News-based trading strategies
Feuerriegel and Prendinger (2018) study news sentiment and text signals in equities using reinforcement learning. The abstract mentions excess returns, profits and a benchmark but not an out-of-sample test, transaction costs, multiple testing or the size of the universe.
“In this paper, we design trading strategies that utilize textual news in order to obtain profits on the basis of novel information entering the market.”
AssetEquities
StrategyNews sentiment
TechniqueReinforcement learning
ClaimExcess returnprofit
Also stated: Text and news, benchmark
Missing from abstract: out-of-sample test, costs, multiple testing, universe
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The paper's neighbourhoodNews sentiment and text signals by year
FamilyNews sentiment and text signals148Momentum and trend following289Factor investing240Machine learning return prediction15318 more · 854
AssetEquities97
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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