Financial Risk Management

An Analytical Approach (First Edition)
Tong Yu and Mark Liu
©2026, 726 pages

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Financial Risk Management

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$102.95

Summary
    Financial Risk Management: An Analytical Approach guides readers on a comprehensive journey through varied dimensions of financial risk, including market risk, credit risk, operational risk, and liquidity risk. It presents a cogent exploration of mathematical models, statistical methods, and computational techniques essential for risk assessment and mitigation. The text highlights the emergence of Python as a pivotal tool for finance professionals in risk analysis, modeling, and decision-making.

    The book provides readers with shrewd insights into industry best practices and advanced methodologies merging the theoretical aspects of risk management with Python's practical applications. Key risk management concepts are paired with real-world applications and supported by Python code samples, case studies, and exercises. This framework equips learners with the knowledge and ability they need to confront contemporary risk management challenges.

    Financial Risk Management serves as a foundational text for those entering the field and an effective guide for practitioners interested in integrating Python programming with financial analyses to enhance decision-making in the discipline. It is an ideal resource for courses and programs in finance and risk management.

    Tong Yu is the Virgil M. Schwarm Professor of Finance at the Lindner School of Business at the University of Cincinnati. His teaching and research interests are in asset pricing, risk management and insurance, Fintech, and investments of institutional investors. He serves as associate editor of Financial Management, Financial Review, Journal of Financial Counseling and Planning, and China Finance Review International.
    Mark Liu is an associate professor of finance with tenure and the founding director of the Master of Science in Finance program at the University of Kentucky. He is the author of four books: Learn Generative AI with PyTorch (Manning Publications, 2024); AlphaGo Simplified (CRC Press, 2024); Machine Learning, Animated (CRC Press, 2023); and Make Python Talk (No Starch Press, 2021). His research interests include machine learning and corporate finance.
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