Christina Ray

Extreme Risk Management: Revolutionary Approaches to Evaluating and Measuring Risk

• Gebundenes Buch

Produktbeschreibung

The unprecedented turmoil in the financial markets turned the field of quantitative finance on its head and generated severe criticism of the statistical models used to manage risk and predict black swan events. Something very important had been lost when statistical representations replaced expert knowledge and statistics substituted for causation.
Extreme Risk Management brings causation into the equation. The use of causal models in risk management, securities valuation, and portfolio management provides a real and much-needed alternative to the stochastic models used so far. Providing an alternative tool for risk modeling and scenario-building in stress-testing, this game-changing book uses causal models that help you:

Evaluate risk with extraordinary accuracy
Predict devastating worst-case scenarios
Enhance transparency
Facilitate better decision making

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Produktdetails

• Verlag: McGraw-Hill Professional
• Seitenzahl: 304
• Erscheinungstermin: 28. Juni 2010
• Englisch
• Abmessung: 234mm x 158mm x 26mm
• Gewicht: 578g
• ISBN-13: 9780071700597
• ISBN-10: 0071700595
• Artikelnr.: 27841927

Autorenporträt

Christina Ray is senior managing directorfor Market Intelligence at Omnis Inc. She has over 25 yearsexperience in quantitative finance and is the author of TheBond Market and Think Like a Trader, Invest Like a Pro.

Inhaltsangabe

Introduction: A Profound Transformation in Risk Management
1. Plausibility vs. Probability: Alternative World Views
2. The Evolution of Modern Analytics
3. Risk Management Metrics and Models
4. The Future as Forecast: Assumptions Implicit in Stochastic Risk Measurement Models
5. An Alternative Path to Actionable Intelligence
6. Solutions: Moving Toward a Connectivist Approach
7. An Introduction to Causality: Theory, Models, and Inference
8. Risk Inference Networks: Estimating Vulnerability, Consequences, and Likelihood
9. Securities Valuation, Risk Measurement, and Portfolio Management Using Causal Models
10. Risk Fusion and Super Models: A Framework for Enterprise Risk Management
11. Inferring Causality from Historical Market Behavior
12. Sensemaking for Warnings: Reverse-Engineering Market Intelligence
13. The United States as Enterprise: Implications for National Policy and Security