I am a Ph.D. candidate in finance from the University of Mannheim. My research focuses on empirical asset pricing and market microstructure.Â
I am on the 2025 finance job market.
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Research Interest
Research Interest
Empirical Asset Pricing,
Market Microstructure
Presented at: 3rd Bonn-Cologne-Frankfurt-Mannheim PhD Conference, DGF conference 2025
Abstract: Could advances in algorithmic trading counterbalance insider information advantage? I test this prediction by exploiting the U.S. SEC Tick Size Pilot Program, where temporarily coarser tick sizes reduced algorithm effectiveness. I find that insider purchases increased by approximately 30% during the program but returned to pre-pilot levels upon its conclusion. These effects are concurrently observed with informed outsider trading moving in the opposite direction, and are concentrated in stocks with above-median pre-pilot algorithmic trading activity. These results underscore the role of algorithmic trading in providing outside investors with competitive edges in trade execution, which offsets insider information superiority.
This table presents results indicating that algorithmic trading shifts informed trading activities from corporate insiders to outsider investors.
The key independent varaible is the predicted changes in algorithmic trading proxies using the quote treatment in the U.S. tick size pilot program as an instrument. The dependent variables are insider purchase intensity (purchaseInShrout), insider purchase propensity (isPurchase), and outsider informed trading intensity (ITI).
These results support the notion that outsider investors could leverage on developments in trade execution technology to offset the informational advantages of insiders.
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