The (adaptive) Lasso in the Zoo - Firm Characteristic Selection in the Cross-Section of Expected Returns
Journal
Working paper
Type
monograph
Date Issued
2017-03-09
Author(s)
Research Team
Faculty of Mathematics and Statistics
Abstract
We find short-term reversal, the twelve-months momentum and research spending scaled by market-value to be the firm characteristics (FC) most robustly selected by the adaptive Lasso in the US cross-section of stock returns. Moreover, the majority of the 68 FC included in our analysis are not considered. Nonetheless, the return process we identify is multi-dimensional, comprising 14 FC. Additionally, our Monte Carlo Simulations indicate that the adaptive Lasso is superior to Lasso and OLS-based selection in panel specifications with a low signal-to-noise ratio. The results are robust to various assumptions. These findings gain support by an empirical out-of-sample factor analysis.
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
SEPS - Quantitative Economic Methods
Refereed
No
Contact Email Address
francesco.audrino@unisg.ch
Eprints ID
250747
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Name
LassoInTheZoo_MessmerAudrino_v137.pdf
Size
1.45 MB
Format
Adobe PDF
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