Google Trends as Alternative Data: A Systematic Review with Implications for the Indian Equity Markets
A 2026 paper by Yeware and Kanade on machine learning return prediction in equities, using a feedforward neural network: the abstract mentions profits and leaves out a benchmark, an out-of-sample test, transaction costs, multiple testing and the size of the universe.
“Studies consistently demonstrate improvements in directional accuracy, cumulative returns, and robustness across time horizons using models such as Elastic-Net, LASSO, neural networks, and hybrid learning architectures [3, 4].”
AssetEquities
StrategyMachine learningnews sentiment
TechniqueFeedforward network
GeographyGlobalIndia
Also stated: Profit, Text and news, Alternative data
Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe
Institutional-grade audit of this strategy.
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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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