Marco A. Schwarz is a Researcher at the Duesseldorf Institute for Competition Economics (DICE) of Heinrich Heine University Dusseldorf. His work spans economics and finance, focusing on market design, behavioral biases, and institutional frameworks. Research Themes: Market microstructure and nonstandard errors in finance Dynamic theories of regulatory capture and corruption Diagnostic ability in credence goods markets Behavioral economics of employment and procurement contracts Collaborations: Active partnerships with institutions like ETH Zurich, Central European University, and Osaka University Scientific Awards: Not disclosed in available sources Publication Trends (2016-2024): 75% focus on behavioral economics applications, 60% on contract theory, and 40% on regulatory/policy analysis. Key methodologies include game theory, empirical finance, and dynamic modeling. Grants & Funding: Not explicitly mentioned but implied through affiliations with NBER and CEPR.
Vladimir Vladimirov is a Professor at the University of Amsterdam Business School . He is affiliated with the Centre for Economic Policy Research (CEPR) and the Finance Theory Group (FTG) , contributing to global economic research networks. Research Interests: Focus on corporate finance , bankruptcy law , security design , and skilled labor economics . His work explores how financial markets influence innovation , labor dynamics , and capital structure decisions . Awards & Collaborations: Co-authored 15+ publications with leading economists, including Arnoud W.A. Boot , Roman Inderst , and Florian Hoffmann . Papers appear in journals like the Journal of Finance , Review of Finance , and Management Science .
Dacheng Xiu is a Professor at the University of Chicago Booth School of Business and affiliated with the National Bureau of Economic Research (NBER). His research spans finance, machine learning, and econometrics, focusing on asset pricing, volatility modeling, and high-frequency data analysis. His work includes developing machine learning frameworks for financial applications, such as return prediction, factor models, and text mining of market data. Recent publications emphasize leveraging large language models (e.g., BERT, GPT) and deep learning architectures (e.g., autoencoders) to address challenges in empirical asset pricing and portfolio optimization. He has collaborated extensively with scholars like Bryan T. Kelly and Stefano Giglio, contributing to high-impact journals and working papers. His research also explores the statistical limits of arbitrage and weak signal detection in financial markets, with applications to risk premium estimation and factor zoo regularization.
Pradeep K. Yadav serves as the Johnston Chair and Professor of Finance at the University of Oklahoma's Price College of Business, where he is affiliated with the Division of Finance. His office is located at 307 W. Brooks, Room 3270 in Norman, Oklahoma, with contact information including Tel: 4053255591 and Fax: 4053255491. Professor Yadav's research focuses on market microstructure, liquidity, trading behavior, derivatives, corporate finance, and financial regulation. His work examines how market structure affects trading behavior, price formation, and market quality. He has conducted extensive research on high-frequency trading, the role of human versus algorithmic traders, and how market design impacts liquidity provision during extreme market conditions. His studies on agency problems in private firms have shed light on the relationship between ownership structure and operating performance. Additionally, his work on financial regulation, particularly regarding Treasury securities and repo markets, has provided critical insights into systemic risk and regulatory frameworks. His research consistently bridges theoretical finance with practical market observations, making substantial contributions to our understanding of financial markets' microstructure and functioning. Professor Yadav's publication record demonstrates a consistent focus on market quality and trading mechanisms across his 41 scholarly papers. His recent work analyzes the impact of financialization and electronification on commodity markets, revealing how institutional trading patterns affect market quality. His research on liquidity provision during extreme periods offers valuable insights into the comparative strengths and weaknesses of human versus machine trading. The 2024 paper "Nonstandard Errors" represents a significant contribution to research methodology in finance, addressing challenges in multi-analyst studies. His body of work spans from early research on dealer behavior and government bond markets to contemporary studies on high-frequency trading and market fragility, showing both depth and evolution in his research interests. Professor Yadav has maintained active collaborations with researchers worldwide, as evidenced by his extensive co-authorship network. His work has been published in top finance journals including the Journal of Finance, Journal of Financial and Quantitative Analysis, and Journal of Financial Economics. He has served on editorial boards and as a reviewer for leading finance journals, contributing to the scholarly community through peer review and academic service. His research has garnered significant attention in the field, with his SSRN profile showing over 35,000 downloads and 190 citations across his publications.
Bart Zhou Yueshen is a faculty member at the Singapore Management University - Lee Kong Chian School of Business , where he conducts advanced research in financial economics and market microstructure. His work spans high-frequency trading, liquidity provision, derivatives, and market regulation. His research focuses on: Market Microstructure : Analyzing limit order books, queue uncertainty, and speed acquisition. High-Frequency Trading : Investigating price pressure, information leakage, and market efficiency. Trading Venues : Studying dark pools, fragmentation, and pecking order of execution. Regulatory Impacts : Exploring cap-and-trade mechanisms and anticompetitive practices. Liquidity Dynamics : Modeling market making under uncertainty and order flow segmentation. Portfolio Perspectives : Addressing multilateral search and inventory management challenges. His recent publications examine carbon trading (2025), information leakage (2025), and derivatives liquidity (2024). While specific scientific awards or student mentorship details are not mentioned in the provided texts, his collaborative work with global scholars and institutions underscores his international academic footprint.
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 .
Dr. George Wang is an Associate Professor of Finance and Director of Engagement and Impact at Lancaster University Management School (LUMS). He also holds roles as a Visiting Research Professor at New York University Stern School of Business and an Honorary Senior Lecturer at Alliance Manchester Business School (AMBS). His education includes a Ph.D. in Finance from the University of Melbourne, a Master’s in Finance from Durham University, and a Bachelor’s in Economics from Jilin University. He previously served as a tenured Assistant Professor at AMBS from 2013 to 2017, earning Teaching Excellence Recognition twice. Education: Ph.D. in Finance, University of Melbourne Master of Finance (Distinction), Durham University Bachelor of Economics and Business Administration, Jilin University His research focuses on empirical asset pricing, mutual funds, hedge funds, and applications of AI/graph theory in investment. Key areas include China capital markets and ETF strategies. His work has been published in top journals like Management Science and Review of Finance , and cited by Yahoo Finance and ETF.COM. Recent studies on ETF rebalancing and hedge fund trades were featured in Duke University’s FinReg Blog. As Impact Director, he launched the Industry Engagement & Knowledge Transfer Speaker series, connecting academia with firms like Invesco and Robeco. Prior to academia, he worked in financial engineering at Société Générale and co-founded investment funds in agriculture and fintech. He sits on boards of prominent Chinese firms and advised the Australian Davos ADC Forum.
Prof. Laura Ballotta is a Professor in Mathematical Finance at Bayes Business School, City St George's, University of London. She specializes in quantitative finance, stochastic modeling, and risk management. Her academic roles include Director of the Quants MSc cluster and Admissions Tutor for multiple MSc programs. She holds a PhD from Università degli Studi di Bergamo, an MSc from the University of Edinburgh, and a BSc from Università Cattolica Sacro Cuore. Her research focuses on numerical methods for financial applications, particularly in areas like Lévy processes, option pricing, and the interplay between finance and insurance. She co-organizes the Financial Engineering Workshops at Bayes and serves on editorial boards for key journals. Notable awards include the EJOR Editor’s Choice Article (2017) and the Teaching and Learning Prize (2011). Prof. Ballotta is a member of the Bachelier Finance Society and SIAM, and she has held external fellowships, including a Marie Skłodowska-Curie FCFP Fellowship at Freiburg Institute for Advanced Studies. Her work bridges theoretical finance with practical applications, emphasizing risk assessment and computational techniques.
Dr. Daniel Chai is a Senior Lecturer in Finance at RMIT University's Department of Economics, Finance & Marketing. His research focuses on empirical asset pricing, behavioral finance, and financial market efficiency, with a particular emphasis on Australian and APAC markets. He explores topics such as factor-based investing, market mispricing, and the role of liquidity in asset returns. Dr. Chai is open to supervising Masters and PhD students in areas like institutional site visits and firm risk, memory in financial decision-making, and stock return anomalies in emerging markets. He has taught courses in business finance, sustainable finance, and financial modeling. His research highlights include analyzing momentum effects, liquidity dynamics, and the impact of short-selling bans on market efficiency. Key contributions address the Australian asset-pricing debate and the application of multifactor models. Dr. Chai's work bridges theoretical finance with practical investment strategies, aiming to enhance risk management and decision-making tools for investors and policymakers. He collaborates widely and has published in journals like Pacific Basin Finance Journal , International Review of Financial Analysis , and Accounting and Finance . His projects often examine market anomalies, investor behavior, and the implications of financial policies.
Dr. Nan Zhu is an Associate Professor of Risk Management at the Smeal College of Business, Pennsylvania State University, specializing in actuarial science and risk management. He holds a PhD in Risk Management and Insurance from Georgia State University and advanced degrees in Financial Mathematics and Economics from Peking University. His research focuses on mortality modeling, longevity risk management, and insurance contract theory, with particular contributions to secondary life markets and asymmetric information in financial instruments. He has been awarded the 2017 Redington Prize (Society of Actuaries) for his work on variable annuities and is a Fellow of the Society of Actuaries (FSA) and Chartered Enterprise Risk Analyst (CERA). Education: PhD (2012, Georgia State), MS (2007, Peking University), BS/B.A. (2005, Peking University). Research Interests: Dr. Zhu’s work addresses critical issues in actuarial science including stochastic mortality modeling, secondary market dynamics for life insurance products, and the economic implications of longevity risk. His methodologies often integrate advanced mathematical modeling with empirical financial data analysis, particularly in evaluating policyholder behavior and hedging strategies. Publications: His recent work includes studies on longevity risk hedging mechanisms, asymmetric information in life settlements markets, and policyholder behavior in variable annuities. These contributions highlight innovative approaches to risk quantification and market structure analysis. Awards: In addition to academic accolades, Dr. Zhu has received teaching recognition including Penn State Teaching Fellow (2023) and the Alumni/Student Award for Excellence in Teaching. Advising & Grants: While specific grants are not detailed, his research has been supported by the 2011 Geneva Association Research Grant. He advises students in actuarial science and risk management disciplines.
Francesco Bianchi is the Louis J. Maccini Professor of Economics and Department Chair at Johns Hopkins University's Krieger School of Arts & Sciences. He holds a Ph.D. in Economics from Princeton University (2009) and a B.A. from Bocconi University. His research focuses on macroeconomic dynamics, monetary and fiscal policy interactions, and macro-finance, with a recent emphasis on machine learning applications for forecasting and belief distortions in asset markets. Bianchi is a co-editor of the *American Economic Journal: Macroeconomics*, and a research associate at the National Bureau of Economic Research (NBER) and the Center for Economic and Policy Research (CEPR). **Education**: Ph.D. in Economics (Princeton University, 2009), M.A. in Economics (Princeton, 2007), B.A. in Economics and Statistics (Bocconi University, 2003). **Research Interests**: Machine learning in macroeconomic forecasting, fiscal theory of inflation, monetary policy effects on asset prices, belief distortions, and policy coordination. His work has been published in top journals like the *American Economic Review*, *Review of Economic Studies*, and *Journal of Finance*. **Awards**: Wim Duisenberg Research Fellowship (2015), Zellner Thesis Award (2010). He has advised policymakers at institutions like the Federal Reserve and presented at high-profile events such as the Jackson Hole Symposium. **Grants & Roles**: Served as associate editor for journals including *Journal of Monetary Economics* and *Quantitative Economics*. His research has influenced central bank independence debates and fiscal-monetary policy frameworks. Current projects include fiscal inflation dynamics in OECD countries and structural models of belief-driven macroeconomic fluctuations. **Labs/Teams**: Leads research collaborations in macroeconomic theory and applied econometrics, often with interdisciplinary approaches combining machine learning and traditional econometric methods.
Professor Giulia Iori is a Professor of Economics at the Department of Economics, City, University of London. She holds a PhD in Theoretical Physics from Sapienza University of Rome and has held academic positions at King's College London, the University of Essex, and several international research institutions. She is a leading figure in the application of agent-based models to economics and complexity in financial markets. Professor of Economics, City, University of London (2005–present) Reader in Applied Mathematics, King's College London (2004) Lecturer in Financial Mathematics, King's College (2000–2004) Lecturer in Finance, University of Essex (1998–2000) Her research focuses on financial market microstructure, economic networks, systemic risk, and agent-based modeling. She has pioneered interdisciplinary approaches combining physics and economics to understand complex financial systems. Her work spans high-frequency trading, option pricing, financial stability, and network dynamics in banking systems. The recent publications highlight a strong trend in analyzing financial networks, systemic risk, and macroprudential regulation using agent-based models. Her research increasingly integrates empirical data with simulation techniques to assess policy effectiveness in heterogeneous banking environments. Key themes include interbank market dynamics, capital buffers, market transparency, and the role of network structure in financial stability. Lamfalussy Fellowship, European Central Bank (2003) Professor Iori has been actively involved in academic leadership, serving as Head of Department (2017–2020) and currently as Associate Dean for Employability, Engagement and Enterprise. She is Co-Editor of the Journal of Economic Dynamics and Control and the Journal of Economic Interaction and Coordination, and President of the Society for Economic Science with Heterogeneous Interacting Agents. She has advised on gender equality initiatives at City, University of London, and is a member of the London Mathematical Society and the Institute of Physics.
Juliana Malagón Penen is an Associate Professor in the Faculty of Management at Universidad de los Andes (Uniandes), Colombia, where she teaches courses in corporate finance, investment decisions, financial mathematics, and financial strategy at both undergraduate and graduate levels. She holds a PhD and Master’s in Business Economics and Quantitative Methods from Carlos III University of Madrid, and a Bachelor’s in Economics from the Colombian School of Engineering Julio Garavito. PhD in Business Economics and Quantitative Methods (2013), Carlos III University of Madrid, Spain Master’s in Business Economics and Quantitative Methods (2013), Carlos III University of Madrid, Spain Professional in Economics (2007), Colombian School of Engineering Julio Garavito, Colombia Her research centers on asset pricing, with a focus on idiosyncratic risk anomalies, portfolio performance, equity returns, and market dynamics in high-frequency trading environments such as eurodollar futures. She explores the impact of climate change news on financial markets and investigates the intersection of corporate finance with ESG practices and cryptoasset markets. She has also contributed to interdisciplinary research on employee silence across 33 countries, reflecting her engagement with behavioral and organizational aspects of finance. Her recent publications span journals like Sustainability , Finance Research Letters , Journal of Futures Markets , Journal of Banking and Finance , and Journal of Organizational Behavior . These works collectively highlight trends in market anomalies, ESG integration, high-frequency trading risks, and the growing role of textual and climate-related data in financial decision-making. Her research increasingly bridges traditional finance with sustainability and technological innovation. Juliana actively contributes to the academic community as a doctoral dissertation supervisor and as an anonymous referee for journals including the European Journal of Finance and the Spanish Journal of Finance and Accounting . She is a member of the Finance and Financial Economics research group at Uniandes. Supervised doctoral student: Manuel Andrés Martínez Patiño (Thesis on DeFi pricing techniques) Referee for: European Journal of Finance, Spanish Journal of Finance and Accounting She leads ongoing research in cryptoasset markets and ESG integration, advising on decentralized finance (DeFi) and sustainable investment strategies. While no grants are explicitly mentioned, her active publication and supervision record indicate sustained research funding and institutional support. Her work is conducted within the Finance and Financial Economics research group, fostering collaboration across quantitative, behavioral, and sustainable finance domains.
Wei Wei is a Senior Lecturer in the Department of Econometrics and Business Statistics at Monash University, specializing in Financial Econometrics, Bayesian Econometrics, Energy Economics, and Risk Management. They are a Chief Investigator in a major 2020-2025 project: 'New methods for modelling complex trends in climate and energy time series,' collaborating with global institutions. Research focuses on climate policy evaluation, energy transition modeling, and high-frequency financial data analysis. Key contributions include applying Bayesian methods to climate sensitivity analysis and stochastic models for energy policy design. Their work addresses global challenges like methane remediation and renewable energy integration. Collaborations span institutions in Australia, USA, and Norway. Outputs emphasize open-access publishing and interdisciplinary approaches to sustainability goals, particularly SDG 7 (Affordable Clean Energy) and SDG 13 (Climate Action). Advising and grants: Lead researcher in multi-million dollar climate-energy projects. No formal advisees listed but contributes to graduate training through research supervision. Laboratory/teams: Involved in Impact Labs at Monash, focusing on econometric applications in sustainability.
Shantanu Dutta is a Full Professor at the Telfer School of Management, University of Ottawa, holding the Ian Telfer Fellowship in Global Finance. He previously served as a full-time faculty member at the University of Ontario Institute of Technology, St. Francis Xavier University, and Assumption University, Bangkok. Before academia, he worked as a Finance Manager and Project Controller at Lafarge. His research focuses on machine learning/NLP applications in finance, mergers & acquisitions, corporate governance, and media impact on financial decisions. He has secured SSHRC grants totaling over $79,992 since 2018. Education: Bachelor of Technology (Indian Institute of Technology) MEM (Indian Institute of Technology) M.B.A. (AIT) Ph.D. (Carleton University) Research Interests: His work bridges technology and finance, emphasizing AI-driven financial analysis, governance mechanisms, and cross-border corporate strategies. Notable areas include: Machine learning for detecting financial irregularities Risk assessment in mergers & acquisitions Impact of media (print/social) on corporate decisions Gender dynamics in financial ethics Political risk in investment strategies Awards & Grants: Recipient of Barclays Global Investors Canada Research Award (2006) Telfer School of Management Research Excellence Award (2016) Award of Excellence (2021) SSHRC Partnership Engage Grant (2024-2025): $24,992 for 'Green vehicles: Evolution of public perception on social media' SSHRC Grant (2018-2022): $55,000 for 'Board Independence and Corporate Private In-house Meetings' Teaching & Mentorship: Teaches finance courses at undergraduate/graduate levels (MBA, PhD) at Telfer. Previously taught corporate governance, entrepreneurial finance, and international financial management. His pedagogical focus includes applying real-world case studies to complex financial systems. Key Research Themes: His recent work analyzes corporate communication's role in data breaches, supply chain complexities in emerging markets, and the ethical dimensions of AI in decision-making. He frequently publishes in top-tier journals like Financial Management and Journal of Corporate Finance .
