Multi-(Horizon) Factor Investing with AI
Factor investing in equities, studied by Goyenko and Zhang in 2022 with a large language model. The abstract mentions transaction costs but not a benchmark, an out-of-sample test, multiple testing or the size of the universe.
“We apply this tech-engine, adapted for finance applications, to multi-factor investing by a long-horizon investor who uses bigger that traditionally used data and takes into consideration long-term versus short-term volatility, liquidity and trading costs trade offs while maximizing expected portfolio returns.”
AssetEquities
StrategyFactor investing
TechniqueLarge language model
InputsFundamentals
Also stated: costs
Missing from abstract: benchmark, out-of-sample test, multiple testing, universe
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The paper's neighbourhoodFactor investing by year
FamilyFactor investing240Momentum and trend following289Machine learning return prediction153News sentiment and text signals14818 more · 854
AssetEquities196
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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