The Return–Volatility Relation in Commodity Futures Markets

Abstract

By employing a continuous time multi-factor stochastic volatility model, the dynamic relation between returns and volatility in the commodity futures markets is analyzed. The model is estimated by using an extensive database of gold and crude oil futures and futures options. A positive relation in the gold futures market and a negative relation in the crude oil futures market subsist, especially over periods of high volatility principally driven by market-wide shocks. The opposite relation holds over quiet periods typically driven by commodity-specific effects. According to the proposed convenience yield effect, normal (inverted) commodity futures markets entail a negative (positive) relation.

Pricing of long-dated commodity derivatives: Do stochastic interest rates matter?

“…Factors with higher η i drive mainly the short end of the term structure. Furthermore, in line with Dennis, Mayhew, and Stivers (2006) and Chiarella et al (2016), the negative correlations in Period 1 and 2 imply a negative return-volatility relationship in the crude oil futures markets over these periods leading up to the GFC, where systematic market wide shocks impact the market. The more quiet Period 3 displays a positive return-volatility relationship consistent with the fact that the market was mostly in backwardation.…”

“…The constant volatility model fits futures prices better, but fitting to option prices improves significantly when a stochastic volatility model is considered. Chiarella, Kang, Nikitopoulos, and Tô (2016) present an alternative approach to study the return-volatility relationship in commodity futures markets and analyse this relation in the crude oil futures markets and the gold futures markets. However, most of these studies assume deterministic interest rates, thus they may not be suitable for the evaluation of long-dated contracts.…”

Can volume predict Bitcoin returns and volatility? A quantiles-based approach

“…While the volume-return relationship has been extensively uncovered in equities (Karpoff, 1987;Li et al, 2016), bonds (Balduzzi et al, 2001), commodities (Chiarella et al, 2016), and interest rate and currency future (Puri and Philippatos, 2008), it remains unexplored in the Bitcoin market. The latter has recently attracted the attention of the media and scholars given the rising importance of Bitcoin not only as an electronic payment system but also as a financial and speculative asset (Kristoufek, 2014).…”

Do Scheduled Macroeconomic Announcements Influence Energy Price Jumps?

“…Using a constant‐volatility jump‐diffusion process, Askari and Krichene () show that oil price dynamics are dominated by a discontinuous jump component. Moving beyond constant volatility, Chiarella, Kang, Nikitopoulos, and Tô () model crude oil futures using a stochastic volatility model. Liu, Chng, and Xu () and Schmitz, Wang, and Kimin () augment the jump factor with a stochastic volatility component and show that both features improve model fit for agricultural and metal futures returns.…”