Comparing Hedging Effectiveness: An Application of the Encompassing Principle

An empirical methodology is developed for statistically testing the hedging effectiveness among competing futures contracts. The presented methodology is based on the encompassing principle, widely used in the forecasting literature, and applied here to minimum variance hedging regressions. Intuitively, the test is based on an alternative futures contract's ability to reduce residual basis risk by offering either diversification or a smaller absolute level of basis risk than a preferred futures contract. The methodology is easily extended to cases involving multiple hedging instruments and general hedge ratio models. Empirical applications suggest that the encompassing methodology can provide information beyond traditional approaches of comparing hedging effectiveness.cross-hedging, encompassing, hedging effectiveness, Research Methods/ Statistical Methods,

A BAYESIAN APPROACH TO OPTIMAL CROSS-HEDGING OF COTTONSEED PRODUCTS USING SOYBEAN COMPLEX FUTURES

Cottonseed crushers face substantial risk in terms of input and output price variability and they are limited in their planning by the lack of viable futures markets for cottonseed or cottonseed products. This study examines the feasibility of cross-hedging cottonseed products using soybean complex futures. Bayesian tests for market efficiency are performed on the cash and futures prices. The test results reject the presence of nonstationary roots, leading to the conclusion that the markets are not efficient. Different cross-hedging strategies are designed and analyzed for eight different hedging horizons in order to maximize the expected profit and utility of the crusher. A Bayesian approach is employed to estimate the parameters, which is consistent with expected utility maximization in the presence of estimation risk. The investigation reveals that both whole cottonseed and cottonseed products can be successfully cross-hedged using soybean complex futures. The profitability of cross-hedging cottonseed products depends not only on the appropriate size of the contract but also on the optimal choice of strategy consistent with the time of placing and lifting hedge and the appropriate hedging horizon.Marketing,

BALANCING FOOD VALUES: MAKING SUSTAINABLE CHOICES WITHIN COOKING PRACTICES

Within user-centred design and topics such as persuasive design, pleasurable products, and design for sustainable behaviour, there is a danger of over-determining, pacifying or reducing people’s diversity. Taking the case of sustainable food, we have looked into the social aspects of cooking at home, in specific related to the type of food that is purchased. This paper describes what it means for people to make more sustainable choices in food shopping and how that can be mediated while taking different ‘food values’ that household members have into account. In a design experiment, we developed a service for selecting daily dinner meals while supporting choices of sustainable food which reported on environmental impact, health and nutrition values, and purchase data. Through visualizations of alternative food choices, the experiment provided a space for households to negotiate food values, while opening up possibilities for changing cooking practices

Carrots and sticks for new technology: Abating greenhouse gas emissions in a heterogeneous and uncertain world

Many governments use technology incentives as an important component of their greenhouse gas abatement strategies. These “carrots” are intended to encourage the initial diffusion of new, greenhouse-gas-emissions-reducing technologies, in contrast to carbon taxes and emissions trading which provide a “stick” designed to reduce emissions by increasing the price of high-emitting technologies for all users. Technology incentives appear attractive, but their record in practice is mixed and economic theory suggests that in the absence of market failures, they are inefficient compared to taxes and trading. This study uses an agent-based model of technology diffusion and exploratory modeling, a new technique for decision-making under conditions of extreme uncertainty, to examine the conditions under which technology incentives should be a key building block of robust climate change policies. We find that a combined strategy of carbon taxes and technology incentives, as opposed to carbon taxes alone, is the best approach to greenhouse gas emissions reductions if the social benefits of early adoption sufficiently exceed the private benefits. Such social benefits can occur when economic actors have a wide variety of cost/performance preferences for new technologies and either new technologies have increasing returns to scale or potential adopters can reduce their uncertainty about the performance of new technologies by querying the experience of other adopters. We find that if decision-makers hold even modest expectations that such social benefits are significant or that the impacts of climate change will turn out to be serious then technology incentive programs may be a promising hedge against the threat of climate change.climate change, technology policy, uncertainty, agent-based modeling, exploratory modeling, social interactions

Underpinnings for Prospective, Net Revenue Forecasting in Hog Finishing: Characterizing the Joint Distribution of Corn, Soybean Meal and Lean Hogs Time Series

This research focuses on developing a biannual net revenue forecasting model for hog producers based on Monte Carlo simulation of the joint distribution of hog, corn and soybean meal price series. The relative forecasting power of historical volatility, implied volatility and GARCH-based volatility is examined. Consistent with recent research, the performance of these three methods is both commodity and horizon specific, which means there is no single best predictor. However, implied volatility often performs well. Thus, implied volatility is used to forecast variance. Historical covariance is introduced to capture the co-movement of the three price series. Our forecasting model performs well out of sample; most of the realized net revenues fall in 95 percent prediction interval. Based on this forecasting model and the assumption of a utility function, we compare our prospective evaluation with retrospective evaluation of risk management strategies. Though prospective evaluation is not significantly superior to retrospective evaluation for this particular dataset, it is useful because all the market information has been incorporated in this model and because it did protect producers from adverse price movements.Agricultural Finance, Livestock Production/Industries,

FRACTAL GEOMETRY IN AGRICULTURAL CASH PRICE DYNAMICS

Agricultural prices are determined by natural and socio-economic factors that are known to be self-similar at different time scales and to follow non-periodic cyclical patterns. These properties are most easily understood using Mandelbrot's fractal geometry, in which a jagged time series is treated as a jagged coastline or any other natural phenomenon. The fractal market hypothesis provides the theory needed to explain why fractal structure exists in agricultural prices. Empirical evidence confirms theoretical predictions.Demand and Price Analysis,

The learning technologies of the future: technologies that learn?

Higher Education Institutions (HEIs) operate in a borderless and complex environment, abundant in potentially useful information. The Creating Academic Learning Futures (CALF) research project, carried out in partnership by the University of Leicester and University College Falmouth in the UK, involves the development of approaches and tools for structuring and filtering information, in order to facilitate institutional decision-making in participative and creative ways. One of the aims of the CALF project is to involve students in creating and exploring a variety of plausible ‘alternative futures’ for learning and teaching technologies in higher education. This paper discusses some of the issues that are emerging in the course of the research process and presents ideas for the future, grounded in and emergent from ‘student voices’ from the CALF research project. Students expected the technologies of the near future to enable them to become co-creators in their own education processes. The future scenarios imagined the rise of learning technologies which instead of becoming outdated with use, become more valuable as more user-generated content is invested, technologies which are truly learning in that they learn about their users and constantly morph/adapt to their users’ needs. Finally, increasing virtualisation was a recurrent theme across most student-generated scenarios. The paper concludes with a discussion of some of the strengths and limitations of using technologies for involving students in creative activities for generating future scenarios for higher education. The technologies used by the project enabled collaborative creative thinking across a broader spectrum of possibilities about the relationship between the present and the future of higher education

NEW GENERATION CO-OPERATIVES (NGC) AS A MODEL FOR VALUE-ADDED AGRICULTURAL PROCESSING IN ALBERTA: APPLICATIONS TO FACTORS AFFECTING CHOICE OF PRICING AND PAYMENT PRACTICES BY TRADITIONAL MARKETING AND NEW GENERATION CO-OPERATIVES

This study examines the factors affecting choice of pricing and payment practices by traditional marketing and new generation co-operatives for commodities delivered by their members. These factors include the demographic variables related to type of co-operative organization, level of competition in commodity market, and risk-return perceptions of members and co-operatives. Data for the analysis were obtained through a mail survey. Questionnaires were send to one hundred and ninety five (195) co-operatives in mid-west states of the U.S.A. and Canada. Altogether 93 co-operatives responded to the survey. Mean score analysis, factor analysis and multinomial logit analysis were done. The results indicate that traditional marketing co-operatives are more likely to choose spot market cash price, while new generation co-operatives are more likely to choose pooling practices. Traditional marketing co-operatives appear to be concerned about the members' cash flow needs and members' uncertainty of return; they are also more responsive to increased competitive level in commodity market. New generation co-operatives are more concerned with avoiding the risk of co-operatives' operating deficits and survival of co-operatives. This has implications for new co-operatives just beginning in business.Agribusiness,

Mean reversion in stock index futures markets: a nonlinear analysis

Several stylized theoretical models of futures basis behavior under nonzero transactions costs predict nonlinear mean reversion of the futures basis towards its equilibrium value. Nonlinearly mean-reverting models are employed to characterize the basis of the SandP 500 and the FTSE 100 indices over the post-1987 crash period, capturing empirically these theoretical predictions and examining the view that the degree of mean reversion in the basis is a function of the size of the deviation from equilibrium. The estimated half lives of basis shocks, obtained using Monte Carlo integration methods, suggest that for smaller shocks to the basis level the basis displays substantial persistence, while for larger shocks the basis exhibits highly nonlinear mean reversion towards its equilibrium value. © 2002 Wiley Periodicals, Inc

The optimal number of contracts in cross- or delta-hedges.

When hedging in futures markets, the hedge instruments typically fail to match the exposed asset or portfolio by expiration date and/or underlying asset. The theoretical variance-minimizing hedge is given by the slope coefficient of the conditional (forward-looking) regression of the spot-price that one is exposed to on the futures price used as a hedge. We explore the hedging performance of simple rules of thumb and of unconditional regressions on past data, focusing on the effect of the choice of observation frequency, sample period, percentage vs. dollar returns, and lead/lag effects. Our findings are the following : (a) the effects of varying the observation frequency, sample period, etc., are much larger than the effects of using GARCH instead of OLS. (b) Regardless of sample size and estimation technique, the exposure is best estimated using percentage returns rather than (dollar) first differences. © In the case of delta hedges, and also a cross-hedges among closely related currencies, regressions are systematically beaten by naïve rules of thumb. (d) This relatively poor performance of regression-based hedges is not just due to errors in data. (e) The optimal estimation technique depends on the situation. For cross-hedges involving two European currencies, high-frequency OLS estimates is flawed by EMS-induced leads and lags among exchange rate changes, and the best regressions are those using monthly data from longish sample periods. For delta-hedges the dominant source of estimation problems seems to be a time-varying relationship between the regression variables, and the best regressions use daily data from short sample periods.Optimal;