Predicting Returns using Production Networks and MLP
Patel (2023) studies machine learning return prediction using a feedforward neural network. The abstract does not mention a benchmark, an out-of-sample test, transaction costs, multiple testing or the size of the universe.
“By utilizing a blend of traditional economic theories and contemporary machine learning approaches, a model is constructed to predict returns by leveraging the inherent structures and data emanating from production networks.”
StrategyMachine learning
TechniqueFeedforward network
GeographyGlobal
Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe
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