Time‐varying market price of risk in the crude oil futures market

In this study, a three‐factor model of crude oil prices is estimated, which incorporates a time‐varying market price of risk. The model is able to accurately capture the term structure of futures prices with evidence suggesting that risk premiums in the crude oil market are time‐varying. Using the cross‐section of futures prices, we estimate a time‐series of the market price of risk in the crude oil market implied by the model. We find that the risk premiums in the crude oil market are driven by the same risk factors as equity and bond markets. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:779–807, 2011     

The new market for volatility trading

This study analyses the new market for trading volatility; VIX futures. We first use market data to establish the relationship between VIX futures prices and the index itself. We observe that VIX futures and VIX are highly correlated; the term structure of average VIX futures prices is upward sloping, whereas the term structure of VIX futures volatility is downward sloping. To establish a theoretical relationship between VIX futures and VIX, we model the instantaneous variance using a simple square root mean‐reverting process with a stochastic long‐term mean level. Using daily calibrated long‐term mean and VIX, the model gives good predictions of VIX futures prices under normal market situation. These parameter estimates could be used to price VIX options. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 30:809–833, 2010     

Forecasting oil price movements: Exploiting the information in the futures market

Relying on the cost of carry model, the long‐run relationship between spot and futures prices is investigated and the information implied in these cointegrating relationships is used to forecast out of sample oil spot and futures price movements. To forecast oil price movements, a vector error correction model (VECM) is employed, where the deviations from the long‐run relationships between spot and futures prices constitute the equilibrium error. To evaluate forecasting performance, the random walk model (RWM) is used as a benchmark. It was found that (a) in‐sample, the information in the futures market can explain a sizable portion of oil price movements; and (b) out‐of‐sample, the VECM outperforms the RWM in forecasting price movements of 1‐month futures contracts. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:34–56, 2008     

Mean Reversion and the Comovement of Equilibrium Spot and Futures Prices: Implications from Alternative Data‐Generating Processes

The comovements of spot and futures prices are characterized by six binary variables, including the term structure curvature of futures prices. These variables are used to uniquely identify 48 possible comovement patterns. Among them, 24 cases are associated with mean reversion, which is defined as a state when spreads between futures and spot prices are shrinking. These pattern frequencies are then calculated on a daily basis with the futures prices of 10 commodities, including precious metal, agricultural, and financial commodities. The results are further compared to simulation output from three data‐generating processes: a bivariate pure random walk, a mixed random walk with first‐order autoregression (AR(1)), and an error‐correction representation. The mean‐reverting frequencies for all 10 commodities are about 50%. Around half of the time, spot and futures prices are moving toward each other, and the rest of the time they move in the same direction. The symmetry of these results implies that the existence of substantial shocks originated from futures markets; thus, this is consistent with the risk premium view of futures trading. Also, although all simulation models produce similar mean‐reversion frequencies, the patterns of comovements of spot and futures prices are different, and the price dynamics depend heavily on whether the market is dominant contango or backwardation. Furthermore, the error‐correction model outperforms the random‐walk model for agricultural commodities, and the mixed random walk with AR(1) is hardly distinguishable from the pure random walk. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:769–796, 2001     

A maximal affine stochastic volatility model of oil prices

This study develops and estimates a stochastic volatility model of commodity prices that nests many of the previous models in the literature. The model is an affine three‐factor model with one state variable driving the volatility and is maximal among all such models that are also identifiable. The model leads to quasi‐analytical formulas for futures and options prices. It allows for time‐varying correlation structures between the spot price and convenience yield, the spot price and its volatility, and the volatility and convenience yield. It allows for expected mean‐reversion in the short term and for an increasing expected long‐term price, and for time‐varying risk premia. Furthermore, the model allows for the situation in which options' prices depend on risk not fully spanned by futures prices. These properties are desirable and empirically important for modeling many commodities, especially crude oil. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:101–133, 2010     

Drift matters: An analysis of commodity derivatives

This article presents a reduced‐form, two‐factor model to price commodity derivatives, which generalizes the model by Schwartz and Smith (2000). The model allows for two mean‐reverting stochastic factors and therefore implies that spot and futures prices can be stationary. An empirical study for the crude oil market tests the new model. Out‐of‐sample pricing and hedging results for futures and forwards show that the new model dominates the nonstationary model by Schwartz and Smith in the following sense: It works equally well for short‐term contracts but leads to major improvements for long‐term contracts. This finding is particularly relevant for typical applications like the valuation of commodity‐linked real assets with long maturities. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:211–241, 2005     

Modes of fluctuation in metal futures prices

This article examines the stochastic structure of metal futures prices. First, this article presents a stationary multi‐factor model of fluctuations in the futures price curve. Next, the model is extended to allow for time variation in the factors or “modes” of fluctuation. The model is estimated using futures price data for three very different metals: copper, which is an industrial metal; gold, which is a precious metal; and silver, which is in transition from a precious metal to an industrial metal. The estimation results show that the shapes and importance of the various modes of fluctuation for gold and silver are much different from those for copper. Gold and silver futures price curves can be adequately modeled as a time‐varying one‐factor model. Copper, however, has a more complicated structure and should be modeled as a time‐varying two‐ or three‐factor model. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20:219–242, 2000     

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     

Intraday price‐reversal patterns in the currency futures market: The impact of the introduction of GLOBEX and the euro

This article assesses the intraday price‐reversal patterns of seven major currency futures contracts traded on the Chicago Mercantile Exchange over 1988–2003 after 1‐day returns and opening gaps. Significant intraday price‐reversal patterns are observed in five of the seven currency futures contracts, following large price changes. Additional tests are conducted in three subperiods (1988–1992, 1993–1998, and 1999–2003) to examine the impact of the introduction of electronic trading on GLOBEX in 1992 (to assess how a near 24‐hour trading session might impact the next‐day opening and closing futures prices) and the introduction of the euro in 1999 (to assess its impact on price predictability in other futures markets). It is found that the introduction of the GLOBEX in 1992 significantly reduced pricing errors in currency futures in the second subperiod, making the currency futures markets fairly efficient. However, the introduction of the new currency, the euro, and the disappearance of several European currencies in 1999, resulted in significant price patterns (mostly reversals and some persistence) in most of the currency futures, indicating inefficiencies in the third subperiod. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:1089–1130, 2006     

A cointegrated commodity pricing model

We propose a commodity pricing model that extends the Gibson–Schwartz two‐factor model to incorporate the effect of linear relations among commodity spot prices, and provide a condition under which such linear relations represent cointegration. We derive futures and call option prices for the proposed model, and indicate that, unlike in Duan and Pliska (2004), the linear relations among commodity prices should affect commodity derivative prices, even when the volatilities of commodity returns are constant. Using crude oil and heating oil market data, we estimate the model and apply the results to the hedging of long‐term futures using short‐term ones.     

Do futures prices help forecast the spot price?

This study proposes a futures‐based unobserved components model for commodity spot prices. Prices quoted at the same time incorporate the same information, but are affected differently, resulting in the different shapes of futures curves. This model utilizes information from part of the futures curve to improve forecasting accuracy of the spot price. Applying this model to oil market data, I find that the model forecasts outperform the literature benchmark (the no‐change forecast) and futures prices forecasts in multiple dimensions, with smaller average error variation over the sample period and higher chance of smaller absolute error in each period.     

Migration of price discovery in semiregulated derivatives markets

This study investigates the information content of futures option prices when the underlying futures price is regulated and the futures option price is not. The New York Board of Trade (NYBOT) provides the empirical setting for this regulatory mismatch. Many commodity derivatives markets regulate the prices of all derivatives on a single underlying commodity simultaneously. Some exchanges, including the NYBOT, regulate only their futures contracts, leaving the options on these futures contracts unregulated. This study takes a particular interest in the option‐implied futures price when the observed futures price is locked limit. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:209–241, 2006     

Hedging long‐term commodity risk: A comment

Y. V. Veld‐Merkoulova and F. A. de Roon (2003) adopted an encompassing model to demonstrate their linear yield assumption on the term structure of futures prices gains more empirical support than the linear price assumption proposed by A. Neuberger (1999). This comment points out the test procedure adopted is inappropriate and proposes an alternative non‐nested hypothesis testing method. Using the crude oil data, we find that the linear price assumption outperforms the linear yield assumption but is inferior to a generalized version of the linear yield assumption. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:1093–1099, 2004     

Why do expiring futures and cash prices diverge for grain markets?

In recent years, cash and futures prices have failed to converge at expiration for selected corn, soybean, and wheat commodity contracts. This lack of convergence raises questions about the effectiveness of arbitrage activities, and increases concerns about the usefulness of these contracts for hedging. We describe the delivery process for these contracts, and show that it embeds a valuable real option on the long side—the option to exchange the deliverable for another futures contract. As the relative volatility of cash and futures prices increases, this option increases in value, which disconnects the cash market from the deliverable instrument in a futures contract. Our estimates of this option's value show that it may create significant price divergence. We parameterize an option pricing model using data on these three commodities from 2000 to 2008 and show that the option model fits closely to recent episodes of non‐convergence, which lends support to the importance of real option effects. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark

相似文献   

The impact of crude oil inventory announcements on prices: Evidence from derivatives markets

This study examines the impact of weekly crude oil storage announcements on oil futures and options prices. We document evidence of a strong announcement day effect on both markets, and find prices to move in anticipation of the inventory surprise. Futures returns significantly decrease with positive surprises and increase with negative surprises. There is no evidence of an asymmetric impact on futures prices. Near‐the‐money options exhibit the greatest price sensitivity, and the magnitude of the price response of both futures and options declines with maturity. The results remain robust even after controlling for various macroeconomic and other storage‐related news variables.     

Stock index futures markets: stochastic volatility models and smiles

This study examined whether the inclusion of an appropriate stochastic volatility that captures key distributional and volatility facets of stock index futures is sufficient to explain implied volatility smiles for options on these markets. I considered two variants of stochastic volatility models related to Heston (1993). These models are differentiated by alternative normal or nonnormal processes driving log‐price increments. For four stock index futures markets examined, models including a negatively correlated stochastic volatility process with nonnormal price innovations performed best within the total sample period and for subperiods. Using these optimal stochastic volatility models, I determined the prices of European options. When comparing simulated and actual options prices for these markets, I found substantial differences. This suggests that the inclusion of a stochastic volatility process consistent with the objective process alone is insufficient to explain the existence of smiles. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:43–78, 2001     

The effect of oil price shocks on asset markets: Evidence from oil inventory news

We quantify the reaction of U.S. equity, bond futures, and exchange rate returns to oil price shocks driven by oil inventory news. Across most sectors, equity prices decrease in response to higher oil prices before the 2007/2008 crisis but increase after it. Positive oil price shocks cause a depreciation of the U.S. dollar against a broad range of currencies but have only a modest effect on bond futures returns. The evidence suggests that changes in risk premia help to explain the time-varying effect of oil price shocks on U.S. equity returns.     

Instantaneous squared VIX and VIX derivatives

In this paper, we propose a parsimonious and efficient model to price derivatives written on VIXs with different horizons. Our model is built on Luo and Zhang's (2012, J Futures Markets, 32, 1092–1123) concept of the instantaneous squared VIX (ISVIX) that is the sum of instantaneous diffusive and jump variances of the SPX return. Modeling the ISVIX as a mean-reverting jump-diffusion process with a stochastic long-term mean, we obtain analytical formulas for VIX options and futures. Estimation with VIX term structure and calibration with VIX options data show that our model performs well in matching both time series and cross-sectional VIX derivatives market prices.     

A non‐lattice pricing model of American options under stochastic volatility

In this article, an analytical approach to American option pricing under stochastic volatility is provided. Under stochastic volatility, the American option value can be computed as the sum of a corresponding European option price and an early exercise premium. By considering the analytical property of the optimal exercise boundary, the formula allows for recursive computation of the American option value. Simulation results show that a nonlattice method performs better than the lattice‐based interpolation methods. The stochastic volatility model is also empirically tested using S&P 500 futures options intraday transactions data. Incorporating stochastic volatility is shown to improve pricing, hedging, and profitability in actual trading. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:417–448, 2006     

Price discovery in the foreign exchange futures market

Examination is made of the relative contributions to price discovery of the floor and electronically traded euro FX and Japanese yen futures markets and the corresponding retail on‐line foreign exchange spot markets. GLOBEX electronic futures contracts provide the most price discovery in the euro; the on‐line trading spot market provides the most in the Japanese yen. The floor‐traded futures markets contribute the least to price discovery in both the euro and the Japanese yen markets. The overall results show that electronic trading platforms facilitate price discovery more efficiently than floor trading. Futures traders may also extract information from on‐line spot prices. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:1131–1143, 2006