Visualizing Income Statements
Garfinkel, Hribar and Hsiao (2026) study machine learning return prediction in equities using a feedforward neural network. The abstract mentions an out-of-sample test but not a benchmark, transaction costs, multiple testing or the size of the universe.
“We render each firm's income statement as an image that preserves both the numerical values and the spatial structure of its major line items and train a convolutional neural network to extract features that predict post-filing stock returns.”
AssetEquities
StrategyMachine learning
TechniqueFeedforward networkconvolutional network
InputsFundamentals
Also stated: out-of-sample test
Missing from abstract: benchmark, costs, multiple testing, universe
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The paper's neighbourhoodMachine learning return prediction by year
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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