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
General
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