Determination of stock closing prices and hedging performance with stock indices futures

This paper examines the impact of the determination of stock closing prices on futures price efficiency and hedging effectiveness with stock indices futures. The empirical results indicate that the increase in the length of the batching period of the stock closing call improves price efficiency in the futures closing prices and then enhances hedging performance in terms of the hedging risks. Additionally, from a utility‐maximization point of view, hedging performance does not improve after the introduction of the 5 min stock closing call, which can be explained by an improvement in price efficiency at the futures market close.     

Commodity futures hedging,risk aversion and the hedging horizon

This paper examines the impact of management preferences on optimal futures hedging strategy and associated performance. Applying an expected utility hedging objective, the optimal futures hedge ratio is determined for a range of preferences on risk aversion, hedging horizon and expected returns. Empirical results reveal substantial hedge ratio variation across distinct management preferences and are supportive of the hedging policies of real firms. Hedging performance is further shown to be strongly dependent on underlying preferences. In particular, hedgers with high risk aversion and short horizon reduce hedge portfolio risk but achieve inferior utility in comparison to those with low aversion.     

Mean-variance hedging with oil futures

We analyze mean-variance-optimal dynamic hedging strategies in oil futures for oil producers and consumers. In a model for the oil spot and futures market with Gaussian convenience yield curves and a stochastic market price of risk, we find analytical solutions for the optimal trading strategies. An implementation of our strategies in an out-of-sample test on market data shows that the hedging strategies improve long-term return-risk profiles of both the producer and the consumer.     

The relation between forward prices and futures prices

This paper consolidates the results of some recent work on the relation between forward prices and futures prices. It develops a number of propositions characterizing the two prices. These propositions contain several testable implications about the difference between forward and futures prices. Many of the propositions show that equilibrium forward and futures prices are equal to the values of particular assets, even though they are not in themselves asset prices. The paper then illustrates these results in the context of two valuation models and discusses the effects of taxes and other institutional factors.     

Conditional extreme risk,black swan hedging,and asset prices

Motivated by the asset pricing theory with safety-first preference, we introduce and operationalize a conditional extreme risk (CER) measure to describe expected stock performance conditional on a small-probability market downturn (black swan). We document a significant CER premium in the cross-section of expected returns. We also demonstrate that CER explains the premia to downside beta, coskewness, and cokurtosis. CER provides distinct information regarding black swan hedging that cannot be captured by co-crash-based tail dependence measures. As we find that the pricing effect is stronger among black swan hedging stocks, this distinction helps explain the absence of premium to tail dependence.     

Noise, equity prices, and hedging: A new approach

The existence of noise trading in equity markets has possible economic implications for arbitrage, and asset pricing. In terms of pricing, noise trading can lead to excess volatility which has been shown to influence the value of options and futures. Furthermore, option research shows that modeling volatility leads to improved hedging performance. To this end, we derive a general hedging model for equity index futures in the presence of noise trading. Our analysis shows how the level and dynamics of noise trading should influence a hedger's behavior. Finally, we empirically test our model using the NASDAQ-100 index futures and FTSE 100 index futures over the period of January 1998 to May 2003.     

Systematic risk, hedging pressure, and risk premiums in futures markets

I examine the uniformity of risk pricing in futures and assetmarkets. Tests against a general alternative do not reflectcomplete integration of futures and asset markets. As predicted,estimates of the 'zero-beta' rate for futures are close to zero,and premiums for systematic risk do not differ significantlyacross assets and futures. There is, however, evidence consistentwith a specific alternative model presented by Hirshleifer (1988).Returns in foreign currency and agricultural futures vary withthe net holdings of hedgers, after controlling for systematicrisk. These results imply a degree of market segmentation andsupport hedging pressure as a determinant of futures premiums.     

Optimal futures hedging under jump switching dynamics

The article develops a Markov regime switching Generalized Orthogonal GARCH model with conditional jump dynamics (JSGO) for optimal futures hedging. To the author's knowledge, there is no existing study on dynamic futures hedging investigating both the effects of regime switching and conditional jumps. This might be the fact that there is no existing hedging model encompassing both of these features. The JSGO solves this problem by introducing a jump switching filtering algorithm to infer ex post both the distributions of jumps and state variables and a recombining procedure to solve the path-dependency problem. To justify the usefulness of the JSGO on dynamic futures hedging, hedging exercises are performed using FTSE 100 futures data traded in the London International Financial Futures and Options Exchange (LIFFE). JSGO exhibits good out-of-sample performance compared to its jump-free and state-independent counterparts in terms of both criteria of variance reductions and utility improvements.     

Optimal dynamic hedging in incomplete futures markets

This article derives optimal hedging demands for futures contracts from an investor who cannot freely trade his portfolio of primitive assets in the context of either a CARA or a logarithmic utility function. Existing futures contracts are not numerous enough to complete the market. In addition, in the case of CARA, the nonnegativity constraint on wealth is binding, and the optimal hedging demands are not identical to those that would be derived if the constraint were ignored. Fictitiously completing the market, we can characterize the optimal hedging demands for futures contracts. Closed-form solutions exist in the logarithmic case but not in the CARA case, since then a put (insurance) written on his wealth is implicitly bought by the investor. Although solutions are formally similar to those that obtain under complete markets, incompleteness leads in fact to second-best optima.     

Cross hedging with stochastic correlation

This paper is concerned with the study of quadratic hedging of contingent claims with basis risk. We extend existing results by allowing the correlation between the hedging instrument and the underlying of the contingent claim to be random itself. We assume that the correlation process ρ evolves according to a stochastic differential equation with values between the boundaries −1 and 1. We keep the correlation dynamics general and derive an integrability condition on the correlation process that allows to describe and compute the quadratic hedge by means of a simple hedging formula that can be directly implemented. Furthermore, we show that the conditions on ρ are fulfilled by a large class of dynamics. The theory is exemplified by various explicitly given correlation dynamics.     

A comparison of futures and forward prices

This paper uses the pricing models of Cox, Ingersoll and Ross (1981), Richard and Sundaresan (1981), and French (1982) to examine the relation between futures and forward prices for copper and silver. There are significant differences between these prices. The average differences are generally consistent with the predictions of the futures and forward price models. However, these models are not helpful in describing intra-sample variations in the futures-forward price differences. This failure is apparently caused by measurement errors in both the price differences and in the explanatory variables.     

Long memory in energy futures prices

This paper extends the work in Serletis [Serletis, A. (1992). Unit root behavior in energy futures prices. The Energy Journal 13, 119-128] by re-examining the empirical evidence for random walk type behavior in energy futures prices. It tests for fractional integrating dynamics in energy futures markets utilizing more recent data (from January 3, 1994 to June 30, 2005) and a new semi-parametric wavelet-based estimator, which is superior to the more prevalent GPH estimator (on the basis of Monte-Carlo evidence). We find new evidence that energy prices display long memory and that the particular form of long memory is anti-persistence, characterized by the variance of each series being dominated by high frequency (low wavelet scale) components.     

Cross-commodity hedging for illiquid futures: Evidence from China's base metal futures market

This paper evaluates the effectiveness of cross-commodity hedging between China's base metal spot and futures markets, using daily data of metal spot and futures prices in the Shanghai Futures Exchange. The main findings suggest that, compared to unhedged spot portfolios, a naïve hedge increases risk exposure, while static and dynamic hedges can significantly reduce the risk of holding spot assets. Zinc futures and nickel futures outperform other base metal futures in individually hedging lead spot and tin spot respectively, while copper futures constitute a moderately optimal instrument to hedge both lead and tin spot assets.     

Stock index futures hedging in the emerging Malaysian market

The paper investigates hedging effectiveness of dynamic and constant models in the emerging market of Malaysia where trading information is not readily available and market liquidity is lower compared to the developed equity markets. Using daily data from December 1995 to April 2001 and bivariate GARCH(1,1) and TGARCH models, the paper uses differing variance–covariance structures to obtain hedging ratios. Performance of models is compared in terms of variance reduction and expected utility levels for the full sample period as well as the three sub-periods which encompass the Asian financial crisis and introduction of new capital control measures in Malaysia. Findings show that rankings of the hedging models change for the in-sample period depending on evaluation criteria used. TGARCH based models provide better hedging performance but only in the period of higher information asymmetry following the imposition of capital controls in Malaysia. Overall, despite the structural breaks caused by the Asian financial crisis and new capital control regulations, out of sample hedging performance of dynamic GARCH models in the Malaysian emerging market is as good as the one reported for the highly developed markets in the previous literature. The findings suggest that changes in the composition of market agents caused by large scale retreat of foreign investors following the imposition of capital control regulations do not seem to have any material impact on the volatility characteristics of the Malaysian emerging market.     

Using high, low, open, and closing prices to estimate the effects of cash settlement on futures prices

Due to dwindling commercial interest in the feeder cattle futures contract, the Chicago Mercantile Exchange (CME) decided to replace the contract's physical delivery provision with a cash settlement provision, arguing that cash settlement would help reduce price volatility and attracts more commercial interests. In this article, we apply stochastic volatility models to investigate the CME conjecture, using four different estimators based on opening, high, low, and closing prices, respectively. With each estimator, we find that the volatility of the feeder cattle futures price decreases after the implementation of cash settlement. We conclude that the change in the contract specification enhances price discovery and the contract's hedging performance.     

Risk premia in crude oil futures prices

If commercial producers or financial investors use futures contracts to hedge against commodity price risk, the arbitrageurs who take the other side of the contracts may receive compensation for their assumption of nondiversifiable risk in the form of positive expected returns from their positions. We show that this interaction can produce an affine factor structure to commodity futures prices, and develop new algorithms for estimation of such models using unbalanced data sets in which the duration of observed contracts changes with each observation. We document significant changes in oil futures risk premia since 2005, with the compensation to the long position smaller on average in more recent data. This observation is consistent with the claim that index-fund investing has become more important relative to commerical hedging in determining the structure of crude oil futures risk premia over time.     

Analytical bounds for Treasury bond futures prices

The pricing of delivery options, particularly timing options, in Treasury bond futures is prohibitively expensive. Recursive use of the lattice model is unavoidable for valuing such options, as Boyle in J Finance 14(1):101?C113, (1989) demonstrates. As a result, the main purpose of this study is to derive upper bounds and lower bounds for Treasury bond futures prices. This study first shows that the popular preference-free, closed form cost of carry model is an upper bound for the Treasury bond futures price. Then, the next step is to derive analytical lower bounds for the futures price under one and two-factor Cox-Ingersoll-Ross models of the term structure. The bound under the two-factor Cox-Ingersoll-Ross model is then tested empirically using weekly futures prices from January 1987 to December 2000.     

The relationship between reciprocal currency futures prices

Consider a futures contract on Country 2’s currency denominated in Country 1’s currency, and its reciprocal, a futures contract on Country 1’s currency denominated in Country 2’s currency. Because both are marked to market in different currencies, the relationship between the associated futures prices is not simple. We investigate the functional relationship between these two futures prices.     

Quadratic hedging in affine stochastic volatility models

We determine the variance-optimal hedge for a subset of affine processes including a number of popular stochastic volatility models. This framework does not require the asset to be a martingale. We obtain semiexplicit formulas for the optimal hedging strategy and the minimal hedging error by applying general structural results and Laplace transform techniques. The approach is illustrated numerically for a Lévy-driven stochastic volatility model with jumps as in Carr et al. (Math Finance 13:345–382, 2003).      

Multivariate GARCH hedge ratios and hedging effectiveness in Australian futures markets

We use the All Ordinaries Index and the corresponding Share Price Index futures contract written against the All Ordinaries Index to estimate optimal hedge ratios, adopting several specifications: an ordinary least squares‐based model, a vector autoregression, a vector error‐correction model and a diagonal‐vec multivariate generalized autoregressive conditional heteroscedasticity model. Hedging effectiveness is measured using a risk‐return comparison and a utility maximization method. We find that time‐varying generalized autoregressive conditional heteroscedasticity hedge ratios perform better than constant hedge ratios in terms of minimizing risks, but when return effects are also considered, the utility‐based measure prefers the ordinary least squares method in the in‐sample hedge, whilst both approaches favour the conditional time‐varying multivariate generalized autoregressive conditional heteroscedasticity hedge ratio estimates in out‐of‐sample analyses.