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Trading and Hedging When the Market Panics

May 31, 2018

If you need a loan, your interest rate depends on factors like your income level and credit score. No job? You’re probably out of luck on that loan because there’s a higher probability you won't be able to pay back your debt. As you may expect, individuals with worse risk profiles pay higher interest rates.

Likewise, countries' borrowing cost is linked to economic factors. Lower growth and exports translate into lower tax revenues and reserves, decreasing the ability of a government to honor its debt. Because borrowers can default, they must promise a spread over the riskless country (like the U.S.). Nowadays, there is a market dedicated to the trade of this spread, the credit default swaps (CDS) market. A CDS is an insurance against the potential default of the borrower, and it trades as a spread over a similar U.S. Treasury bond.

Borrowers' default probability changes with the economic environment, increasing in bad economic times. In addition, the uncertainty about this default probability (e.g. 5 percent chance of default in the next year) also changes over time. Suddenly, what was supposed to be 5 percent can be 0.2 percent or even 10 percent. This situation leads to an additional premium over the interest rate to be paid. The compensation for uncertainty about default risk is referred to as the credit risk premium.

Current studies value default swaps using unobserved variables, which can be impractical for portfolio management and trading purposes or can generate negative default probabilities contrary to economic intuition. The objective of Assistant Professor of Finance Virgilio Zurita was to develop an approach to theoretically and empirically take care of these issues.

He and his co-authors Hitesh Doshi and Kris Jacobs set out to create a more accurate model that assesses the probability of default on bonds—taking the compensation for default uncertainty into account. The authors model default swap spreads as a function of country specific and global financial variables. In their article, “Economic and Financial Determinants of Credit Risk Premiums in the Sovereign CDS Market,” which was published in the Review of Asset Pricing Studies, the researchers used immense amounts of data to establish a mathematical model to better predict default probabilities and investors’ compensation for risk.

"We show that during periods of financial distress, both default probability and its uncertainty increase, with changes in the latter being sometimes disproportionately higher," Zurita, who began working at Baylor in fall 2016, said.

Because investors have a risk aversion to uncertainty about default risk, they demand a premium to hold the bond. The ability to disentangle these components of risk, default probabilities and uncertainty about default probabilities, has a direct impact in the trading and hedging of individual securities and portfolios of securities.

"This is quite useful, as in each point in time it determines the positions to take in order to offset global or local risk exposure," he said.

Zurita knows the benefits of this model firsthand. He worked in the hedge fund industry before pursuing his PhD in Finance at the University of Houston, and ultimately, he joined the faculty at the Hankamer School of Business.

“I didn’t really have time to do research because everything in a hedge fund is [immediate],” he said. “In academia, you get to spend more time doing proper, intensive, deep research. Hedge funds are more about the bottom line. That’s not exactly what I wanted to do.”

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