As corporate debt markets continue to grow in importance, it will become crucial for investors and regulators to understand the nuanced factors influencing their liquidity. Photo via Getty Images

At the end of every quarter, publicly traded companies announce their profits and losses in an earnings report. These updates provide insight into a company’s performance and, in theory, give investors and shareholders clarity on whether to buy, sell or hold. If earnings are good, the stock price may soar. If they’re down, the price might plunge.

However, the implications for the stock price may not be immediately clear to all investors. In the face of this uncertainty, sellers will ask for high prices, and buyers will offer low ones, creating a significant “bid-ask spread.” When this happens, it becomes more costly to trade, and the stock becomes less liquid.

This is a well-documented effect on equity stock markets. However, according to research by Stefan Huber (Rice Business), Chongho Kim (Seoul National University) and Edward M. Watts (Yale SOM), the corporate bond market responds differently to earnings news. This is because bond markets differ from stock markets in a significant way.

Stocks v. Bonds: What Happens When Earnings Are Announced?

Equities are usually traded on centralized exchanges (e.g., New York Stock Exchange). The exchange automatically queues up buyers and sellers according to the quote they’ve entered. Trades are executed electronically, and the parties involved are typically anonymous. A prospective buyer might purchase Microsoft shares from someone drawing down their 401(k) — or they could be buying from Bill Gates himself.

Corporate bond markets work differently. They are “over-the-counter” (OTC) markets, meaning a buyer or seller needs to find a counterparty to trade with. This involves getting quotes from and negotiating with potential counterparties. This is an inherent friction in bond trading that results in much higher costs of trading in the form of wider bid-ask spreads.

Here’s what Huber and his colleagues learned from the research: Earnings announcements prompt many investors to trade. And on OTC markets, potential buyers and sellers become easier to find and negotiate with.

A Stronger Bargaining Position for Bonds

According to Huber, “When earnings information comes out, a lot of people want to trade. In bond markets, that makes it much easier to find someone to trade with. The more options you have to trade, the stronger your bargaining position becomes, and the lower your trading costs go.”

He compares the process to shopping in a market with a flexible approach to pricing.

“Let's say you're at a farmers market and you want to buy an apple,” Huber says. “If there is only one seller, you buy the apple from that person. They can ask for whatever price they want. But if there are multiple sellers, you can ask around, and there is potential to get a better price. The price you get depends on the number of options you have in trading partners.”

What’s at Stake?

Although bonds receive less attention than equities, the stakes are high. There is about $10 trillion in outstanding corporate debt in the U.S., and more than $34 billion in average daily trading volume.

A detailed record of bond trades is available from the Financial Industry Regulatory Authority (FINRA), which requires that trades be reported via their Trade Reporting and Compliance Engine (TRACE).

The study from Huber and co-authors uses an enhanced version of TRACE to examine trades executed between 2002 and 2020. The team analyzed the thirty-day periods before and after earnings announcements to gather data about volume, bid-ask spreads and other measures of liquidity.

They find that, like on the stock market, there are more investors and broker-dealers trading bonds around earnings announcements. However, unlike on the stock market, transaction costs for bonds decrease by 6 to 7 percent in the form of bid-ask spreads.

What Sets This Research Apart?

“Taking a purely information asymmetry-based view would predict that what happens to stock liquidity would also happen to bonds,” Huber says. “A piece of information drops, and some people are better able to work with it, so others price protect, and bid-ask spreads and the cost of trading go up.”

“But if you consider the search and bargaining frictions in bond markets, you get a more nuanced picture. While information asymmetry increases, like it does on stock markets, the information prompts more investors into bond trading, which makes it easier to find counterparties and get better transaction prices. Consequently, bid-ask spreads go down. This search and bargaining friction does not really exist on equities exchanges. But we cannot ignore it in OTC markets.”

As corporate debt markets continue to grow in importance, it will become crucial for investors and regulators to understand the nuanced factors influencing their liquidity. This study provides a solid foundation for future research.

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This article originally ran on Rice Business Wisdom. For more, see “Earnings News and Over-the-Counter Markets.” Journal of Accounting Research 62.2 (2024): 701-35.

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Austin company to bring AI-powered school to The Woodlands

AI education

Austin-based Alpha School, which operates AI-powered private schools, is opening its first Houston-area location in The Woodlands.

The 8,000-square-foot school, scheduled to be ready for the 2026-27 academic year, initially will serve students in kindergarten through eighth grade. Alpha says the school will offer “open workshop spaces and innovative classrooms that support personalized instruction, core academics, leadership development, and real-world life skills.”

Alpha sets aside two hours each school day for the AI-driven, self-paced study of core subjects like math, reading and science. The rest of each school day consists of life-skills workshops focusing on topics such as leadership and financial literacy.

Alpha’s school in The Woodlands has begun accepting applications for the 2026-27 school year. Annual tuition costs $40,000.

“The Woodlands is one of the most dynamic, forward-thinking communities in Texas, and Alpha is proud to bring

an innovative educational model that complements its strong academic foundation,” says Rachel Goodlad, head

of expansion for Alpha.

Founded in 2014, Alpha School combines adaptive technology-driven instruction with immersive life-skills workshops. Its model emphasizes mastery-based learning in core subjects alongside development of communication, critical thinking, financial literacy and leadership skills. It operates more than 15 schools across the country.

Elsewhere in Texas, Alpha operates schools in Austin, Brownsville, Fort Worth and Plano. Alpha also operates 12 Texas Sports Academy campuses in Texas, including locations in Houston, Pearland and Richmond, along with a NextGen Academy esports school in Austin, a school for gifted students in Georgetown, and lower-cost Nova Academy campuses in Austin and Bastrop.

Alpha has fans and critics. While supporters tout students’ high achievement rates, detractors complain about the high tuition and the AI-influenced depersonalization of education.

“Students and our country need to be in relationship with other human beings,” Randi Weingarten, president of the American Federation of Teachers, a teachers union, tells The New York Times. “When you have a school that is strictly AI, it is violating that core precept of the human endeavor and of education.”

Alpha co-founder MacKenzie Price, a podcaster and social media influencer, doesn’t share Weingarten’s views.

“Parents and teachers: We need to embrace this change,” Price wrote after President Trump signed an executive order promoting AI in schools.

The Times notes that Alpha doesn’t employ AI as a tutor or a supplement. Rather, the newspaper says, AI is “the school’s primary educational driver to move students through academic content.”

Houston researcher secures $1.7M to develop drug for aggressive form of breast cancer

cancer research

A University of Houston researcher has joined a $3.2 million effort to develop a new drug designed to attack a cancer-driving protein commonly found in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is one of the most difficult-to-treat forms of cancer and accounts for 10 percent to 15 percent of all breast cancer cases. The disease gets its name because tumors associated with it test negative for estrogen receptors, progesterone receptors and excess HER2 protein, making it difficult to target. Due to this, TNBC is often treated with general chemotherapy, which can come with negative side effects and drug resistance, according to UH.

UH College of Pharmacy research associate professor Wei Wang is developing a drug that can target the disease more specifically. The drug will target MDM2, a protein often overproduced in TNBC that also contributes to faster tumor growth.

Wang is working on a team led by Wei Li, director of the University of Tennessee Health Science Center College of Pharmacy’s Drug Discovery Center. She has received $1.7 million to support the research.

Wang and UH professor of pharmacology and toxicology Ruiwen Zhang have discovered a compound that can break down MDM2. In early laboratory models, the compound has shown the ability to shrink tumors.

Wang and Zhang will focus on understanding how the treatment works and monitoring its effectiveness in models that closely mirror human disease.

“We will study how the drug targets MDM2 and evaluate the most promising drug candidates to determine effective dosing, understand how the drug behaves in the body, compare it with existing treatments and assess early safety,” Wang said in a news release.

Li’s team at the University of Tennessee will be working on the chemistry and drug design end of the project.

“This work could lead to an entirely new class of therapies for triple-negative breast cancer,” Li added in the release. “We’re hopeful that by directly removing the MDM2 protein from cancer cells, we can help more patients respond to treatment regardless of their tumor type.”