The dynamics of commodity prices

By Chris Brooks, Marcel Prokopczuk. Quantitative finance (Print), 2013

112 citations recorded by the source corpus.

Abstract In this paper we study the stochastic behavior of the prices and volatilities of a sample of six of the most important commodity markets and we compare these properties with those of the equity market. we observe a substantial degree of heterogeneity in the behavior of the series. Our findings show that it is inappropriate to treat different kinds of commodities as a single asset class as is frequently the case in the academic literature and in the industry. We demonstrate that commodities can be a useful diversifier of equity volatility as well as equity returns. Options pricing and hedging applications exemplify the economic impacts of the differences across commodities and between model specifications.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/b48cb90867a627586858a4f67553cd72a4640d8b

How researchers see this paper

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In Economics and Econometrics

1. Subrata Kumar Mitra
2. Joshua C. C. Chan
3. Angelia L. Grant
4. Debdatta Pal
5. Jin-li Wang
6. Yue‐Jun Zhang

In Finance

1. Subrata Kumar Mitra
2. Joshua C. C. Chan
3. Angelia L. Grant
4. Debdatta Pal

Citations in the corpus

• Modeling energy price dynamics: GARCH versus stochastic volatility (2016, background): “Alternatively, some recent papers have considered stochastic volatility models, where the volatility is a latent variable that follows a stochastic process (see, e.g., Sadorsky, 2005; Vo, 2009; Trolle and Schwartz, 2009; Larsson and Nossman, 2011; Brooks and Prokopczuk, 2013).”
• Bayesian Model Comparison for Time-Varying Parameter VARs with Stochastic Volatility (2018, unknown): “, Yu and Meyer, 2006; Abanto-Valle, Bandyopadhyay, Lachos, and Enriquez, 2010; Mumtaz and Surico, 2012; Brooks and Prokopczuk, 2013). However, this variant has recently been criticized on both theoretical and practical grounds. Li, Zeng, and Yu (2012) argue that the conditional DIC should not be use”
• Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis (2017, background): “…of the traditional investment instruments such as stocks and treasuries, leading to investors starting to explore new assets for higher returns (Brooks and Prokopczuk, 2013); (2) since the factors driving agricultural commodity prices (e.g., weather variations, supply constraints) are…”