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Convenience Yield (convenience + yield)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	90%

Selected Abstracts

Forecasting the price of crude oil via convenience yield predictions

JOURNAL OF FORECASTING, Issue 7 2007
Thomas A. KnetschArticle first published online: 14 NOV 200
Abstract The paper develops an oil price forecasting technique which is based on the present value model of rational commodity pricing. The approach suggests shifting the forecasting problem to the marginal convenience yield, which can be derived from the cost-of-carry relationship. In a recursive out-of-sample analysis, forecast accuracy at horizons within one year is checked by the root mean squared error as well as the mean error and the frequency of a correct direction-of-change prediction. For all criteria employed, the proposed forecasting tool outperforms the approach of using futures prices as direct predictors of future spot prices. Vis-à-vis the random-walk model, it does not significantly improve forecast accuracy but provides valuable statements on the direction of change. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Algebraic properties of evolution partial differential equations modelling prices of commodities,

MATHEMATICAL METHODS IN THE APPLIED SCIENCES, Issue 6 2008
C. Sophocleous
Abstract Schwartz (J. Finance 1997; 52:923,973) presented three models for the pricing of a commodity. The simplest was a variation on the Black,Scholes equation. The second allowed for a stochastic convenience yield on the commodity and the third added a stochastic variation in the underlying interest rate. We apply the techniques of Lie group analysis to resolve these equations, discuss their peculiar algebraic properties and indicate the route to the addition of other stochastic influences. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Updating the estimation of the supply of storage

THE JOURNAL OF FUTURES MARKETS, Issue 7 2006
Carl R. Zulauf
An updated supply of storage is estimated to reflect recent developments in the literature. This study adds a measure of price variability, specifically implied volatility. It also adds a measure of the call-option value to sell stocks before the end of the storage period, specifically a measure developed by Heaney (2002). The model is estimated for U.S. soybean stocks carried between crop years. A quadratic relationship is found between stocks to use ratio and implied volatility. A statistically significant, inverse, linear relationship is found between the storage-cost,adjusted spread and the estimated call-option value. This finding is consistent with the much debated idea that convenience yield is a return to storage that can offset losses from storage when intertemporal price spreads are negative. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:657,676, 2006 [source]

An empirical analysis of commodity pricing

THE JOURNAL OF FUTURES MARKETS, Issue 4 2006
Richard Heaney
Commodity pricing models generally explain the link between commodity prices and stock levels in terms of a stock-out constraint or a convenience yield. Analysis of this link is provided using monthly London Metals Exchange copper, lead, and zinc prices obtained for the period November 1964 to December 2003. A Markov model, fitted to these data, supports the existence of two distinct pricing regimes while the impact of convenience yields is also identified. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:391,415, 2006 [source]

Asymmetric volatility of basis and the theory of storage

THE JOURNAL OF FUTURES MARKETS, Issue 4 2005
Andre H. Gao
The theory of storage states that the marginal convenience yield on inventory falls at a decreasing rate as inventory increases. Previous literature has tested this hypothesis using the so-called "direct test" approach, which employs a direct measurement of inventory levels, or the "indirect test" approach, which examines the relative variation of spot and futures prices and the relative variation of negative basis to positive basis as alternative proxies for inventory levels. The rationale behind the indirect test is based on the hypothesis that futures prices are less variable than spot prices when inventory is low, and have similar variability when inventory is high. The authors propose a "unified test" of the theory of storage that incorporates aspects of both direct and indirect tests in an ARMAX-asymmetric GARCH model framework. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:399,418, 2005 [source]

Approximation for convenience yield in commodity futures pricing

THE JOURNAL OF FUTURES MARKETS, Issue 10 2002
Richard HeaneyArticle first published online: 13 AUG 200
The pricing of commodity futures contracts is important both for professionals and academics. It is often argued that futures prices include a convenience yield, and this article uses a simple trading strategy to approximate the impact of convenience yields. The approximation requires only three variables,underlying asset price volatility, futures contract price volatility, and the futures contract time to maturity. The approximation is tested using spot and futures prices from the London Metals Exchange contracts for copper, lead, and zinc with quarterly observations drawn from a 25-year period from 1975 to 2000. Matching Euro-Market interest rates are used to estimate the risk-free rate. The convenience yield approximation is both statistically and economically important in explaining variation between the futures price and the spot price after adjustment for interest rates. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:1005,1017, 2002 [source]

Minimum variance cross hedging under mean-reverting spreads, stochastic convenience yields, and jumps: Application to the airline industry

THE JOURNAL OF FUTURES MARKETS, Issue 8 2009
Mark Bertus
Exchange traded futures contracts often are not written on the specific asset that is a source of risk to a firm. The firm may attempt to manage this risk using futures contracts written on a related asset. This cross hedge exposes the firm to a new risk, the spread between the asset underlying the futures contract and the asset that the firm wants to hedge. Using the specific case of the airline industry as motivation, we derive the minimum variance cross hedge assuming a two-factor diffusion model for the underlying asset and a stochastic, mean-reverting spread. The result is a time-varying hedge ratio that can be applied to any hedging horizon. We also consider the effect of jumps in the underlying asset. We use simulations and empirical tests of crude oil, jet fuel cross hedges to demonstrate the hedging effectiveness of the model. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:736,756, 2009 [source]