Stochastic Optimal Control and the U.S. Financial Debt Crisis

Nonfiction, Science & Nature, Mathematics, Statistics, Business & Finance, Finance & Investing, Finance
Cover of the book Stochastic Optimal Control and the U.S. Financial Debt Crisis by Jerome L. Stein, Springer New York
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Jerome L. Stein ISBN: 9781461430797
Publisher: Springer New York Publication: March 30, 2012
Imprint: Springer Language: English
Author: Jerome L. Stein
ISBN: 9781461430797
Publisher: Springer New York
Publication: March 30, 2012
Imprint: Springer
Language: English

Stochastic Optimal Control (SOC)—a mathematical theory concerned with minimizing a cost (or maximizing a payout) pertaining to a controlled dynamic process under uncertainty—has proven incredibly helpful to understanding and predicting debt crises and evaluating proposed financial regulation and risk management. Stochastic Optimal Control and the U.S. Financial Debt Crisis analyzes SOC in relation to the 2008 U.S. financial crisis, and offers a detailed framework depicting why such a methodology is best suited for reducing financial risk and addressing key regulatory issues.  Topics discussed include the inadequacies of the current approaches underlying financial regulations, the use of SOC to explain debt crises and superiority over existing approaches to regulation, and the domestic and international applications of SOC to financial crises.  Principles in this book will appeal to economists, mathematicians, and researchers interested in the U.S. financial debt crisis and optimal risk management.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Stochastic Optimal Control (SOC)—a mathematical theory concerned with minimizing a cost (or maximizing a payout) pertaining to a controlled dynamic process under uncertainty—has proven incredibly helpful to understanding and predicting debt crises and evaluating proposed financial regulation and risk management. Stochastic Optimal Control and the U.S. Financial Debt Crisis analyzes SOC in relation to the 2008 U.S. financial crisis, and offers a detailed framework depicting why such a methodology is best suited for reducing financial risk and addressing key regulatory issues.  Topics discussed include the inadequacies of the current approaches underlying financial regulations, the use of SOC to explain debt crises and superiority over existing approaches to regulation, and the domestic and international applications of SOC to financial crises.  Principles in this book will appeal to economists, mathematicians, and researchers interested in the U.S. financial debt crisis and optimal risk management.

More books from Springer New York

Cover of the book Phase Response Curves in Neuroscience by Jerome L. Stein
Cover of the book Search for a Rational Ethic by Jerome L. Stein
Cover of the book Metal-Dielectric Interfaces in Gigascale Electronics by Jerome L. Stein
Cover of the book Empirical Agent-Based Modelling - Challenges and Solutions by Jerome L. Stein
Cover of the book 3D-TV System with Depth-Image-Based Rendering by Jerome L. Stein
Cover of the book Regression Modeling Strategies by Jerome L. Stein
Cover of the book Affect Regulation Training by Jerome L. Stein
Cover of the book Magnetic Resonance Elastography by Jerome L. Stein
Cover of the book Hedgehog signaling activation in human cancer and its clinical implications by Jerome L. Stein
Cover of the book Come On! by Jerome L. Stein
Cover of the book Spectral and Dynamical Stability of Nonlinear Waves by Jerome L. Stein
Cover of the book Studies on the Cornea and Lens by Jerome L. Stein
Cover of the book Open Government by Jerome L. Stein
Cover of the book Advances in Biology and Therapy of Multiple Myeloma by Jerome L. Stein
Cover of the book Information Retrieval: A Health Care Perspective by Jerome L. Stein
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy