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Synthesizing Information-Driven Insider Trade Signals
Heckmann, Jens; Jacobs, Heiko; Schwarz, Patrick
2023
 

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Keywords :
Informed trading; insider trading; return predictability; global stock markets
Abstract :
[en] We propose a simple approach to synthesize presumably information-driven insider trading signals for the cross-section of stocks. We find that the resulting composite strategy can predict returns, predominantly in equal-weighted portfolios, in our global sample. The results indicate that the benefits of our composite strategy reflect a short-term informational advantage of insiders. Finally, cross-country analysis reveals that varying insider trading restrictions between countries have limited explanatory power for the benefits of the composite strategy.
Disciplines :
Finance
Author, co-author :
Heckmann, Jens;  University of Duisburg-Essen
Jacobs, Heiko;  University of Duisburg-Essen
Schwarz, Patrick  ;  Université de Liège - ULiège > HEC Liège Research > HEC Liège Research: Financial Management for the Future
Language :
English
Title :
Synthesizing Information-Driven Insider Trade Signals
Publication date :
2023
Source :
Available on ORBi :
since 27 August 2024

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