TECHNICAL ANALYSIS IN COMMODITY MARKETS: RISK, RETURNS, AND VALUE

Although there is little academic research that supports the usefulness of technical analysis, its use remains widespread in commodity markets. Much prior research into technical analysis suffered from data-snooping biases. Using genetic programming, ex ante optimal technical trading strategies are identified. Because they are mechanically generated from simple arithmetic operators, they are free of the data-snooping bias common in technical analysis research. These rules are clearly capable of forecasting periods of high and low volatility, but rules generated for corn and soybeans cannot consistently generate profits in the presence of transactions costs. Rules generated for wheat futures produce profits that are weakly significant, both statistically and economically.Technical Analysis, Genetic Algorithms, Commodity Markets, Futures Markets, Marketing,

A strong law of large numbers for branching processes: almost sure spine events

We demonstrate a novel strong law of large numbers for branching processes, with a simple proof via measure-theoretic manipulations and spine theory. Roughly speaking, any sequence of events that eventually occurs almost surely for the spine entails the almost sure convergence of a certain sum over particles in the population.Comment: 6 page

FORECASTING DAILY VOLATILITY USING RANGE-BASED DATA

Users of agricultural markets frequently need to establish accurate representations of expected future volatility. The fact that range-based volatility estimators are highly efficient has been acknowledged in the literature. However, it is not clear whether using range-based data leads to better risk management decisions. This paper compares the performance of GARCH models, range-based GARCH models, and log-range based ARMA models in terms of their forecasting abilities. The realized volatility will be used as the forecasting evaluation criteria. The conclusion helps establish an efficient forecasting framework for volatility models.Marketing,

A Term Structure Model for Commodity Prices: Does Storability Matter?

Econometric models of commodity prices have been estimated for more than 80 years, but both structural and time series models require ad hoc assumptions to capture all the features of commodity price series. Commodities can be broadly divided into two categories: storable and non-storable. The purpose of this study is to investigate the effects of storability on commodity futures pricing, especially whether meats can be reasonably approximated by storable commodity term structure models. From the empirical analysis of seven commodity futures prices, the two-factor Schwartz model is found to perform well for less storable commodities.Demand and Price Analysis,

Storability on Modeling Commodity Futures Prices

Econometric models of commodity prices have been estimated for more than 80 years, but both structural and time series models require ad hoc assumptions to capture all the features of commodity price series. Commodities can be broadly divided into two categories: storable and non-storable. The purpose of this study is to investigate the effects of storability on commodity futures pricing, especially whether meats can be reasonably approximated by storable commodity term structure models. From the empirical analysis of seven commodity futures prices, the two-factor Schwartz model is found to perform well for less storable commodities.Marketing,

A TERM STRUCTURE MODEL FOR AGRICULTURAL FUTURES

An extension of Schwartz's model of futures price term structure that includes seasonality is developed. The approach allows futures prices for all maturities to be estimated simultaneously by exploiting arbitrage relationships. An application to wheat futures prices is presented.futures markets, price analysis, Demand and Price Analysis, Marketing,

Forecasting Livestock Feed Cost Risks Using Futures and Options

The costs of corn- and soybean-based feeds compose a substantial proportion of the variable costs faced by both mainstream and emergent confined livestock producers. This research develops a method to provide a joint distribution of prices of corn and soybean meal at a future time. Black's 1976 option model and stochastic volatility jump diffusion (SVJD) model are compared in volatility forecasting performance. In general, SVJD is superior to Black's model, though their performance is both commodity-specific and forecasting horizon specific.Livestock Production/Industries, Marketing,

MANAGING DAIRY PROFIT RISK USING WEATHER DERIVATIVES

Replaced with revised version of paper 05/26/04.Risk and Uncertainty,