Do speculators drive commodity prices away from supply and demand fundamentals?

Fishe, Raymond P. H.; Smith, Aaron

doi:10.1016/j.jcomm.2018.09.006

Cited by 4 publications

(5 citation statements)

References 20 publications

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“…There is less evidence that index traders and swap dealers trade based on past futures returns. Fishe and Smith (2019) demonstrate that speculators (more specifically) managed money traders are trend-followers (change position in the same directions as prices) while hedgers are contrarian. 8 The normal backwardation theory postulates that as hedgers seek protection against price changes, they tend to hold short futures positions, while speculators engage in long futures positions and require compensation for bearing the risk.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 92%

Hedging pressure and oil volatility: Insurance versus liquidity demands

Nikitopoulos,

Thomas,

Wang

2023

Journal of Futures Markets

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This study evaluates the dual role of hedging pressure (HP) in oil futures markets and analyses its effects on weekly oil volatility. We find that HP driven by hedgers' insurance demands is negatively related to volatility, while HP driven by speculators' short‐term liquidity demands is positively related to volatility. Oil volatility tends to be more responsive to speculators' short‐term liquidity demands than variations induced by hedgers' insurance demands. These channels are also significant determinants of volatility in inverted and normal markets, with the effects being more pronounced in inverted markets. Under low financial and business‐cycle risk environments, the two HP channels typically have a measurable impact on volatility. These opposing effects of HP on weekly volatility provide empirical support on the significance of the dual role of hedgers in oil markets, as price insurance seekers and as short‐term liquidity providers.

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Section: Literature Review and Hypothesis Developmentmentioning

confidence: 92%

Hedging pressure and oil volatility: Insurance versus liquidity demands

Nikitopoulos,

Thomas,

Wang

2023

Journal of Futures Markets

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“…The majority of the empirical literature on speculation in the commodity markets discusses the impact of financialisation as well as the role of speculators without considering a specific trader group. As a result, the largest part of the empirical literature also comes to the same conclusion (see Boyd et al, 2018;Fishe & Smith, 2019;Kim, 2015;Manera et al, 2013;Mayer et al, 2017;Often & Wisen, 2013;Wimmer et al, 2021). In the context of the increasing world population, this political and ethical discussion about the world's most essential resources remains vivid and primarily concentrates on index-tracking market players to our surprise.…”

Section: Introductionmentioning

confidence: 93%

“…On the other hand, an influence in sub‐samples such as booms and crises can be observed for both commercials and non‐commercials, while the effect is greater for long futures positions. Fishe and Smith (2019) show that money managers including speculators tend to follow commodity prices according to their assessment of the future price development having no price‐influencing impact.…”

Section: Review Of the Literaturementioning

confidence: 99%

Long‐short speculator sentiment in agricultural commodity markets

Borgards

Czudaj

2022

Int. J Fin Econ

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This paper tests the hypothesis that long-short speculators are able to generate short-term investment returns based on their sentiment for twelve agricultural commodity futures. For this purpose, we dynamically model the equidirectional trading of long and short commodity futures of long-short speculators as a proxy for their market sentiment. We find evidence that the sentiment period returns are considerably positive and differ significantly from neutral sentiment periods for all commodities which underlines the sentiment's relevance. In line with the empirical literature, we can reject the argument of price manipulation as the price continues to develop into the direction of the sentiment period although long-short speculators trade non-directionally in the following. We rather indicate the existence of a short-term time-series momentum effect, which can be robustly identified without the requirement to define an external model parameter. From the superior sentiment-based momentum returns, we conclude that long-short speculators have valuable, exclusive information, which cannot be replicated by observing their trading activity with a time lag of eight trading days. We also find that a sentiment-based momentum strategy generates significantly higher returns than the long-short speculators have realized in the fifteen-year sample period which we attribute to the complexity of the long-short speculators' investment strategies.

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“…Other predictors common for various commodities are the U.S. inflation rate, world industrial production, and the world stock index (Kagraoka 2016). Furthermore, financialisation issues were discussed in the context of various commodities (Fishe and Smith 2019;Yan and Yuan 2019). Moreover, the recent economic growth of several emerging economies resulted in increasing the demand for commodities (Labys 2006).…”

Section: General Remarks On Commodity Price Predictorsmentioning

confidence: 99%

Forecasting Selected Commodities’ Prices with the Bayesian Symbolic Regression

Drachal,

Pawłowski

2024

IJFS

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This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities’ prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approach to symbolic regression, based on genetic programming, was also used as a benchmark tool. Secondly, various other econometric methods dealing with variable uncertainty were estimated including Bayesian Model Averaging, Dynamic Model Averaging, LASSO, ridge, elastic net, and least-angle regressions, etc. Therefore, this study reports a concise and uniform comparison of an application of several popular econometric models to forecasting the prices of numerous commodities. Robustness checks and statistical tests were performed to strengthen the obtained conclusions. Monthly data beginning from January 1988 and ending in August 2021 were analysed.

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Do speculators drive commodity prices away from supply and demand fundamentals?

Cited by 4 publications

References 20 publications

Hedging pressure and oil volatility: Insurance versus liquidity demands

Hedging pressure and oil volatility: Insurance versus liquidity demands

Long‐short speculator sentiment in agricultural commodity markets

Forecasting Selected Commodities’ Prices with the Bayesian Symbolic Regression

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