Commodity Futures Volatility (Finance)

The definition of a commodity (by the Commodity Futures Trading Commission) includes all goods, articles, services, rights, and interest in which contracts for future delivery are dealt. However, another approach extracts the financial instruments (interest rate, equity, and foreign currency) leaving those assets more commonly referred to as commodities, that is agricultural (such as grains and livestock), metals (such as copper and platinum), and energy (such as crude oil and natural gas).

Early studies of commodity futures identified several factors that have an impact on volatility, including effects due to contract maturity, contract month, seasonality, quantity, and loan rate. For the contract maturity theory, Samuelson (1965) suggested that futures contracts close to maturity exhibit greater volatility than futures contracts away from maturity. The intuition for this idea is that contracts far from maturity in corporate a greater level of uncertainty to be resolved and therefore react weakly to information. On the other hand, the nearer contracts tend to respond more strongly to new information to achieve the convergence of the expiring futures contract price to the spot price.

The seasonality theory is also grounded in the resolution of uncertainty, but is approached by Anderson and Danthine (1980) in the framework of the simultaneous determination of an equilibrium in the spot and futures markets based on supply and demand. As explained by Anderson (1985), during the production period, supply and demand uncertainty are progressively resolved as random variables are realized and publicly observed. Thus ex ante variance of futures price is shown to be high (low) in periods when a relatively large (small) amount of uncertainty is resolved. For agricultural commodities, particularly the grains, crucial phases of the growing cycle tend to oc cur at approximately the same time each year leading to a resolution of production uncertainty that follows a strong seasonal pattern. Seasonality on the demand side is explained on the basis of substitute products, which also exhibit production seasonalities. Under the general heading of ”seasonality” are various studies of such aspects as month-of-the -year effect, day-of-the-week effect, and turn-of-the-year effect.

The contract month effect explained by Milonas and Vora (1985) suggests that an old crop contract should exhibit higher variability than a new crop contract due to delivery problems (squeezes) when supply is low.

Quantity and loan rate effects are an artifact of the government farm programs. Government involvement in price support and supply control in the grain market can have an impact on volatility as follows. A major component of price support is the loan, whereby a producer who participates may obtain a loan at the predetermined loan rate (dollars per bushel) regardless of the cash market price. If cash prices do not rise above the loan rate plus storage and interest costs, the producer forfeits the grain to the government to satisfy the loan. As a result, the program tends to put a floor on the cash and futures price near the loan rate and thus, as prices decline to the loan rate level, price volatility should decline. Additionally, when production and ending inventories are relatively large (quantity effect), the cash and futures prices have a tendency to be supported by the loan program, and once again, volatility should decrease.

Several empirical tests of these hypotheses have been conducted, of which we will mention only a few. First, Anderson (1985) tests the seasonality and maturity effects theories for nine commodities including five grains, soybean oil , livestock, silver, and cocoa. Employing both non-parametric and parametric tests, he finds that the variance of futures price changes is not constant and that the principal predictable factor is seasonality with maturity effects as a secondary factor. Milon as (1986) finds evidence of the contract maturity effect in agricultural s, financials, and metals markets, which shows that the impact of a vector of known or unknown variables is progressively increasing as contract maturity approaches. Gay and Kim (1987) confirm day-of-the-week and month-of-the-year effects by analyzing a twenty-nine-year history of the Commodity Re search Bureau (CRB) futures price index. This index is based on the geometric average of tw enty-seven commodities using prices from all contract maturities of less than twelve months for each commodity. Kenyon et al. (1987) incorporate four factors into a model to estimate the volatility of futures prices (seasonal effect, futures price level effect, quantity effect, and loan rate effect). Test results of the model in three grain markets support the loan rate hypothesis, while the quantity effect was insignificant. Once again, seasonality effects are supported.

A recent paper by Crain and Lee (1996) also studies the impact of government farm programs on futures volatility. The test period covers forty-three years (1950-93) with thirteen pieces of legislation and concentrates on the wheat market. Patterns of changes in futures and spot price volatility are linked to major program provision changes, such as allotments, loan rates, and the conservation reserve. Three sub-periods of distinguishable volatility magnitudes seem to exist with the discernible patterns explained as follows. Mandatory allotments contribute to low volatility, voluntary allotments and low loan rates contribute to higher volatility, and both market-driven loan rates and conservation reserve programs induce lower levels of volatility. Seasonality is also confirmed in this study, but the seasonality effects do not seem to be as important as farm program impacts. Additionally, there is evidence of changing seasonality patterns over the three defined sub-periods.

Another issue addressed in Crain and Lee (1996) concerns the price discovery role of futures markets. In particular, the wheat futures market has carried out this role by transferring volatility to the spot market. This is consistent with previous studies in other markets, such as equity, interest rate, and foreign exchange markets. Also, there is some evidence that the causal relationship has been affected by the farm programs.

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