Crude oil arbitrage and momentum trading strategies with targeting volatility by using Large Language Models
A 2026 paper by Garmash on news sentiment and text signals in commodities, using a large language model: the abstract mentions profits and leaves out a benchmark, an out-of-sample test, transaction costs, multiple testing and the size of the universe.
“Therefore, although high oil prices normally imply high profits for oil exploration and production companies, the uncertainty of price could still significantly impact their strategic investment decisions.”
AssetCommoditiesfutures
StrategyNews sentimentmomentum
TechniqueLarge language modelstate-space model
GeographyGlobal
Also stated: Daily, Profit, Macro, Text and news
Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe
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The paper's neighbourhoodNews sentiment and text signals by year
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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