Stalking the Black Swan
Research and Decision Making in a World of Extreme Volatility

Kenneth A. Posner



Kenneth A. Posner spent close to two decades as a Wall Street analyst, tracking the so-called "specialty finance" sector, which included controversial companies such as Countrywide, Fannie Mae, Freddie Mac, CIT, and MasterCard—many of which were caught in the subprime mortgage and capital markets crisis of 2007. While extreme volatility is nothing new in finance, the recent downturn caught many off guard, indicating that the traditional approach to decision making had let them down. Introducing a new framework for handling and evaluating extreme risk, Posner draws on years of experience to show how decision makers can best cope with the "Black Swans" of our time.

Posner's shrewd assessment combines the classic fundamental research approach of Benjamin Graham and David Dodd with more recent developments in cognitive science, computational theory, and quantitative finance. He outlines a probabilistic approach to decision making that involves forecasting across a range of scenarios, and he explains how to balance confidence, react accurately to fast-breaking information, overcome information overload, zero in on the critical issues, penetrate the information asymmetry shielding corporate executives, and integrate the power of human intuition with sophisticated analytics. Emphasizing the computational resources we already have at our disposal—our computers and our minds—Posner offers a new track to decision making for analysts, investors, traders, corporate executives, risk managers, regulators, policymakers, journalists, and anyone who faces a world of extreme volatility.

CONTENTS

Acknowledgments
Introduction

PART I: Uncertainty
1. Forecasting in Extreme Environments
2. Thinking in Probabilities
3. The Balance Between Overconfidence and Underconfidence, and the Special Risk of Complex Modeling

PART II: Information
4. Fighting Information Overload with Strategy
5. Making Decisions in Real Time: How to React to New Information Without Falling Victim to Cognitive Dissonance
6. Mitigating Information Asymmetry

PART III: Analysis and Judgment
7. Mapping from Simple Ideas to Complex Analysis
8. The Power and Pitfalls of Monte Carlo Modeling
9. Judgment

Notes
Index

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