Optimal hedging with futures options

This paper explores the use of commodity options as risk management tools in incomplete markets with particular attention to alternative hedging strategies in the presence of basis and quantity risks. Hedgers typically face basis and quantity risks, which result in incomplete markets. In such markets, portfolios of commodity options prove a viable means of managing risks.Hedging opportunities are characterized using partial equilibrium frameworks, comparative statics, and an illustration from a simulation. A nonlinear optimization technique determines optimal portfolios of commodity options. All models examined are static two-date models. Therefore, they ignore the dynamic aspects of the hedger's problem, and distinguish neither American from European options, nor futures from forward markets.     

Fractional cointegration and futures hedging

This article examines the performance of various hedge ratios estimated from different econometric models: The FIEC model is introduced as a new model for estimating the hedge ratio. Utilized in this study are NSA futures data, along with the ARFIMA-GARCH approach, the EC model, and the VAR model. Our analysis identifies the prevalence of a fractional cointegration relationship. The effects of incorporating such a relationship into futures hedging are investigated, as is the relative performance of various models with respect to different hedge horizons. Findings include: (i) Incorporation of conditional heteroskedasticity improves hedging performance; (ii) the hedge ratio of the EC model is consistently larger than that of the FIEC model, with the EC providing better post-sample hedging performance in the return–risk context; (iii) the EC hedging strategy (for longer hedge horizons of ten days or more) incorporating conditional heteroskedasticty is the dominant strategy; (iv) incorporating the fractional cointegration relationship does not improve the hedging performance over the EC model; (v) the conventional regression method provides the worst hedging outcomes for hedge horizons of five days or more. Whether these results (based on the NSA index) can be generalized to other cases is proposed as a topic for further research. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 457–474, 1999     

Dynamic hedging of paper with T bill futures

Despite the growing importance of the commercial paper market there is no empirical work investigating the hedging performance of dynamic hedging strategies versus traditional static hedging strategies. This article proposes a dynamic hedging model for commercial paper that takes advantage of time dependencies present in the joint density of commercial paper and T-bill futures. The hedging effectiveness of the dynamic model is compared to that of the static regression model. There is clear evidence that dynamic hedging is superior to static hedging in terms of both total variance reduction and expected utility maximization. These results hold even when transactions costs are explicitly taken into account. © 1998 John Wiley & Sons, Inc. Jrl Fut Mark 18:925–938, 1998     

A hedging deficiency in eurodollar futures

The eurodollar futures contract of the Chicago Mercantile Exchange is arguably the most successful of all futures contracts. The contract is structured such that its price does not converge to the price of the underlying eurodollar time deposit. Ignoring the daily settlement, one typically assumes that a eurodollar futures contract perfectly hedges an anticipated loan pegged to LIBOR, provided the loan rate is set at the eurodollar expiration. This article demonstrates that this hedge is not perfect, leaving a risk empirically estimated at four basis points, a seemingly small amount but considerably larger than the bid–ask spread on the futures. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:189–207, 2006     

Pricing and hedging in the freight futures market

In this article, we consider the pricing and hedging of single‐route dry bulk freight futures contracts traded on the International Maritime Exchange. Thus far, this relatively young market has received almost no academic attention. In contrast to many other commodity markets, freight services are non‐storable, making a simple cost‐of‐carry valuation impossible. We empirically compare the pricing and hedging accuracy of a variety of continuous‐time futures pricing models. Our results show that the inclusion of a second stochastic factor significantly improves the pricing and hedging accuracy. Overall, the results indicate that the Schwartz and Smith ( 2000 ) two‐factor model provides the best performance. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:440–464, 2011     

Liquidity constraints and the hedging role of futures spreads

This paper examines the behavior of the competitive firm under price uncertainty in general and the hedging role of futures spreads in particular. The firm has access to a commodity futures market where unbiased nearby and distant futures contracts are transacted. A liquidity constraint is imposed on the firm such that the firm is forced to prematurely close its distant futures position whenever the net interim loss due to its nearby and distant futures positions exceeds a threshold level. This paper shows that the liquidity constrained firm optimally opts for a long nearby futures position and a short distant futures position should the firm be prudent, thereby rendering the optimality of using futures spreads for hedging purposes. This paper further shows that the firm's production decision is adversely affected by the presence of the liquidity constraint. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:909–921, 2004