Causal Modeling for Finance and Business
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A01=Frank J. Fabozzi
A01=Sergio Focardi
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Product details
- ISBN 9780262054270
- Dimensions: 152 x 229mm
- Publication Date: 04 Aug 2026
- Publisher: MIT Press Ltd
- Publication City/Country: US
- Product Form: Paperback
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A comprehensive look at causality’s theoretical and practical aspects in economics and finance.
In Causal Modeling for Finance and Business, Frank Fabozzi and Sergio Focardi offer a foundation for understanding causal relationships and their importance in complex systems. Topics include the theory of graphs, probabilistic frameworks, structural causal models, algorithms for learning causal structures, and the empirical testing of these models.
The book emphasizes applying and deploying causal models in real-world business and investment scenarios. However, it also offers a novel theoretical perspective on causal modeling. Fabozzi and Focardi argue that causation is not a law of nature, but a characteristic of causal systems. If we accept the modern idea of causation as manipulability, causal systems are characterized by causal relationships as well as purely descriptive functional relationships.
With these arguments in mind, the book addresses a critical gap in understanding and applying causal reasoning in complex systems. While correlations have often been relied upon in data analysis, decision-making in business and economics demands a deeper understanding of causation and functional relationships to drive actionable outcomes.
The book’s objective is to provide a comprehensive resource that bridges foundational theories and practical applications of causal models. By integrating recent advancements in artificial intelligence, probabilistic logic, and graph theory, the authors offer a robust framework for researchers, practitioners, and decision-makers to harness the power of causality in solving intricate problems.
In Causal Modeling for Finance and Business, Frank Fabozzi and Sergio Focardi offer a foundation for understanding causal relationships and their importance in complex systems. Topics include the theory of graphs, probabilistic frameworks, structural causal models, algorithms for learning causal structures, and the empirical testing of these models.
The book emphasizes applying and deploying causal models in real-world business and investment scenarios. However, it also offers a novel theoretical perspective on causal modeling. Fabozzi and Focardi argue that causation is not a law of nature, but a characteristic of causal systems. If we accept the modern idea of causation as manipulability, causal systems are characterized by causal relationships as well as purely descriptive functional relationships.
With these arguments in mind, the book addresses a critical gap in understanding and applying causal reasoning in complex systems. While correlations have often been relied upon in data analysis, decision-making in business and economics demands a deeper understanding of causation and functional relationships to drive actionable outcomes.
The book’s objective is to provide a comprehensive resource that bridges foundational theories and practical applications of causal models. By integrating recent advancements in artificial intelligence, probabilistic logic, and graph theory, the authors offer a robust framework for researchers, practitioners, and decision-makers to harness the power of causality in solving intricate problems.
Frank J. Fabozzi (Author) Frank J. Fabozzi is Professor of Practice at Johns Hopkins Carey Business School. He has held positions at EDHEC Business School, Yale, Princeton, MIT, NYU, and Carnegie Mellon. He is the author of Entrepreneurial Finance and Accounting for High-Tech Companies and Introduction to Fixed-Income Analysis and Portfolio Management, and coauthor of Bond Markets, Analysis, and Strategies, Tenth Edition and Foundations of Global Financial Markets and Institutions, all published by the MIT Press. His forthcoming coauthored books to be published by MIT Press are The Economics of FinTech and Simulation, Optimization, and Machine Learning for Finance.Sergio Focardi (Author) Sergio Focardi is a professor at the University of Genoa, DIME, Italy, where he teaches risk management and financial engineering. He is also the founder of the consulting firm Economics and Complexity. Focardi has taught Complexity Economics at Franklin University, Lugano, Switzerland. Previously, he was a professor of finance at the Pole Universitaire Leonard De Vinci, Paris La Defense, France, and a researcher at the De Vinci Research Center after spending three years as a visiting professor of finance at the University of New York at Stony Brook, Long Island, and lecturing at Princeton University. Sergio holds a degree in Electronic Engineering from the University of Genova (Italy) and a PhD in Mathematical Finance from the University of Karlsruhe (Germany). He co-founded the Interdisciplinary Research Center in Economics & Finance at the University of Genova. Sergio is the author or coauthor of 20 books and more than 100 peer-reviewed papers.
