Explore the vast range of titles available.

This paper presents a novel multivariate mean-reverting jump-diffusion model that incorporates correlated jumps and seasonal effects to capture the complex dynamics of commodity prices. The model also accounts for the interplay between price volatility and convenience yield, offering a comprehensive framework for commodity futures pricing. By leveraging the Feynman–Kac theorem, we derive a partial integro-differential equation for the conditional moment generating function of the log price, enabling an analytical solution for pricing commodity futures. This solution is validated against Monte Carlo simulations, demonstrating high accuracy and computational efficiency. The model is empirically applied to historical futures prices of natural rubber from the Thailand Futures Exchange. Key parameters—including commodity price dynamics, convenience yields, and seasonal factors—are estimated, revealing the critical role of jumps and seasonality in influencing market behavior. Notably, our findings show that convenience yields are negative, reflecting higher inventory costs, and tend to increase with rising spot prices. These results provide actionable insights for traders, risk managers, and policymakers in commodity markets, emphasizing the importance of correlated jumps and seasonal patterns in pricing and risk assessment.

This paper uses a novel dataset of commodity-linked notes (CLNs) to examine the impact of the flows of financial investors on commodity futures prices. Investor flows into and out of CLNs are passed to and withdrawn from the futures markets via issuers' trades to hedge their CLN liabilities. The flows are not based on information about futures price movements but nonetheless cause increases and decreases in commodity futures prices when they are passed through to and withdrawn from the futures markets. These finding are consistent with the hypothesis that non-information-based financial investments have important impacts on commodity prices.

We analyze how institutional investors entering commodity futures markets, referred to as the financialization of commodities, affect commodity prices. Institutional investors care about their performance relative to a commodity index. We find that all commodity futures prices, volatilities, and correlations go up with financialization, but more so for index futures than for nonindex futures. The equity-commodity correlations also increase. We demonstrate how financial markets transmit shocks not only to futures prices but also to commodity spot prices and inventories. Spot prices go up with financialization, and shocks to any index commodity spill over to all storable commodity prices.

This paper explores the impact of investor flows and financial market conditions on returns in crude oil futures markets. I argue that informational frictions and the associated speculative activity may induce prices to drift away from \"fundamental\" values, and may result in price booms and busts. Particular attention is given to the interplay between imperfect information about real economic activity, including supply, demand, and inventory accumulation, and speculative activity in oil markets. Furthermore, I present new evidence that there were economically and statistically significant effects of investor flows on futures prices, after controlling for returns in the United States and emerging-economy stock markets, a measure of the balance sheet flexibility of large financial institutions, open interest, the futures/spot basis, and lagged returns on oil futures. The largest impacts on futures prices were from intermediate-term growth rates of index positions and managed-money spread positions. Moreover, my findings suggest that these effects were through risk or informational channels distinct from changes in convenience yield. Finally, the evidence suggests that hedge fund trading in spread positions in futures impacted the shape of term structure of oil futures prices. This paper was accepted by Wei Xiong, finance.

We introduce a return predictor related to the slope and curvature of the futures term structure: basis-momentum. Basis-momentum strongly outperforms benchmark characteristics in predicting commodity spot and term premiums in both the time series and the cross section. Exposure to basis-momentum is priced among commodity-sorted portfolios and individual commodities. We argue that basis-momentum captures imbalances in the supply and demand of futures contracts that materialize when the market-clearing ability of speculators and intermediaries is impaired, and that it represents compensation for priced risk. Our findings are inconsistent with alternative explanations based on storage, inventory, and hedging pressure.

This paper studies the dynamic interaction between the net positions of traders and risk premiums in commodity futures markets. Short-term position changes are driven mainly by the liquidity demands of noncommercial traders, while long-term variation is driven primarily by the hedging demands of commercial traders. These two components influence expected futures returns with opposite signs. The gains from providing liquidity by commercials largely offset the premium they pay for obtaining price insurance.

We develop a simple model of futures arbitrage that implies that if purchases by commodity index funds influence futures prices, then the notional positions of the index investors should help predict excess returns in these contracts. We find no evidence that the positions of index traders in agricultural contracts as identified by the Commodity Futures Trading Commission can help predict returns on the near futures contracts. Although there is some support that these positions might help predict changes in oil futures prices over 2006–2009, the relation breaks down out of sample.

The authors found that, concurrent with the rapidly growing index investment in commodity markets since the early 2000s, prices of non-energy commodity futures in the United States have become increasingly correlated with oil prices; this trend has been significantly more pronounced for commodities in two popular commodity indices. This finding refiects the financialization of the commodity markets and helps explain the large increase in the price volatility of non-energy commodities around 2008.

Commodity derivatives are becoming an increasingly important part of the global derivatives market. Here we develop a tractable stochastic volatility model for pricing commodity derivatives. The model features unspanned stochastic volatility, quasi-analytical prices of options on futures contracts, and dynamics of the futures curve in terms of a low-dimensional affine state vector. We estimate the model on NYMEX crude oil derivatives using an extensive panel data set of 45,517 futures prices and 233,104 option prices, spanning 4082 business days. We find strong evidence for two predominantly unspanned volatility factors.

We uncover stylized facts of commodity futures' price and volatility dynamics in the post-financialization period and find a factor structure in daily commodity volatility that is much stronger than the factor structure in returns. The common factor in commodity volatility relates to stock market volatility as well as to the business cycle. Model-free realized commodity betas with the stock market were high during 2008–2010 but have since returned to the pre-crisis level, close to 0. While commodity markets appear segmented from the equity market when considering only returns, commodity volatility indicates a nontrivial degree of market integration.