Equity options can act as an alternative to credit default swaps for detecting a company’s credit risk. Photo via Getty Images

Up until the 2007-2009 financial crisis, credit default swaps (CDS) were a predominant method for predicting the probability of corporate default. CDS function like insurance for loan assets — if an asset defaults, the bank who purchased the CDS would recoup their loss. Higher-risk assets usually have higher premiums, and in this way the price of a CDS indicates the probability of default.

When the housing market crashed in 2007, the CDS market crashed along with it when banks had to pay out more than they had expected. The CDS market is not expected to ever return to its previous high, leaving a void in market-driven estimates for determining an asset’s default probability.

To fill that void, a team of researchers including Rice Business Professor Robert Dittmar created an alternative method for measuring default risk: equity options data. The team found that equity options not only correlate with CDS data in terms of accurate prediction of default but also provide additional insights on what types of assets are more likely to default, and when they will default.

There are two types of options, a call option, which is essentially a bet that a stock’s price will be higher than a contracted value (the strike price) and a put option, which is a bet that a stock’s price will be less than a contracted value.

A put is often viewed as an insurance contract — if you hold a stock, but also a put option on it, you limit your loss on the stock if the stock price falls.

“What we are looking at is essentially how expensive put options get,” says Dittmar. “If the market thinks a company is likely to default, it expects that its stock value will fall (almost to zero). As a result, put options, which represent insurance against this loss become more expensive. We are looking at how these option prices change to see if they inform us about the probabilities of default.”

According to Dittmar and his team, this approach has several advantages. 1) There are more stocks with options than CDS. 2) The CDS market is drying up whereas the option market remains liquid. And 3) Because of the nature of an option contract, and the fact that in principle equity holders have the lowest claim on a company’s assets, this approach may allow investors to predict losses in case of default.

The team looked at CDS quotes on 276 firms between 2002 and 2017, focusing attention on entities that had quote data available on one-year credit default swaps. The 15-year sample enabled the researchers to analyze the money lost through defaults over a longer period of time, including the 2007-2009 financial crisis.

Using equity options data as a predictor of default led to some interesting insights. First, there are two components that investors in corporate bonds think about when weighing default risk — the probability of default and (should there be a default) how much of the bond’s principal they will get back (i.e., recovery rate). “What we see is that credit ratings imply different levels of default thresholds, which may mean that investors believe that there are differences in the amount that debt holders will lose in the case of default,” says Dittmar.

Second, option-implied default probabilities correlate to historical changes in the economy. Default probabilities are higher in bad economic times and for firms with poorer credit ratings and financial positions. Default spikes are more likely during times of economic turbulence, such as the financial crisis of 2007-2009, which correlated with the decline of the CDS market after an onslaught of debt defaults during the recession. Assets are less likely to default during times of economic expansion. Over the period of 2013-2017, forecasted losses through defaults hovered around 15%.

The research sample ends in 2017, and the paper was published in 2020, about a month after the start of the coronavirus pandemic. Since then, there have been unprecedented changes in the economy, and some economists are anticipating another recession in 2023. With such instability in the market, multiple methods of predicting losses should be especially relevant. This research suggests that the equity options market may provide additional ways of finding the probability of these losses.

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This article originally ran on Rice Business Wisdom and was based on research from Robert Dittmar, professor of finance at the Jones Graduate School of Business at Rice University.

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UH receives $2.6M gift to support opioid addiction research and treatment

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The estate of Dr. William A. Gibson has granted the University of Houston a $2.6 million gift to support and expand its opioid addiction research, including the development of a fentanyl vaccine that could block the drug's ability to enter the brain.

The gift builds upon a previous donation from the Gibson estate that honored the scientist’s late son Michael, who died from drug addiction in 2019. The original donation established the Michael C. Gibson Addiction Research Program in UH's department of psychology. The latest donation will establish the Michael Conner Gibson Endowed Professorship in Psychology and the Michael Conner Gibson Research Endowment in the College of Liberal Arts and Social Sciences.

“This incredibly generous gift will accelerate UH’s addiction research program and advance new approaches to treatment,” Daniel O’Connor, dean of the College of Liberal Arts and Social Sciences, said in a news release.

The Michael C. Gibson Addiction Research Program is led by UH professor of psychology Therese Kosten and Colin Haile, a founding member of the UH Drug Discovery Institute. Currently, the program produces high-profile drug research, including the fentanyl vaccine.

According to UH, the vaccine can eliminate the drug’s “high” and could have major implications for the nation’s opioid epidemic, as research reveals Opioid Use Disorder (OUD) is treatable.

The endowed professorship is combined with a one-to-one match from the Aspire Fund Challenge, a $50 million grant program established in 2019 by an anonymous donor. UH says the program has helped the university increase its number of endowed chairs and professorships, including this new position in the department of psychology.

“Our future discoveries will forever honor the memory of Michael Conner Gibson and the Gibson family,” O’Connor added in the release. “And I expect that the work supported by these endowments will eventually save many thousands of lives.”

CenterPoint and partners launch AI initiative to stabilize the power grid

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Houston-based utility company CenterPoint Energy is one of the founding partners of a new AI infrastructure initiative called Chain Reaction.

Software companies NVIDIA and Palantir have joined CenterPoint in forming Chain Reaction, which is aimed at speeding up AI buildouts for energy producers and distributors, data centers and infrastructure builders. Among the initiative’s goals are to stabilize and expand the power grid to meet growing demand from data centers, and to design and develop large data centers that can support AI activity.

“The energy infrastructure buildout is the industrial challenge of our generation,” Tristan Gruska, Palantir’s head of energy and infrastructure, says in a news release. “But the software that the sector relies on was not built for this moment. We have spent years quietly deploying systems that keep power plants running and grids reliable. Chain Reaction is the result of building from the ground up for the demands of AI.”

CenterPoint serves about 7 million customers in Texas, Indiana, Minnesota and Ohio. After Hurricane Beryl struck Houston in July 2024, CenterPoint committed to building a resilient power grid for the region and chose Palantir as its “software backbone.”

“Never before have technology and energy been so intertwined in determining the future course of American innovation, commercial growth, and economic security,” Jason Wells, chairman, president and CEO of CenterPoint, added in the release.

In November, the utility company got the go-ahead from the Public Utility Commission of Texas for a $2.9 billion upgrade of its Houston-area power grid. CenterPoint serves 2.9 million customers in a 12-county territory anchored by Houston.

A month earlier, CenterPoint launched a $65 billion, 10-year capital improvement plan to support rising demand for power across all of its service territories.

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This article originally appeared on our sister site, EnergyCapitalHTX.com.

Houston researchers develop material to boost AI speed and cut energy use

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A team of researchers at the University of Houston has developed an innovative thin-film material that they believe will make AI devices faster and more energy efficient.

AI data centers consume massive amounts of electricity and use large cooling systems to operate, adding a strain on overall energy consumption.

“AI has made our energy needs explode,” Alamgir Karim, Dow Chair and Welch Foundation Professor at the William A. Brookshire Department of Chemical and Biomolecular Engineering at UH, explained in a news release. “Many AI data centers employ vast cooling systems that consume large amounts of electricity to keep the thousands of servers with integrated circuit chips running optimally at low temperatures to maintain high data processing speed, have shorter response time and extend chip lifetime.”

In a report recently published in ACS Nano, Karim and a team of researchers introduced a specialized two-dimensional thin film dielectric, or electric insulator. The film, which does not store electricity, could be used to replace traditional, heat-generating components in integrated circuit chips, which are essential hardware powering AI.

The thinner film material aims to reduce the significant energy cost and heat produced by the high-performance computing necessary for AI.

Karim and his former doctoral student, Maninderjeet Singh, used Nobel prize-winning organic framework materials to develop the film. Singh, now a postdoctoral researcher at Columbia University, developed the materials during his doctoral training at UH, along with Devin Shaffer, a UH professor of civil engineering, and doctoral student Erin Schroeder.

Their study shows that dielectrics with high permittivity (high-k) store more electrical energy and dissipate more energy as heat than those with low-k materials. Karim focused on low-k materials made from light elements, like carbon, that would allow chips to run cooler and faster.

The team then created new materials with carbon and other light elements, forming covalently bonded sheetlike films with highly porous crystalline structures using a process known as synthetic interfacial polymerization. Then they studied their electronic properties and applications in devices.

According to the report, the film was suitable for high-voltage, high-power devices while maintaining thermal stability at elevated operating temperatures.

“These next-generation materials are expected to boost the performance of AI and conventional electronics devices significantly,” Singh added in the release.