During the tenth anniversary of the fall of Lehman Brothers last September, media outlets, which failed to anticipate the last financial crisis, fell all over themselves to warn where and when the next one would emerge.
But the exercise, by its very nature, was based on speculation rather than hard data. Now, Poets&Quants’ Professor of the Week, Nobel Prize-winning economist Robert F. Engle of New York University Stern School of Business, has created a new tool to measure systemic risk in the financial system, and hence the risk of a new global financial crisis. Spoiler alert: Right now it’s pretty low but rising rapidly.
His paper, “Measuring the Probability of a Financial Crisis,” co-written with Tuanyue Ruan of NUS Business School at the National University of Singapore, was published in September in PNAS, Proceedings of the National Academy of Sciences.
ENGLE FINDS THE ROOT CAUSE OF FINANCIAL CRISES IS EXCESSIVE CREDIT GROWTH
Engle and Ruan start by identifying the root cause of financial crises as “excessive credit growth,” which comes from banks lending too much money or taking on too much leverage late in an economic and credit cycle. The flip side of that, the authors argue, is “the undercapitalization of the financial sector,” which is what helps crises spread.
“The risk of a financial crisis in a country depends on the total capital shortfall of the financial sector in this country,” the researchers contend. “Thus, a firm that increases its leverage or beta will not only increase its own risk but also increase the risk of other financial institutions in the country.”
“At the end of a credit cycle, increasingly risky credit will be issued and the holders of this credit will be leveraged financial institutions with insufficient capital to cover losses in a downturn,” Engle and Ruan write. “This is how a ‘credit boom goes bust.’” It’s also how risk taken on by individual banks or firms metastasizes into systemic risk.
GOVERNMENT REGULATION IS ANOTHER KEY ELEMENT OF SYSTEMIC FINANCIAL RISK
Engle and Ruan develop one key indicator of systemic risk, SRISK, which “measures the dollar amount of capital that a financial firm would need to raise to function normally if we have another financial crisis”—in other words, the “median capital shortfall, conditional on a future financial crisis.”
The other key element is government regulation, or the lack thereof. “A country that relaxes its regulation or fails to adequately capitalize its institutions will increase the risk of a financial crisis in other countries,” they write. That’s what happened during the subprime mortgage bubble when independent mortgage originators fell between the cracks of U.S. regulators and credit derivatives traded by big Wall Street banks also wound up in a regulatory no man’s land. When the financial crisis hit, it spread quickly beyond U.S. borders.
Engle and Ruan divide a country’s SRISK score by its GDP to calculate its systemic financial risk, absent a government bailout. But their best measure of financial vulnerability comes from dividing SRISK by the total assets in the financial sector. Using data on SRISK from Stern’s Volatility Institute, the authors tracked systemic risk for 23 developed countries since 2000. By these measures, the probability of financial crisis peaked at 80-90% in 2008 but now sits below 10%, which means that concerns about future global financial crises appear unwarranted for now. The measure is rapidly rising, however, and data for China and Japan are much more worrisome.
Engle, 76, is the Michael Armellino Professor in the Management of Financial Services at NYU Stern and Director of the Stern Volatility Institute. He has published more than 100 articles and specializes in risk and volatility in financial markets over time. He teaches classes in financial markets and financial theory.
Engle earned his BA in physics from Williams and his MS in Physics and Ph.D. in economics from Cornell. He started out his academic career at MIT, then taught at the University of California, San Diego, for 25 years before joining NYU Stern in 2000, where he has been ever since.
In 2003, he and former UC San Diego colleague Clive W.J. Granger won the Nobel Prize in Economic Sciences—in Engle’s case, for his research on “analyzing economic time series with time-varying volatility (ARCH).”
In the past, researchers used statistical methods that assumed constant volatility. But Engle “developed methods for statistical modeling of time-varying volatility,” the Swedish Academy of Sciences noted, which “have become indispensable tools not only for researchers but also for analysts on financial markets, who use them in asset pricing and in evaluating portfolio risk.”