Financial Econometrics and Empirical Market Microstructure
Summary
Adaptive stress testing is a blend of art and science which continually integrates qualitative macro and quantitative micro perspectives. The first challenge in stress testing is to conceive of a wide range of credible potential threats before they materialize. Let’s tap into the marketplace of ideas for scenarios, and harness the ability of visionaries to perceive risk in potential form (think Albert Einstein). After constructing Stress Indices to reflect scenarios, we monitor outliers, which are precursors to regime shifts. The StressGrades methodology amplifies market- based risk signals, which highlights cascading risk (e. g., super-exponential increases in PStress). StressGrades are also useful in identifying assets with exceptionally low volatility, which should be stressed for hidden risks (e. g., high DStress & low StessQ). Let’s never forget that volatility only represents visible risk and that risk managers must be contrarian and uncover risks that are invisible to most. Low volatility is a temporary respite which allows us to search for hidden risks and rebalance to build more resilient portfolios and institutions. By being intelligently contrarian, we can mitigate systemic risks and transform future crises into opportunity.
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Conclusions: Spark Network Intelligence Evolutionary adaptation is a learning process: we sense changes in the environment and respond with learning experiments. Failures are not only inevitable, but essential to learning. As Tim Harford elegantly observes in Adapt: Why Success Always Starts With Failure (2011): “the art of success is to fail productively.” But to be able to learn from failure, we must be able to survive and keep playing. The obvious priority for risk managers is to ensure that their organization can withstand credible stresses. And yet paradoxically, many risk strategies that are designed to reduce individual risk (e. g., portfolio insurance, stop-loss limits, and liquidity hoarding in crisis situations) increase coupling, and often even precipitate crises. In A Demon Of Our Own Design (2008) Richard Bookstaber shows that many crises were precipitated by flawed safety mechanisms. When faced with complexity, tightly coupled systems eventually break down. To manage systemic risks, we must look beyond individual nodes and understand the non-linear processes driving ecosystems. In “Rethinking Capitalism” Nick Hanauer and Eric Liu implore us to transcend “Machinebrain” linear thinking: In the Gardenbrain story, markets are not perfectly efficient, but they are effective if managed well. Humans are not perfectly rational, calculating and selfish; they are emotional, approximating and reciprocal. And outcomes are not just as they should be; rather, they reflect the kinds of compounding and feedback loops—virtuous circles or death spirals—that distort all complex systems. (Hanauer and Liu 2012) Industrial capitalism has fuelled economic growth and expanded wealth worldwide. But it also comes with new liabilities (externalities), many of which are in hidden form. We face serious disruptive threats across all our global ecosystems.16 As Otto Scharmer writes in “Leading from the Emerging Future: From Ego-System to Eco-System Economies” (2013), individually oriented approaches are unsustainable: What’s dying is an old civilization and a mindset of maximize “me”—maximum material consumption, bigger is better, and special-interest-group driven decisionmaking that has led us into a state of organized irresponsibility, collectively creating results that nobody wants. Throughout history, humans have faced a basic choice when meeting challenges: conflict or cooperation. Conflict, while unavoidable at times, is negative sum. Cooperation yields far better results, and indeed is the (continued) |
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riskcommons. org and to produce the first generation of StressGrades analytics. Gilles Zumbach’s RiskMetrics 2006 time series research were invaluable. It was an honor to work with Knut Kjaer on next generation risk management, which evolved into the Adaptive Stress Testing framework. It was always a joy to brainstorm with my RiskMetrics labs partner Ron Papanek. Marty Nemeth was also a great sounding board, overflowing with ideas. Alvin Lee was my first mentor at JPMorgan and has always supported new ideas and a path of growth and adventure. And it was great to work with Ken Parker, Tom Stockdale, and the NextThought. com team to produce our online Adaptive Stress Testing course.
Thank you to PRMIA for much support. Lori Ramos-Marilla offered constant encouragement and enabled the opportunity to present the work at several conferences. Alex Voicu has been a creative force in enabling this research. He established a bridge to the global risk community by organizing many excellent workshops and producing the Adaptive Stress Testing online course at PRMIA University.
I deeply appreciate the insightful conversations with Anne Lalsing of Citibank, who inspired the StressGrades methodology and has provided so much thoughtful feedback.
Thank you to my Winhall Consulting partner David Shimko for encouraging early warning research, an area he had pioneered many years ago at JPMorgan.
I am grateful to philosopher Ken Wilber who inspired Integral Risk Management, and to the Boulder Integral community (especially Jeff Salzman and Nomali Perera).
Thank you to the editors at Springer for their detailed attention and patience.
And finally, I hope that Didier Sornette’s foundational Dragon King research will empower the global community to be more proactive in managing systemic risks before irreversible tipping points are crossed.
