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Whence LASSO? A Rational Interpretation
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AI
DOI：10.1287/mnsc.2024.06127.png)
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Abstract
En 中文
This paper develops an economic setting to rationalize the use of the least absolute shrinkage and selection operator (LASSO) in estimating asset returns. In this setting, multiple traders engage in trading based on information extracted from historical asset prices. Facing model uncertainty in forecasting asset returns, these traders adopt robusttrading strategies. Within this context, the use of LASSO for estimating asset returns emerges endogenously as an equilibrium outcome. We further extend our analysis to rationalize the application of elastic-net estimation. Although LASSO-type strategies enhance traders' profits by mitigating competition among them, they also introduce biases in trading decisions, which can adversely affect profitability. This dual effect highlights the nuanced tradeoffs associated with employing such estimation techniques in financial markets.
Keywords:
LASSO
model uncertainty
robust optimization
supracompetitive profits
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