions and volatility forecasting in metal futures markets: Evidence from gold,silver, and copper

The characterization of return distributions and forecast of asset‐price variability play a critical role in the study of financial markets. This study estimates four measures of integrated volatility—daily absolute returns, realized volatility, realized bipower volatility, and integrated volatility via Fourier transformation (IVFT)—for gold, silver, and copper by using high‐frequency data for the period 1999 through 2008. The distributional properties are investigated by applying recently developed jump detection procedures and by constructing financial‐time return series. The predictive ability of a GARCH (1,1) forecasting model that uses various volatility measures is also examined. Three important findings are reported. First, the magnitude of the IVFT volatility estimate is the greatest among the four volatility measures. Second, the return distributions of the three markets are not normal. However, when returns are standardized by IVFT and realized volatility, the corresponding return distributions bear closer resemblance to a normal distribution. Notably, the application of financial‐time sampling technique is helpful in obtaining a normal distribution. Finally, the IVFT and realized volatility proxies produce the smallest forecasting errors, and increasing the time frequency of estimating integrated volatility does not necessarily improve forecast accuracy. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:55–80, 2011     

What moves German Bund futures contracts on the Eurex?

The German 10‐year Bund futures contract traded on the Eurex futures and options exchange in Frankfurt became the world's most actively traded derivative product by the end of 1999. In this article, we provide a detailed exploration of the interday and intraday return volatility in the Bund futures contract using a sample of five‐min returns from 1997 to 1998. The evolution of interday volatility is described best by a MA(1)‐fractionally integrated process that allows for the long‐memory features. At the intraday level, we find that macroeconomic announcements from both Germany and the U.S. are an important source of volatility. Among the various German announcements, we identify the IFO industry survey of business climate, industrial production (preliminary), and Bundesbank policy meeting as being by far the most important. The three most significant U.S. announcements include the employment report, the National Association of Purchasing Managers (NAPM) survey, and employment costs. Overall, U.S. macroeconomic announcements have a far greater impact on the Bund futures market than their German counterparts. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:679–696, 2002     

Intertemporal volatility and price interactions between Australian and Japanese spot and futures stock index markets

Previous studies have examined causality within and between different spot and futures markets with a motivation to discover market comovements, price leadership effects, and, more recently, volatility spillovers across markets. However, the empirical framework within which this is accomplished tends not to analyze explicitly foreign spillover effects upon a spot–futures relationship, which may significantly alter the equilibrium between these markets. This will then have a direct impact upon the estimation of dynamic risk adjustments that occur from the interaction between these markets. This article develops a quadvariate simultaneous-equation EC-ARCH model with an emphasis on volatility spillovers as a better alternative methodology to evaluate these relationships from a different perspective. This model is applied to examine the interaction between the Australian and Japanese spot and futures stock index markets, which allows for an Australian or Japanese futures trader to analyze the impact of foreign cash and futures markets, as well as the local cash market, on the local futures market in a single coherent framework. This type of analysis is not possible using previous paradigms, because they allow the trader only to examine the impact of local cash and foreign futures markets in separate settings. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 523–540, 1999     

Asymmetric extreme risk spillovers between the Chinese stock market and index futures market: An MV-CAViaR based intraday CoVaR approach

This paper proposes a predictive CoVaR measure to analyze asynchronous risk spillovers between the Chinese stock and futures market. We jointly model the intraday CoVaR dynamics using an extended MV-CAViaR model. The results show the presence of asymmetric spillovers under different market states, different trading rules, and different confidence levels. Specifically, there exist significant downside spillovers and insignificant upside spillovers. Moreover, the futures (stock) market becomes dominant in risk transmission during bearish (bullish) market periods. Furthermore, high margin requirements would weaken the spillover effects of the futures market, but it would also strengthen the spillover effects of the stock market.     

The market quality of commodity futures markets

To study the market quality of commodity futures markets, we construct a commodity futures market quality index from the perspective of liquidity, efficiency, and volatility. Based on the market quality index, the Chinese commodity futures market operates steadily. The metal futures market is more efficient and stable than the market for agricultural futures. The Chinese commodity futures market is less liquid and more volatile than the U.S. market. We examine the determinants of market quality and find that macroeconomic variables and futures market contracts are significantly related to the market quality of Chinese commodity futures.     

Estimating the connectedness of commodity futures using a network approach

Using a network approach of variance decompositions, we measure the connectedness of 18 commodity futures and characterize both static and dynamic connectedness. Our results show that metal futures are net transmitters of shocks to other futures, and agricultural futures are vulnerable to shocks from the others. Furthermore, almost two-thirds of the volatility uncertainty for commodity futures are due to the connectedness of shocks across the futures market. Dynamically, we find connectedness always increases in times of turmoil. An analysis of connectedness networks suggests that investors could be forewarned that the connectedness of various classes of futures could threaten their portfolios.     

Volatility components: The term structure dynamics of VIX futures

In this study we empirically study the variance term structure using volatility index (VIX) futures market. We first derive a new pricing framework for VIX futures, which is convenient to study variance term structure dynamics. We construct five models and use Kalman filter and maximum likelihood method for model estimations and comparisons. We provide evidence that a third factor is statistically significant for variance term structure dynamics. We find that our parameter estimates are robust and helpful to shed light on economic significance of variance factor model. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:230–256, 2010     

Modeling discontinuous periodic conditional volatility: Evidence from the commodity futures market

This paper examines a wide variety of models that allow for complex and discontinuous periodic variation in conditional volatility. The value of these models (including augmented versions of existing models) is demonstrated with an application to high frequency commodity futures return data. Their use is necessary, in this context, because commodity futures returns exhibit discontinuous intraday and interday periodicities in conditional volatility. The former of these effects is well documented for various asset returns; however, the latter is unique amongst commodity futures returns, where contract delivery and climate are driving forces. Using six years of high‐frequency cocoa futures data, the results show that these characteristics of conditional return volatility are most adequately captured by a spline‐version of the periodic generalized autoregressive conditional heteroscedastic (PGARCH) model. This model also provides superior forecasts of future return volatility that are robust to variation in the loss function assumed by the user, and are shown to be beneficial to users of Value‐at‐Risk (VaR) models. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:805–834, 2004