Sentiment Factor in the Cross-Section of Commodity Futures
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Wisdom of Crowds and Commodity Pricing
John Hua Fan; Sebastian Binnewies; Sanuri De Silva
- Griffith University
- ?Griffith University - Department of Accounting, Finance and Economics
- ?Griffith University, Australia
- ?Griffith University - Griffith Business School
Strategy in a nutshell
The strategy trades 28 commodity futures across six sectors using monthly sentiment extracted from Twitter. Commodities with higher sentiment changes are bought, while those with lower changes are sold, forming an equally-weighted long-short portfolio rebalanced monthly.
Economic rationale
The strategy exploits behavioral biases explained by the appraisal-tendency framework, where emotions from prior events affect traders’ decisions, causing systematic mispricing. Correcting these biases generates a return spread between high and low sentiment-change commodities.
Backtest performance
Annualised return7.26%
Volatility9.6%
Sharpe ratio0.75
Maximum drawdown-12.2%
Win rate71%