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Eugene F. Fama, 2013 Nobel Laureate in Economic Sciences, is the Robert R. McCormick Distinguished Service Professor of Finance at the University of Chicago Booth School of Business. Widely regarded as the "father of modern finance," his work on the efficient markets hypothesis and risk-return relationships has profoundly influenced both academic and investment communities. Bachelor's, Tufts University (1960) MBA and PhD, University of Chicago Graduate School of Business (1964) Fama's research centers on theoretical and empirical finance, focusing on asset pricing models, market efficiency, and portfolio management. His recent publications emphasize factor investing, including the development of five-factor models and the analysis of international market anomalies. Key trends in his scholarship include empirical validation of the Capital Asset Pricing Model (CAPM), international factor analysis, and the distinction between luck and skill in mutual fund performance. His work remains foundational for quantitative finance and investment strategies. Scientific Awards and Fellowships Nobel Prize in Economic Sciences (2013) Deutsche Bank Prize in Financial Economics (2005) Morgan Stanley American Finance Association Award for Excellence in Finance (2007) Onassis Prize in Finance (2009) Chaire Francqui (1982) Nicholas Molodovsky Award from CFA Institute (2006) Fred Arditti Innovation Award (2007) Fellow of the American Finance Association (2001) Fellow of the Econometric Society Fellow of the American Academy of Arts and Sciences Fama serves as Advisory Editor for the Journal of Financial Economics and has mentored numerous PhD students through his academic career. His research continues to shape financial theory and practice, with ongoing analysis of market efficiency and factor-based investing.

• Finance
• Investments
• Capital Markets
• +5 more

John C. Heaton is the Myron S. Scholes Distinguished Service Professor of Finance at the University of Chicago Booth School of Business and Director of the Anthony Pritzker Family Foundation - Family Office Initiative. He joined Chicago Booth in 2000 after serving as the Nathan S. and Mary P. Sharp Distinguished Professor of Finance at Northwestern University's Kellogg School of Management, with additional positions at MIT's Sloan School of Management and the Hoover Institution. Heaton maintains an active research affiliation as a research associate of the National Bureau of Economic Research. His educational background includes: Bachelor's degree in commerce from the University of Windsor (1982) Master's degree in economics from the University of Western Ontario (1984) PhD in economics from the University of Chicago (1989) Heaton's research program centers on asset pricing, portfolio allocation, and time-series econometrics , with particular emphasis on understanding how macroeconomic fluctuations affect financial markets. His work investigates the long-run risk-return tradeoff in asset valuation and how background risks from labor and entrepreneurial income influence investment decisions. He approaches these questions through rigorous econometric analysis combined with economic theory, seeking to bridge the gap between academic research and practical investment challenges. Analysis of Heaton's publications reveals a consistent focus on market frictions and their implications for asset pricing and portfolio choice. His research demonstrates how transaction costs, borrowing constraints, and incomplete markets affect investor behavior and market outcomes. A distinctive contribution is his work on long-run risk components that influence asset valuations despite being realized far into the future. Heaton's scholarly achievements have been recognized through: Alfred P. Sloan Research Fellowship (1993-1995) National Science Foundation Fellowship (1993-1998) Ongoing research affiliation with the National Bureau of Economic Research As an educator, Heaton teaches advanced courses in asset pricing, financial instruments, fixed income, and investments, with a focus on connecting theoretical frameworks to real-world investment challenges. His directorship of the Family Office Initiative reflects his expertise in wealth management across generations. His research continues to influence both academic discourse and practical approaches to understanding risk in financial markets, with current teaching commitments extending through 2026.

• Asset pricing
• Portfolio allocation
• Time series econometrics
• +3 more

Francisco Martinez Sanchez is Professor in the Department of Quantitative Methods for Economics and Business at Universidad de Murcia's Faculty of Economics and Business. His research focuses on industrial organization, intellectual property protection, competition policy, and game theory applications in software markets and media industries. He leads the Time Series and Econometrics research group. His extensive publication record examines piracy economics, market competition, privatization policies, and behavioral economics. Education includes a PhD from Universitat d'Alacant (2008) on commercial piracy economics. Contact: fms@um.es

• Industrial Organization
• Game Theory
• Competition Economics
• +2 more

Pedro Galeano is an Associate Professor in the Department of Statistics at Universidad Carlos III de Madrid (UC3M) since 2009. He holds a PhD in Statistics (2004) under Prof. Daniel Peña, focusing on multiple time series. Previously, he served as Visiting Assistant Professor of Statistics and Econometrics at the University of Chicago’s Graduate School of Business and as a Postdoctoral Fellow at the Department of Statistics and Operations Research at Universidade de Santiago de Compostela. His research focuses on time series analysis, outlier detection, Bayesian inference in financial models, and functional data analysis with applications to missing data. He is an Associate Editor of the Journal of Time Series Analysis and advises the Heliyon journal. Key contributions include developing methodologies for detecting structural breaks, modeling systemic risk via copula approaches, and advancing robust statistical techniques for high-dimensional data. Active in academic leadership, Galeano co-organized the NICDA Workshop 2025 and has published extensively on topics like dynamic factor models, sequential parameter change detection, and functional data applications in energy markets. His work bridges theoretical statistics with practical applications in finance, economics, and environmental science.

• Outlier Detection
• Time Series Analysis
• Bayesian Inference
• +3 more

Cecilio Tamarit is a Professor of Applied Economics at the University of Valencia, where he holds a Jean Monnet Chair and coordinates the Research Group on Economic Integration (INTECO). He is also Vice President of the Free Association of Economics (ALDE) and President of the Economics Committee of the National Commission for the Evaluation of Research Activity (CNEAI). Master's in Economics, College of Europe (Bruges) Extraordinary Doctorate Award, University of Valencia (1992) Schuman Scholar, European Parliament (1988) Visiting Scholar, University of Nottingham (1992) Senior Fellow, Wharton School, University of Pennsylvania (1996) His research focuses on applied economics, macroeconomics, and European economic integration, with strong emphasis on modeling and policy analysis. He has contributed extensively to understanding economic convergence, fiscal policy, and international trade dynamics within the EU framework. The 15 most recent publications reflect a consistent focus on empirical and policy-oriented economics, spanning macroeconomic modeling, international trade, public policy, and financial economics. His work frequently appears in high-impact journals, demonstrating sustained scholarly engagement in applied economic research. Scientific Awards: Extraordinary Doctorate Award in 1992 from the University of Valencia He has advised numerous research projects and led major evaluation initiatives in economic research. While specific grants are not listed, his leadership roles in national evaluation bodies and research groups suggest significant involvement in funded research and policy advising. He has directed the European Documentation Center at the University of Valencia and served as an advisor to the Spanish government. He leads the INTECO research group, focusing on economic integration and policy modeling, contributing to both academic and policy debates in European economics.

• Applied Economics
• Economic Integration
• Macroeconomics
• +4 more

Dacheng Xiu is the Joseph Sondheimer Professor of Econometrics and Statistics at the Booth School of Business , University of Chicago, and an Affiliated Faculty in the Department of Statistics. He serves as a Research Associate at the National Bureau of Economic Research and holds editorial roles at journals like Journal of Business & Economic Statistics and Journal of Financial Econometrics . PhD and MA in Applied Mathematics from Princeton University BS in Mathematics from University of Science and Technology of China His research focuses on statistical methodologies for financial data , including risk measurement , portfolio management , and empirical asset pricing using high-frequency data and machine learning . Recent work analyzes text data and large language models for economic forecasting. Editorial leadership includes Co-Editor and Associate Editor roles at top journals like Journal of Finance and Annals of Statistics . His lab ( Risk Lab ) specializes in systemic risk assessment through transaction-level data analysis. 2024 Dimensional Fund Advisors Prize 2023 GSU-RFS FinTech Conference Best Paper Award 2022 Society for Financial Econometrics Fellow 2018 Swiss Finance Institute Outstanding Paper Award

• Financial Econometrics
• Statistics
• Empirical Asset Pricing
• +5 more

Angel Pardo Tornero is a Professor in the Department of Financial Economics and Accounting at the Faculty of Economics, University of Valencia. He is a member of the EFEN (Financial Economics and Energy Finance) research group, where he focuses on carbon markets, energy finance, derivatives, and market microstructure. His research interests lie at the intersection of financial economics and environmental markets, particularly in understanding the dynamics of carbon pricing, speculative behavior, hedging strategies, and the integration of climate risk into financial decision-making. He has extensively studied the European Union Emissions Trading System (EU ETS), analyzing topics such as trader positions, price clustering, volatility, and the role of weather and institutional factors in asset pricing. His recent publications show a strong trend toward carbon finance and sustainable investing, with a focus on whether EUAs constitute a new asset class, the role of carbon in portfolio management, and the macroeconomic implications of carbon pricing. His work combines empirical financial econometrics with practical insights for market participants and policymakers. Scientific awards: No awards mentioned in the provided text. Advising and grants: While specific grants are not listed, Dr. Pardo has supervised PhD research, including his own thesis on financial market integration. There is no mention of current advisees or funded projects in the provided material. Labs and teams: He is actively involved in the EFEN research group, which specializes in financial economics and energy finance, supporting collaborative research in sustainable and energy-related financial markets.

• Financial Economics
• Energy Finance
• Carbon Markets
• +7 more

Maria Antonia Barceló Rado is a Professor at the Department of Economics, University of Girona, and a member of the Research Group on Statistics, Econometrics and Health (GRECS). She is also affiliated with the Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP) and collaborates with the Centre de Recerca en Economia i Salut (CRES) at Pompeu Fabra University. Her research spans methodological advancements in survival analysis, spatio-temporal modeling, Bayesian statistics , and applied work in clinical epidemiology, environmental epidemiology, cardiovascular risk factors, chronic diseases , and cancer epidemiology . She has developed a mixed-methods line combining Real World Data with Real World Evidence for epidemic prevention and detection. Licenciate in Mathematics (Universitat Autònoma de Barcelona, 1995) PhD in Mathematics (University of Girona, 2001) Accredited as Catedràtica d’Universitat (ANECA, 2018) Her recent publications focus on environmental stressors , air pollution effects , and spatio-temporal modeling across Spain. Articles address mental health in adolescents , vaccination equity , Covid-19 impacts , and chronic disease epidemiology . Collaborations include institutions like Johns Hopkins University, Pompeu Fabra University, and hospitals in Bellvitge and Barcelona.

• Survival Analysis
• Spatio-Temporal Modeling
• Bayesian Statistics
• +7 more

Dr. Andrés Modesto Alonso is an Associate Professor in the Department of Statistics at Universidad Carlos III de Madrid, affiliated with the Energy Analytics research group and Flores de Lemus Institute. His work spans computer science, economics, and statistics through advanced time series analysis and energy forecasting methodologies. Primary affiliation: Department of Statistics, UC3M Research groups: Energy Analytics, Flores de Lemus Institute His research focuses on time series analysis , energy forecasting , and statistical clustering with applications in electricity markets, smart grids, and environmental data. Recent publications emphasize deep learning models for energy prediction, dynamic factor models, and market-based distance metrics. Scientific output trends show 15 recent articles (2018-2024) covering topics like: Electricity market price forecasting Smart grid optimization through clustering Adaptive control charts for industrial processes Precision matrix estimation in high-dimensional statistics Extreme value analysis for environmental monitoring Dr. Alonso has supervised multiple theses on time series modeling and classification techniques, while collaborating on grants related to stochastic optimization and responsible AI applications in economic forecasting.

• Time Series Analysis
• Energy Analytics
• Statistical Clustering
• +3 more

Maria Helena Lopes Moreira da Veiga is a Full Professor at Universidad Carlos III de Madrid, affiliated with the Macroeconomic and Financial Prediction and Analysis Research Group within the Statistics Department. Her work bridges economics, statistics, and financial engineering with focus on volatility modeling and macroeconomic forecasting. Principal investigator for geopolitical risk and financial contagion projects (2024-2026, 2019-2020) Key research areas: stochastic volatility models, energy markets, Bayesian methods, outlier detection Collaborates with institutions across Denmark, Portugal, France, Spain, and Canada Her publications demonstrate expertise in financial econometrics, particularly asymmetric volatility models and their applications in energy and stock markets. She employs advanced computational techniques like data cloning and wavelet analysis to address model uncertainty and risk measurement. Current projects focus on climate risk indices, AI-driven economic valuation, and high-dimensional time series prediction. She has received continuous funding from national agencies for uncertainty modeling in macroeconomic and financial contexts since 2006.

• Financial Econometrics
• Macroeconomic Forecasting
• Stochastic Volatility Models
• +3 more

Andreu Sansó Rosselló is a Full Professor of Applied Economics at the University of the Balearic Islands (UIB), where he is affiliated with the Faculty of Economics and Business and the Department of Applied Economics. He previously served as Head of the Department of Applied Economics (2003-2007) and Dean of the Faculty of Economics and Business (2013-2020). He has also held significant positions outside academia, including General Director of Economy for the Government of the Balearic Islands (2007-2011) and Director of the Institute of Statistics of the Balearic Islands (2008-2011). His educational background includes a Degree in Economics and Business from the University of Barcelona (1992) and a PhD in Economics from the University of Barcelona (1996). He previously held academic positions as assistant professor and associate professor at the University of Barcelona, associate professor at UIB, and Professor-tutor at the Open University of Catalonia. Professor Sansó Rosselló's research focuses primarily on econometrics, with specializations in economic statistics and economic time-series analysis. His work spans multiple disciplines including tourism economics, health policy, energy economics, and public finance. He has published extensively in top-tier journals such as Journal of Econometrics, Journal of Business and Economic Statistics, and Tourism Management. His recent work demonstrates a strong interdisciplinary approach, connecting econometric methods with practical applications in tourism, healthcare, and environmental economics. His publications reveal a consistent focus on applying advanced statistical techniques to real-world economic problems, particularly in tourism (7 of his 15 most recent articles) and methodological econometrics (5 articles), with additional contributions to health economics, energy economics, and public finance. Professor Sansó Rosselló leads multiple research initiatives as Main researcher for the Econometrics and Data Science (ECD) Consolidated R+D+I Group and the Economics and Data Science (UECD) R+D+I Unit, while also serving as a Member of the Topological Models for Fuzzy Information Processing (MOTIBO) Consolidated R+D+I Group. He teaches Econometrics, Statistical Learning and Decision-Making, and supervises Final Degree Projects across multiple undergraduate and master's programs at UIB, including the Degree in Business Administration, Double Degree in Business Administration and Law, Double Degree in Business Administration and Tourism, and Master's programs in Big Data Analysis and Data Analytics.

• Econometrics
• Economic Statistics
• Economic Time-Series
• +3 more

Dr. Laleh Tafakori is a Senior Lecturer in the Department of Statistics and Analytics at RMIT University's School of Science. Her research focuses on the intersection of statistical modeling, machine learning, and their applications in healthcare, finance, and environmental science. She is affiliated with the university's City Campus and can be contacted at laleh.tafakori@rmit.edu.au . Her teaching interests include Applied Analytics , Statistical Inference , Time Series Analysis , Mathematical Statistics , Stochastic Processes , and Probability Theory . She actively supervises research projects in areas such as: Healthcare modeling (e.g., diabetes onset prediction, maternal risk assessment) Environmental data analysis (e.g., extreme precipitation estimation via satellite data) Financial risk analysis (e.g., Value-at-Risk forecasting, credit portfolio management) Machine learning applications in complex networks and smart grids Her recent research trends emphasize predictive modeling for public health challenges, leveraging advanced statistical techniques (copula models, functional volatility) and machine learning (CNNs, random forests). She collaborates with institutions worldwide, addressing issues like Saudi Arabia's healthcare indicators and European financial systemic risk. While no formal awards are listed, her work demonstrates impactful contributions to interdisciplinary data science. Dr. Tafakori has advised over 16 students on topics ranging from diabetes epidemiology to edge computing optimization. Her research outputs include 28+ peer-reviewed articles, with a focus on methodological innovation and real-world problem-solving. She maintains active engagement in collaborative projects without explicitly listed grants.

• Applied Analytics
• Statistical Inference
• Time Series Analysis
• +7 more

Dr. Priscila Espinosa Adamez is a Lecturer at the Department of Applied Economics, Faculty of Economics, University of Valencia. Her research focuses on regional economic growth, quantitative policy analysis, and forecasting methodologies. Doctorate in Economics (2024) from University of Valencia Specializes in synthetic control methods and machine learning applications for economic analysis Her work bridges computational techniques with regional economics, particularly analyzing EU fund impacts and banking sector efficiency. She employs entropy-based algorithms for macroeconomic forecast combination and develops automated tools for synthetic index construction. Recent publications highlight her expertise in cross-regional policy evaluation, uncertainty measurement in economic indicators, and machine learning integration for predictive modeling. She contributes to debates on banking infrastructure optimization in Spain through empirical spatial econometric studies.

• Regional Economic Growth
• Quantitative Methods
• Economic Forecasting
• +3 more

José Ignacio Olmeda Martos is a Professor at the Computer Science Department of the University of Alcalá, Spain. His research focuses on artificial intelligence, neural networks, financial modeling, and applications in tourism and e-learning. He leads the CSRG-UAH Cognitive Science Research Group and the AUDITAI Group for AI Software Development. He earned his Ph.D. in 1996 with a thesis on nonlinear financial models under Dr. Sergio Barba-Romero. His work bridges computational methods with real-world challenges in finance, tourism, and education. Research interests include predictive analytics, algorithmic optimization (genetic algorithms, SOMs), and accessibility in digital systems. His contributions span hybrid models in credit scoring, volatility forecasting using neural networks, and e-commerce adoption analysis. Over 25 years, he has published extensively on topics like tourism demand prediction (PLAZA project), web accessibility metrics, and financial market predictability. Key projects include developing internet-based tourism reservation systems for Castilla-La Mancha and applying wavelet filtering in financial time series. His research emphasizes interdisciplinary applications, integrating AI with tourism management and financial engineering. Education: Ph.D., Universidad de Alcalá, 1996 Publications reflect his expertise in computational finance, tourism technology, and machine learning. Despite no listed awards, his work demonstrates sustained impact in both academic and applied domains. Advising and grant activities are not detailed in the provided texts.

• Artificial Intelligence
• Computer Science
• Financial Modeling
• +4 more

Ian Dew-Becker serves as an Adjunct Associate Professor of Finance at the University of Chicago Booth School of Business and as a Senior Economist at the Federal Reserve Bank of Chicago. His academic work centers on theoretical and empirical asset pricing and macroeconomics, with particular emphasis on uncertainty, skewness, and tail risk in economic systems. He received his PhD in economics from Harvard University and has held prior positions at Northwestern University, Duke University, and the Federal Reserve Bank of San Francisco. His educational background includes: PhD in Economics, Harvard University Dew-Becker's research explores how agents form beliefs about economic fundamentals and how these beliefs translate into asset prices and macroeconomic outcomes. He investigates the dynamics of uncertainty and skewness across business cycles, develops novel measures using options data, and examines how production networks propagate economic shocks. His work demonstrates that firm-level uncertainty does not significantly forecast aggregate output, challenging existing models, while revealing how interconnectedness can reduce sensitivity to small shocks while amplifying vulnerability to large ones. Recent studies focus on real-time skewness measurement and tail risk transmission through input-output structures. Analysis of his publication record shows a consistent focus on risk measurement and pricing across financial and macroeconomic domains. Collaborating frequently with Stefano Giglio, he has pioneered methodologies using options data to construct cross-sectional uncertainty indices and measure conditional skewness. His research demonstrates that while exchange-traded options earn negative alphas implying rising risk aversion during downturns, synthetic options show constant risk aversion, suggesting intermediary frictions drive pricing anomalies. Key contributions include establishing empirical regularities about macro skewness and demonstrating how production networks generate left-skewed economic activity. No scientific awards were mentioned in the available information. Information regarding graduate student advising, research grants, or specific funding sources was not provided in the source materials. Dew-Becker teaches the Investments course at Chicago Booth during Autumn quarters but no details about mentored students or grant-supported projects are available. Dr. Dew-Becker actively collaborates with researchers across institutions including Stefano Giglio (Yale University), Andrea Vedolin (London School of Economics), and Bryan Kelly (Yale University), forming a network focused on financial economics and macro-finance linkages. His work bridges theoretical modeling with empirical analysis of market data, particularly options markets, to address fundamental questions about risk and uncertainty in economic systems.

• Asset Pricing
• Macroeconomics
• Uncertainty
• +4 more