Fundamentals and Volatility: Storage, Spreads, and the Dynamics of Metals Prices

Ng, Victor; Pirrong, Stephen Craig

doi:10.1086/296630

Cited by 206 publications

(144 citation statements)

References 17 publications

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“…Thus, the theory of storage implies that a 4 break in the link between nearby and distant futures prices is associated with low inventory and negative cost of carry. Fama and French (1988) and Ng and Pirrong (1994) provide empirical evidence supporting this theory.…”

Section: Pricing and Volatility In Commodity Futures Marketsmentioning

confidence: 62%

Partially overlapping time series: a new model for volatility dynamics in commodity futures

Smith

2005

J of Applied Econometrics

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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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Section: Pricing and Volatility In Commodity Futures Marketsmentioning

confidence: 62%

Partially overlapping time series: a new model for volatility dynamics in commodity futures

Smith

2005

J of Applied Econometrics

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“…Williams and Wright (1991) analyze a quarterly model involving a yearly production of an agricultural commodity and identify that price volatility regularly increases after harvest time until the next one. Ng and Pirrong (1994) also study metals, employ the same proxy for inventory and find that both spot and forward return variances increase with low Forward Curves, Scarcity and Price Volatility in Oil and Natural Gas Markets 03/10/07 inventory. Exploiting the dependence between the current commodity price and the expectation of future prices at a given inventory level, Deaton and Laroque (1992) find that the conditional variance of prices increases with current price and decreases with higher stocks.…”

Section: Introductionmentioning

confidence: 97%

“…Ng and Pirrong (1994) examine four industrial and one precious metals over the period 1986-1992 and use the same proxy for inventory to conclude that fundamentals drive metal prices dynamics.…”

Section: Introductionmentioning

confidence: 99%

Forward curves, scarcity and price volatility in oil and natural gas markets

2009

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The role of inventory in explaining the shape of the forward curve and spot price volatility in commodity markets is central in the theory of storage developed by Kaldor (1939) and Working (1949) and has since been documented in a vast body of financial literature, including the seminal paper by Fama and French (1987) on metals. The goal of this paper is twofold: i) validate in the case of oil and natural gas the use of the slope of the forward curve as a proxy for inventory; in contrast to Fama and French however, our slope is defined in order to filter out seasonality. ii) analyze directly for these two major commodities the relationship between inventory and price volatility. In agreement with the theory of storage, we find the negative correlation to be significant during those periods when the inventory is below the historical average (scarcity). Our results are illustrated by the analysis of a 20 year-database of US oil and natural gas prices and inventory.Forward Curves, Scarcity and Price Volatility in Oil and Natural Gas Markets 03/10/07

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“…As Duffie and Gray (1995) point out, the commodity spot price volatilities are strongly heteroskedastic and closely reflect the supply, demand and inventory conditions in the market. In particular, price volatilities are increasing with the degree of backwardation (see Ng and Pirrong (1994) and Litzenberger and Rabinowitz (1995)). That is, the stronger the backwardation is the higher the convenience yield is.…”

Section: Valuation Modelmentioning

confidence: 99%

“…In particular, price volatilities are increasing with the degree of backwardation (see Ng and Pirrong (1994)) and Litzenberger and Rabinowitz (1995)). These mis-specifications may generate severe option mispricings, as pointed out by Pirrong (1998), Clewlow and Strickland (2000) and Routledge et al (2000).…”

Section: Introductionmentioning

confidence: 99%

A Two-Factor Model for Commodity Prices and Futures Valuation

Ribeiro¹,

Hodges

2004

SSRN Journal

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This paper develops a reduced form two-factor model for commodity spot prices and futures valuation. This model extends the Gibson and Schwartz (1990)-Schwartz (1997) two-factor model by adding two new features. First the Ornstein-Uhlenbeck process for the convenience yield is replaced by a Cox-Ingersoll-Ross (CIR) process. This ensures that our model is arbitrage-free. Second, spot price volatility is proportional to the square root of the convenience yield level. We empirically test both models using weekly

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Fundamentals and Volatility: Storage, Spreads, and the Dynamics of Metals Prices

Cited by 206 publications

References 17 publications

Partially overlapping time series: a new model for volatility dynamics in commodity futures

Partially overlapping time series: a new model for volatility dynamics in commodity futures

Forward curves, scarcity and price volatility in oil and natural gas markets

A Two-Factor Model for Commodity Prices and Futures Valuation

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