Aydogan Alti

Aydogan Alti serves as an Associate Professor of Finance within the Department of Finance at the McCombs School of Business, University of Texas at Austin. His academic career centers on empirical and theoretical research in corporate finance and asset pricing, with particular expertise in market timing phenomena, institutional investor behavior, and characteristic-based return predictability.

Alti's research program explores the intersection of behavioral finance and market microstructure, investigating how investor beliefs influence asset prices and corporate financing decisions. His work frequently employs structural modeling approaches to analyze IPO market timing, equity issuance triggers, and the persistence of market timing effects on capital structure. Key contributions include demonstrating how firms strategically time security offerings based on stock return patterns and identifying mechanisms behind institutional investors' return-chasing behavior.

Analysis of his publication record reveals a consistent focus on empirical finance with strong methodological rigor. His papers predominantly examine cross-sectional return predictability, market anomalies, and the real effects of financial market conditions on corporate policies. Alti frequently collaborates with leading scholars such as Sheridan Titman and Paul Tetlock, producing influential work in premier finance journals.

His scientific recognition includes the prestigious 2022 Q-Group Jack Treynor Prize and the Brattle Prize for Distinguished Paper in the Journal of Finance (awarded twice for separate publications). These awards highlight his contributions to understanding characteristic-based return predictability and corporate financing decisions.

While details about student advisement and research grants are not provided in the source material, Alti's active publication record suggests ongoing supervision of graduate researchers. His current working papers indicate continued investigation into informed intermediation in IPO markets and characteristic-sorted portfolio performance.