Variability in soybean futures prices: An integrated framework

Streeter, Deborah H.; Tomek, William G.

doi:10.1002/fut.3990120609

Cited by 60 publications

(52 citation statements)

References 19 publications

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“…The evidence for either hypothesis, until now, has been far from conclusive. Inverse relationships between speculative activity and agricultural commodity price variability has been found by Peck (1981), Brorsen (1989), and Streeter and Tomek (1992). Bessembinder and Seguin (1993), among others, find a positive relationship between futures market volumes and agricultural commodity price volatility.…”

Section: Financial Investment and Speculationmentioning

confidence: 73%

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What Explains the Rise in Food Price Volatility?

Roache

2010

IMF Working Papers

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This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate.The macroeconomic effects of large food price swings can be broad and far-reaching, including the balance of payments of importers and exporters, budgets, inflation, and poverty. For market participants and policymakers, managing low frequency volatility-i.e., the component of volatility that persists for longer than one harvest year-may be more challenging as uncertainty regarding its persistence is likely to be higher. This paper measures the low frequency volatility of food commodity spot prices using the spline-GARCH approach. It finds that low frequency volatility is positively correlated across different commodities, suggesting an important role for common factors. It also identifies a number of determinants of low frequency volatility, two of which-the variation in U.S. inflation and the U.S. dollar exchange rate-explain a relatively large part of the rise in volatility since the mid-1990s.

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Section: Financial Investment and Speculationmentioning

confidence: 73%

“…Empirical evidence, so far , has been mixed on the effects of inventories (e.g., Streeter and Tomek, 1992). To account for this potential effect, an inventory-to-consumption ratio is included for each commodity.…”

Section: Inventoriesmentioning

confidence: 99%

What Explains the Rise in Food Price Volatility?

Roache

2010

IMF Working Papers

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“…Both studies find a negative relation between the degree of market participation by speculators and futures price volatility. Streeter and Tomek (1992) develop a model with a large 2 Considerable research has been done regarding financial market participation and price volatility using volume as the measure of participation. For example, Clark (1973), Cornell (1981), Tauchen and Pitts (1983), Garcia, Leuthold, and Zapata (1986), and Grammatikos and Saunders (1986) have studied the relationship between volume and volatility in futures markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Market volatility and the demand for hedging in stock index futures

2000

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“…In this case, the broken link means that current demand shocks only affect nearby prices, implying that nearby prices are more volatile (Streeter and Tomek, 1992). When stocks are plentiful, spot and futures prices move together and the effect is less evident.…”

Section: Pricing and Volatility In Commodity Futures Marketsmentioning

confidence: 99%

“…However, Goodwin and Schnepf (2000) study the December contract for corn and the September contract for wheat, rolling each one over to the next 5 year in the delivery month. Streeter and Tomek (1992) go one step further and model jointly the November and March contracts for Soybeans, rolling over to the next year's contract upon maturity. In the following section, I propose an econometric model for all contracts that trade on a given commodity.…”

Section: Pricing and Volatility In Commodity Futures Marketsmentioning

confidence: 99%

Partially Overlapping Time Series: A New Model for Volatility Dynamics in Commodity Futures

Smith

2004

SSRN Journal

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SUMMARYIn commodity futures markets, contracts with various delivery dates trade simultaneously. Applied researchers typically discard the majority of the data and form a single time series by choosing only one price observation per day. This strategy precludes a full understanding of these markets and can induce complicated nonlinear dynamics in the data. In this paper, I introduce the partially overlapping time series (POTS) model to model jointly all traded contracts. The POTS model incorporates timeto-delivery, storability, seasonality, and GARCH effects. I apply the POTS model to corn futures at the Chicago Board of Trade and the results uncover substantial inefficiency associated with delivery on corn futures. The results also support two theories of commodity pricing: the theory of storage and the Samuelson effect.

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Variability in soybean futures prices: An integrated framework

Cited by 60 publications

References 19 publications

What Explains the Rise in Food Price Volatility?

What Explains the Rise in Food Price Volatility?

Market volatility and the demand for hedging in stock index futures

Partially Overlapping Time Series: A New Model for Volatility Dynamics in Commodity Futures

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