معرفی
Terrence Hendershott is a Professor at the University of California, Berkeley's Haas School of Business, specializing in finance. His research focuses on market microstructure, high-frequency trading, liquidity, and financial market structure. He has published extensively in top finance journals including the Journal of Finance.
- Institution: University of California, Berkeley - Haas School of Business
- Research Focus: Market structure, high-frequency trading, liquidity provision
- Publication Record: Over 40 scholarly papers with significant citations
Professor Hendershott's research interests center around financial market structure, particularly examining how technological changes and regulatory interventions impact market quality. His work spans several key areas including high-frequency trading effects on price discovery, liquidity dynamics in electronic markets, and the structure of over-the-counter markets. He has conducted influential research on how market maker inventories affect liquidity, the role of automation in exchanges, and the impact of short sale bans during financial crises.
His recent publications show a clear trend toward examining electronic trading platforms, with particular focus on corporate bond markets and the transition from traditional dealer networks to more electronic, auction-based systems. His research spans both equity and fixed income markets, with increasing attention to over-the-counter market structure.
Through his extensive publication record in top finance journals, Professor Hendershott has established himself as a leading researcher in market microstructure. His work on high-frequency trading, price discovery, and market liquidity has been widely cited and has influenced both academic research and market regulation.
Professor Hendershott has collaborated with numerous leading finance scholars across institutions worldwide, reflecting the collaborative nature of modern finance research. His work often combines theoretical modeling with extensive empirical analysis using high-frequency market data.