Type of Publication: Working paper

Synthesizing Information-driven Insider Trade Signals

Author(s):

Heckmann, Jens; Jacobs, Heiko; Schwarz, Patrick

Publication Date:

2023

Keywords:

Informed trading, insider trading, return predictability, global stock markets

Link to complete version:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4537187

Citation:

Download BibTeX

Abstract

Abstract

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.