جستجوی استاد راهنمای دانشگاهی

Dietmar Maringer is Professor of Computational Economics and Finance at the University of Basel's Faculty of Business and Economics (WWZ), where he leads research at the intersection of finance, computational methods, and artificial intelligence. His work focuses on risk management, portfolio optimization, algorithmic trading, and financial simulations. His research interests span computational finance, artificial intelligence in finance, data analysis, risk management, portfolio optimization, algorithmic and high-frequency trading, financial networks, complex adaptive systems, and market simulations. He applies advanced computational and heuristic optimization techniques to solve real-world financial problems, contributing significantly to quantitative finance and financial engineering. His recent publications demonstrate a consistent focus on applying evolutionary algorithms, reinforcement learning, and numerical optimization to portfolio management, market impact modeling, and financial forecasting. The research integrates econometrics, machine learning, and financial theory, emphasizing practical implementation and robust risk-aware decision-making. Several best-paper awards Maringer has served as Chair of the Portfolio Optimization Section of the IEEE Computational Economics and Finance Technical Committee from 2008 to 2018 and is frequently involved in organizing and program committees of international conferences. He has advised or collaborated with numerous researchers, though specific student names are not listed. His research has been supported through academic affiliations and likely institutional or conference-based grants, though explicit funding sources are not detailed. He is affiliated with several research groups, including IEEE Computational Economics and Finance TC, COMISEF, ERCIM, Centre for Innovative Finance, and the European Financial Management Association, reflecting a broad collaborative network in computational finance and economics.

• Computational Economics
• Computational Finance
• Artificial Intelligence in Finance
• +۸ مورد دیگر

Antonio Mele is a Full Professor of Finance at the Università della Svizzera italiana (USI) and the Swiss Finance Institute (SFI), where he has held a Senior Chair since 2011. He is affiliated with the Faculty of Economic Sciences and the Institute of Finance (IFin) at USI. Additionally, he is a Research Fellow in the Financial Economics program at the Centre for Economic Policy Research (CEPR) in London. Education: PhD in Economics, University of Paris BSc in Economics, LUISS University, Rome Antonio Mele's research spans a wide range of topics in financial economics. His primary areas of expertise include capital market volatility, the interplay between financial markets and the macroeconomy, uncertainty and volatility in financial markets, interest rates and credit markets, and information in securities markets. He also works on econometrics and numerical methods in finance. His recent research interests extend to public debt sustainability, fiscal reforms and financial market behavior, and economic history since World War I. His work is characterized by a strong integration of theoretical modeling, empirical analysis, and practical applications in financial markets. His publications, featured in top journals like the Journal of Financial Economics, Review of Economic Studies, Review of Financial Studies, and Journal of Monetary Economics, reflect a consistent focus on volatility measurement and pricing. Key themes across his 15 most recent works include the development of model-free volatility indices for fixed income markets (such as SRVIX, TYVIX, VXTLT, and Credit VIX), variance swaps, the role of uncertainty in macroeconomic fluctuations, and the design of financial instruments for hedging interest rate and credit risk. His research bridges academic theory and real-world financial innovation. Scientific Awards and Recognition: Research Fellow, Centre for Economic Policy Research (CEPR), London Senior Chair, Swiss Finance Institute (SFI) Member, Group of Economic Advisers, European Securities Markets Authority (ESMA), 2014–2015 Member, Securities and Markets Stakeholder Group, ESMA, 2015–2017 Antonio Mele has had a significant impact beyond academia through his advisory roles and financial innovations. He consulted with central banks and regulatory bodies on capital market volatility, securitization, and credit regulation. He served on ESMA’s advisory bodies between 2014 and 2017. His most notable industry contributions include the co-invention of exchange-traded volatility indices for interest rate swaps, government bonds, and credit markets, adopted by the Chicago Board Options Exchange (Cboe) and S&P Dow Jones Indices. These tools provide real-time measures of uncertainty in fixed income markets and have become standard benchmarks for risk management and trading. He has also authored a major graduate-level textbook on Financial Economics (MIT Press, 2022) and several other books on volatility. Laboratories and Research Teams: Antonio Mele leads research initiatives in financial economics, particularly in the areas of volatility and fixed income markets. He has collaborated extensively with Yoshiki Obayashi on the development of volatility indices and pricing models. His work is associated with the Institute of Finance (IFin) at USI and the Swiss Finance Institute, which serve as hubs for research in finance and macro-finance.

• Financial Economics
• Capital Market Volatility
• Macroeconomics and Financial Markets
• +۱۴ مورد دیگر

Ramin Baghai serves as Associate Professor of Finance at the Stockholm School of Economics, conducting influential research at the nexus of corporate finance, labor economics, and law. His work appears in premier journals including the Journal of Finance, Journal of Financial Economics, and Review of Financial Studies. Education: Ph.D. in Finance, London Business School Research interests reveal a sophisticated integration of disciplines: Corporate Finance : Examines IPOs, mergers, bankruptcy, and credit markets through human capital lenses Corporate Governance : Analyzes credit rating agencies, earnings repatriation, and regulatory impacts on firm behavior Labor-Finance Interface : Pioneers studies on gender disparities in firm shocks, mental health during mergers, and talent retention in distressed firms Law-Economics Synergy : Investigates how wrongful discharge laws and labor regulations shape innovation and corporate strategy Analysis of his 2020-2025 publications indicates a pronounced evolution toward examining social consequences of financial decisions. His recent work increasingly incorporates psychological well-being metrics, gender-disaggregated labor data, and mental health outcomes—transforming traditional finance research into a multidimensional exploration of corporate actions' human impacts while maintaining rigorous analysis of credit markets and governance structures. Scientific Awards: No awards documented in available sources Advising and Grants: Student advising details not disclosed in source materials Grant funding information unavailable in provided texts Labs and Teams: Research collaborations evident through co-authored papers (e.g., with Rui Silva, Marieke Bos), but no dedicated lab or team structures described

• Corporate Finance
• Corporate Governance
• Labor and Finance
• +۲ مورد دیگر

Francis A. Longstaff is a Professor at the University of California, Los Angeles (UCLA) in the Finance Area . His research focuses on finance, fixed income arbitrage, asset pricing, credit risk, corporate finance, and treasury market dynamics . Research Trends: His recent work explores liquidity risk, market efficiency, maturity transformation, municipal bond tax premiums, and macroeconomic-driven prepayment risks. Key themes include nonstandard errors, shadow funding costs, financial sophistication , and the interplay between sovereign debt, systemic risk , and fixed income markets . Collaborative Scope: Longstaff has collaborated with researchers from institutions including Columbia University, Stanford Graduate School of Business, and the National Bureau of Economic Research (NBER), often analyzing treasury bonds, mortgage-backed securities , and credit default swaps in his studies.

• Finance
• Fixed Income Arbitrage
• Asset Pricing
• +۱۳ مورد دیگر

Ludwig B. Chincarini is a Professor in the Department of Finance at the University of San Francisco's School of Management. With an extensive publication record spanning over two decades, his research focuses on practical applications in finance including risk management, hedge funds, and portfolio construction techniques. His work demonstrates consistent scholarly output with recent publications in top finance journals and SSRN working papers. Chincarini's research interests center on quantitative finance, with particular expertise in hedge fund operations, risk management failures (including studies of Amaranth and LTCM collapses), commodities trading, and portfolio optimization techniques. His work bridges academic theory with practical investment applications, often examining real-world market phenomena and financial crises. Recent research has expanded into areas like crowded trades, selectivity theory, and enhanced indexing methodologies. His most notable recent work includes the June 2024 Journal of Finance paper "Nonstandard Errors," which has garnered significant attention with over 17,000 downloads. This multi-author study addresses methodological issues in financial research. His publication pattern shows consistent output with 38 scholarly papers documented on SSRN, reflecting ongoing active research engagement. SSRN Scholarly Papers: 38 Total Downloads: 37,506 Total Citations: 62 SSRN Ranking: Top 1,659 in Total Papers Downloads Chincarini's work demonstrates strong collaborative tendencies, with numerous co-authored papers across various finance subfields. His research has practical implications for portfolio managers, risk officers, and investment professionals navigating complex financial markets. His expertise in hedge fund failures provides valuable lessons for risk management practices in alternative investments.

• Finance
• Risk Management
• Hedge Funds
• +۵ مورد دیگر

Marti G. Subrahmanyam is a Professor of Finance at New York University's Leonard N. Stern School of Business, with additional affiliation at NYU Shanghai. His research focuses on financial markets, derivatives, credit risk, and market microstructure. He maintains an active research agenda with publications in top finance journals including the Journal of Finance and Journal of Financial Economics. His research interests span Financial Markets , Derivatives , Credit Risk , Market Microstructure , Corporate Bonds , Interest Rate Options , and Liquidity . His work often examines the intersection of fixed income markets, monetary policy, and financial regulation. His publication record shows consistent output with 117 scholarly papers and over 66,000 downloads on SSRN. His recent work focuses on central bank interventions, sovereign credit risk, credit default swaps, and market liquidity. His research demonstrates expertise in both theoretical modeling and empirical analysis of financial markets. His most recent publications include Nonstandard Errors (Journal of Finance, 2024), Central Bank-Driven Mispricing (Journal of Financial Economics, 2025), and In Sickness and in Debt: The COVID-19 Impact on Sovereign Credit Risk (2022). Professor Subrahmanyam has collaborated with numerous researchers globally, with affiliations spanning institutions in the United States, Europe, and Asia. His work has significant implications for both academic research and financial market practice.

• Financial Markets
• Derivatives
• Credit Risk
• +۷ مورد دیگر

Paul Schneider is a Full Professor in the Faculty of Economic Sciences at the University of Italian Switzerland (USI), where he has been a faculty member since 2012. He is affiliated with the Institute of Finance (IFin) and the Euler Institute (EUL), contributing to interdisciplinary research in quantitative finance and econometrics. His research focuses on financial econometrics, asset pricing, and statistical methods in finance, with an emphasis on extracting latent market information under minimal assumptions. He integrates techniques from engineering, mathematics, and data science to develop robust models for financial markets. His work spans risk premia, ambiguity in investment decisions, nonlinear pricing, and model-free recovery methods. His recent publications (2023–2024) in journals such as Review of Finance , Management Science , and SIAM Journal on Mathematics of Data Science highlight trends in adaptive learning, empirical scenario generation, constrained likelihood estimation, and optimal investment under ambiguity . These reflect a strong focus on data-driven, computationally efficient, and theoretically sound approaches to financial modeling. Adaptive joint distribution learning Fast empirical scenarios Optimal Investment under Ambiguity Constrained polynomial likelihood Dispersion of Beliefs and Sentimental Recovery Scientific Awards: No specific awards or fellowships are mentioned in the provided text. Advising and Grants: While no formal list of advisees is provided, Paul Schneider has collaborated extensively with researchers such as Damir Filipovic, Fabio Trojani, and Christian Wagner, suggesting a strong mentorship and collaborative role. He has contributed to funded research projects, particularly in financial modeling and econometrics, though specific grant names are not detailed. Labs and Research Teams: He is actively involved with the Institute of Finance (IFin) and the Euler Institute at USI, which support interdisciplinary research in finance, mathematics, and data science. He has also developed computational tools such as the KDM R package for kernel density machines, indicating engagement with data science and open research practices.

• Financial Econometrics
• Asset Pricing
• Statistical Methods in Finance
• +۷ مورد دیگر

Remco C. J. Zwinkels is a Professor at Vrije Universiteit Amsterdam, School of Business and Economics , with affiliations to institutions like Tinbergen Institute and collaborations across global universities including Erasmus University Rotterdam, University of Luxembourg, and Utrecht University. His research bridges finance, economics, and behavioral science. Key affiliations: Vrije Universiteit Amsterdam, Tinbergen Institute, Erasmus University Rotterdam His research focuses on behavioral finance , heterogeneous agent models , market efficiency , and investor sentiment . He investigates how psychological factors and market structures influence asset pricing, exchange rates, and corporate decision-making. Recent work explores climate transition risk (carbon beta), investor attention dynamics (post-COVID-19), and nonstandard errors in market liquidity. His studies often combine empirical analysis, experimental methods, and agent-based modeling. He collaborates with institutions such as Erasmus Research Institute of Management (ERIM), Stockholm School of Economics, and the Bank of Canada. His work appears in journals like the Journal of Finance , Journal of Economic Behavior and Organization , and Journal of Empirical Finance .

• Behavioral Finance
• Asset Pricing
• Investor Sentiment
• +۴ مورد دیگر

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.

• Market Microstructure
• High-Frequency Trading
• Liquidity
• +۵ مورد دیگر

Tony Berrada is a Professor of Finance at the University of Geneva, affiliated with the Geneva Finance Research Institute and the Swiss Finance Institute. He holds a Ph.D. in Finance from the University of Lausanne. Previously, he served as an assistant professor at HEC Montréal and HEC Lausanne, and was a senior visiting fellow at the School of Banking and Finance, Australian School of Business at UNSW. His research focuses on: Asset pricing with incomplete information models Portfolio choice optimization Derivatives pricing mechanisms Behavioral aspects of risk perception and learning Analysis of his recent publications reveals strong emphasis on behavioral finance, sustainable investing, and market anomalies. Key trends include COVID-19 economic impacts, volatility modeling, sustainability-linked bonds, and quantitative arbitrage strategies spanning neuroscience to empirical finance.

• Asset Pricing
• Portfolio Choice
• Derivatives Pricing
• +۱ مورد دیگر