Narrow Results

We provide a new way of hedging a commodity exposure which eliminates downside risk without sacrificing upside potential. The tool used is a variant on the equity passport option and can be used with both futures and forwards contracts as the underlying hedge instrument. Results are given for popular commodity price models such as Gibson-Schwartz and Black with convenience yield. Two different scenarios are considered, one where the producer places his usual hedge and undertakes additional trading, and the other where the usual hedge is not held. In addition, a comparison result is derived showing that one scenario is always more expensive than the other. The cost of these methods are compared to buying a put option on the commodity.

This paper extends and refines the Jarrow et al. (2006, 2008) arbitrage free pricing theory for bubbles to characterize forward and futures prices. Some new insights are obtained in this regard. In particular, we: (i) provide a canonical process for asset price bubbles suitable for empirical estimation, (ii) discuss new methods to test empirically for asset price bubbles using both spot prices and call/put option prices on the spot commodity, (iii) show that futures prices can have bubbles independent of the underlying asset's price bubble, (iv) relate forward and futures prices under bubbles, and (v) relate price options on futures with asset price bubbles.

We study the problem of dynamically trading futures in continuous time under a multifactor Gaussian framework. We present a utility maximization approach to determine the optimal futures trading strategy. This leads to the explicit solution to the Hamilton–Jacobi–Bellman (HJB) equations. We apply our stochastic framework to two-factor models, namely, the Schwartz model and Central Tendency Ornstein–Uhlenbeck (CTOU) model. We also develop a multiscale CTOU model, which has a fast mean-reverting and a slow mean-reverting factor in the spot asset price dynamics. Numerical examples are provided to illustrate the investor’s optimal positions for different futures portfolios.

As interest rate benchmarks move from LIBOR to overnight risk-free rates (RFR), it has become increasingly important for models to accurately capture the interest rate dynamics at the overnight tenor. Overnight rates closely track central bank policy rate decisions resulting, in highly discontinuous dynamics around scheduled meeting dates. In this paper, we construct a dynamic term structure model, which accounts for the discontinuous short-rate dynamics. We show that the model is able to jointly fit the overnight US policy rate, secured overnight financing rate (SOFR) and SOFR futures rates through the recent Fed hiking cycle. Comparing our model with a standard continuous time-homogeneous short-rate model, we find several indications that our model avoids the clear misspecification of the continuous model, in particular with regard to the short-rate dynamics around meeting dates of the Federal Open Market Committee (FOMC). Thiseffect begins to disappear as the term of the rates under consideration is increased, suggesting that diffusive dynamics are a reasonably accurate reflection of the evolution of market expectations embodied in longer-term interest rates.

Macro-hedging is one of the most important issues in hedging, but there are very few studies on the welfare impact of macro-hedging. To bridge a gap in the literature of macro-hedging, this paper introduces a method that generalizes and extends existing models of macro-hedging in several significant ways. We first assume the existence of basis risk in a small country to hedge in futures markets instead of forward contracts and relax the full-hedging assumption. We use the quantity being hedged in futures contracts as a decision variable. We also relax the restrictive assumption regarding the form of the spot price. We then derive the formula to estimate the welfare gain which can be easily implemented in any empirical case. In contrast to quasi-simulation being used in some existing approaches, our proposed method can be used for any real data, including future data, but existing methods in the literature cannot. Our approach is for investors for their investment decision-making when they use macro-hedging as their trading strategy.

In energy markets, changes in the spot price due to the influence of weather and seasonal demand conditions are partially predictable. In this work, we examine the German GASPOOL and NetConnect Germany natural gas markets using the Ederington and Salas [2008] framework that considers the predictive power of the base (futures price minus spot price) in the estimation of minimum variance hedge ratios. A considerable improvement in risk reduction and hedging effectiveness can be obtained by considering the partial predictability of changes in spot prices. We find that long hedges perform better than short hedges and there is no benefit to be gained by using more complex hedging estimations (BEKK) over the simpler OLS model. Seasonality is also found in hedging ratios.

Energy-based assets are showing increased susceptibility to volatility arising out of geo-political, economic, climate and technological events. Given the economic importance of energy products, their market participants need to be able to access efficient strategies to effectively manage their exposures and reduce price risk. This chapter will outline the key futures-based hedging approaches that have been developed for managing energy price risk and evaluate their effectiveness. A key element of this analysis will be the breadth of assets considered. These include Crude and Refined Oil products, Natural Gas and wholesale Electricity markets. We find significant differences in the hedging effectiveness of the different energy markets. A key finding is that, Natural Gas and particularly Electricity futures are relatively ineffective as a risk management tool when compared with other energy assets.