Synthesizing Information-Driven Insider Trade Signals

Jens Heckmann, Heiko Jacobs, and Patrick Schwarz

♦ We propose a novel approach to synthesize presumably information-driven insider trading signals for the cross-section of stocks. We find that the resulting straightforward composite strategy can often forecast returns in a global sample. This predictability is strongest in equal-weighted portfolios, short holding periods, and insider-buying signals, and it improves further with global diversification. Cross-country analysis reveals that varying insider trading restrictions between countries have limited explanatory power for the performance of the composite strategy. Overall, the results are consistent with a short-term informational advantage of insiders, which might be due to the skillful interpretation of non-private news.

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