A revolutionary new approach for detecting and managing inherent risk        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            TABLE OF CONTENTS        Plausibility vs. Probability: Alternative World Views     The Evolution of Modern Analytics    Risk Management Metrics and Models     The Future as Forecast: Assumptions Implicit in Stochastic Risk Measurement Models     An Alternative Path to Actionable Intelligence     Solutions: Moving Toward a Connectivist Approach     An Introduction to Causality: Theory, Models, and Inference     Risk Inference Networks: Estimating Vulnerability, Consequences, and Likelihood     Securities Valuation, Risk Measurement, and Portfolio Management Using Causal Models     Risk Fusion and Super Models: A Framework for Enterprise Risk Management     Inferring Causality from Historical Market Behavior     Sensemaking for Warnings: Reverse-Engineering Market Intelligence     The United States as Enterprise: Implications for National Policy and Security

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