Houston researcher tries to crack the code on the Fed's data to determine economic outlook

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There's no crystal ball, but this researcher from Rice University is trying to see if some metrics work for economic forecasting. Photo via Getty Images

Research by Rice Business Professor K. Ramesh shows that the Fed appears to harvest qualitative information from the accounting disclosures that all public companies must file with the Securities and Exchange Commission.

These SEC filings are typically used by creditors, investors and others to make firm-level investing and financing decisions; and while they include business leaders’ sense of economic trends, they are never intended to guide macro-level policy decisions. But in a recent paper (“Externalities of Accounting Disclosures: Evidence from the Federal Reserve”), Ramesh and his colleagues provide persuasive evidence that the Fed nonetheless uses the qualitative information in SEC filings to help forecast the growth of macroeconomic variables like GDP and unemployment.

According to Ramesh, the study was made possible thanks to a decision the SEC made several years ago. The commission stores the reports submitted by public companies in an online database called EDGAR and records the IP address of any party that accesses them. More than a decade ago, the SEC began making partially anonymized forms of those IP addresses available to the public. But researchers eventually figured out how to deanonymize the addresses, which is precisely what Ramesh and his colleagues did in this study.

"We were able to reverse engineer and identify those IP addresses that belonged to Federal Reserve staff," Ramesh says.

The team ultimately assembled a data set containing more than 169,000 filings accessed by Fed staff between 2005 and 2015. They quickly realized that the Fed was interested only in filings submitted by a select group of industry leaders and financial institutions.

But if Ramesh and his colleagues now had a better idea of precisely which bellwether firms the Fed focused on, they still had no way of knowing exactly what Fed staffers had gleaned from the material they accessed. So the team decided to employ a measure called "tone" that captures the overall sentiment of a piece of text – whether positive, negative, or neutral.

Building on previous research that had identified a set of words with negatively toned financial reports, Ramesh and his colleagues examined the tone of all the SEC filings accessed by Fed staff between one meeting of the Federal Open Markets Committee (FOMC) and the next. The FOMC sets interest rates and guides monetary policy, and its meetings provide an opportunity for Fed officials to discuss growth forecasts and announce policy decisions.

The researchers then examined the Fed's growth forecasts to see if there was a relationship between the tone of the documents that Fed staff examined in the period between FOMC meetings and the forecasts they produced in advance of those meetings.

The team found close correlations between the tone of the reports accessed by the Fed and the agency’s forecasts of GDP, unemployment, housing starts and industrial production. The more negative the filings accessed prior to an FOMC meeting, for example, the gloomier the GDP forecast; the more positive the filings, the brighter the unemployment forecast.

Ramesh and his colleagues also compared the Fed's forecasts with those of the Society of Professional Forecasters (SPF), whose members span academia and industry. Intriguingly, the researchers found that while the errors in the SPF's forecasts could be attributed to the absence of the tonal information culled from the SEC filings, the errors in the Fed’s forecasts could not. This suggests both that the Fed was collecting qualitative information that the SPF was not—and that the agency was making remarkably efficient use of it.

"They weren’t leaving anything on the table," Ramesh says.

Having solved one mystery, Ramesh would like to focus on another; namely, how does the Fed identify bellwether firms in the first place?

Unfortunately, the SEC no longer makes IP address data publicly available, which means that Ramesh and his colleagues can no longer study which companies the Fed is most interested in. Nonetheless, Ramesh hopes to use the data they have already collected to build a model that can accurately predict which firms the Fed is most likely to follow. That would allow the team to continue studying the same companies that the Fed does, and, he says, “maybe come up with a way to track those firms in order to understand how the economy is going to move.”

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This article originally ran on Rice Business Wisdom and was based on research from K. Ramesh is Herbert S. Autrey Professor of Accounting at Jones Graduate School of Business at Rice University.

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

Rice research explains a new way to measure default risk for investors

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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.

Earnings report delays generally lead to drops in stock prices. Disclosure can soften this market reaction. Photo via Getty Images

Houston research: Is no news always bad news in market reports?

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Investors eagerly wait for the news in their earnings reports. When these reports don't appear on the expected date, investors worry — and stock prices often fall as a result. But what if managers could present late reports in a way that spared their companies?

Research by K. Ramesh, a professor at Rice Business, shows that managers' approach to late earnings reports can profoundly affect market reaction. When firms put off filing a report, it's up to managers to decide whether to speak up or stay quiet. Those who choose to talk about a postponement then must decide how, what and how much to say.

All earnings delays, whether they're attended by a statement or not, prompt negative market reaction, prior research suggests. But in his research, Ramesh, Herbert S. Autrey Professor of Accounting, wanted to learn more about the exact consequences of these late reports, and how managers can lessen the blowback.

To do this, Ramesh and a team of coauthors first looked at the incidence, timing and contents of a comprehensive sample of press releases announcing an earnings delay. Then they studied what those delays did to market value.

Conventional wisdom in the business press already suggested that investors viewed any announcement of a delayed earnings report as bad news. But finance theorists tell a more complicated story, one in which the market response might be partially shaped by managerial behavior. Subtle factors, they found, such as whether the impending delay is discussed or treated with silence, really can make a difference.

In the view of some theorists, merely announcing a delay can sometimes avert a drop in stock prices. Others argue that this isn’t necessarily the case, especially if the company discloses that the delay stemmed from legal concerns. The better approach: making it clear up front that reports aren't being postponed to hide disastrous information. But what if the information is indeed disastrous?

That may be the one case where disclosure won’t change much, Ramesh and his team found.

“Those companies that are in fact concealing disastrous results will experience no benefits (in the form of higher stock price) from revealing their true situation,” the research team wrote, “because the market will infer the worst from the manager’s decision not to announce the delay.” For this reason, they added, delayed earnings without a stated explanation prompt the most negative market reaction. As in so many areas of public relations, without a narrative, investors will infer a negative one of their own.

To better understand the impact of late reports, Ramesh and his coauthors built a comprehensive sample of 545 delay announcements by using a keyword search of the Dow Jones Factiva database between January 1, 1995, and December 31, 2009.

As conventional wisdom suggested, the study showed that announcements of late earnings reports led to negative market reactions. (Earlier studies have shown smaller firms are hit hardest by this dynamic, perhaps because investors assume large companies have more finely tuned financial reporting systems, so are less worried by their earnings delays).

Consistent with the anecdotal evidence, the average one-day abnormal stock return for the sample was -6.29 percent, while the median return was -2.27 percent. Both figures are economically and statistically significant.

The researchers next classified the announcements according to stated reason, dividing the delays into “Accounting” and “Non-Accounting” categories. “Accounting” explanations were subdivided into “Accounting Issue,” “Accounting Process” and “Rule Change.”

Meanwhile, “Non-Accounting” explanations were divided into “Business,” which linked the delay to some event such as divestitures or regulatory proceedings, and “Other,” which ranged from earthquakes to power outages. Finally, there were delays for no stated reason at all.

About two-thirds of the late announcements, the team found, were linked to accounting. When firms named a specific accounting issue as the cause for delay, the average abnormal return reached a statistically significant -8.15 percent. When managers explained that the accounting process was not complete, the average abnormal return was slightly lower, at -7.04 percent.

After accounting issues, business events drove most earnings delays. In theory, these events could have been either good or bad news. But the average abnormal return for the subsample was a statistically significant -3.74 percent — a reflection of the fact that most business events linked to late earnings reports tend to be negative.

Curiously, the average abnormal return for the grouping classified as “Other” was almost nil — at 0.53 percent. This suggests that the market does not penalize managers for events outside of their control that have little, if any, relevance to firm performance.

“No Reason,” the researchers found, was the most damaging explanation of all. Seven percent of the sample, or 37 out of 545 delays, came without a stated reason. The average abnormal return for these was a significant -10.41 percent, a greater negative number than the returns for any of the other reasons.

So what should managers do when a deadline is going to be busted? Bite the bullet and disclose the reasons, Ramesh suggests. For one thing, it helps limit legal exposure and preserve credibility. When the reason for the late report is innocuous, explaining to investors can also mitigate the market's displeasure. A caveat: While informing investors that a power outage caused earnings delay will calm jitters, disclosure may not make a difference if the company just can’t balance its books.

It's human nature, apparently, to read no news as bad news. Relaying something—anything—about the cause of a late report seems to soothe investors' nerves by preventing them from filling the silence themselves.

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This article originally ran on Rice Business Wisdom and was based on research from K. Ramesh, Tiago Duarte-Silva, Huijing Fu and Christopher F. Noe. K. Ramesh is the Herbert S. Autrey Professor of Accounting at Jones Graduate School of Business at Rice University.

Research shows that some corporate executives skew earnings to influence the market and inflate share price. Photo via Pexels

Rice University research finds market outliers at risk of misreporting

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Say a company called CoolConsumerGoodsCo has just released its quarterly earnings report, revealing significantly higher profits than its consumer goods industry counterparts.

That result might spur analysts to slap a buy rating on the stock and investors to snap up shares. In an ideal world, the market wouldn't have to consider the possibility that the numbers aren't legit — but then again, it's not an ideal world. (Enron, anyone?)

Rice Business professors Brian R. Rountree and Shiva Sivaramakrishnan, along with Andrew B. Jackson at UNSW in Australia, studied what makes business leaders more likely to engage in fraudulent earnings reporting. Specifically, they focused on the relationship between this kind of misrepresentation and the degree to which a company's earnings are in line with the rest of its industry — a variable the researchers term "co-movements."

Many people are familiar with a similar variable, calculated using stock returns often referred to as a company's beta. The authors adapted the stock return beta to corporate earnings to see how a company's earnings move with earnings at the industry level.

The researchers hypothesized that the less in sync a company's earnings are with its industry, the higher the chance a company's leaders will manipulate earnings reports. They started with the well-accepted premise that corporations try to skew earnings reports to influence the market. The primary motive is typically to raise the company's stock price, as when an executive tries to "choose a level of bias" that balances potential fallout of getting caught against the benefits of a higher stock price.

To test their prediction, the professors analyzed a sample of enforcement actions taken by the U.S. Securities and Exchange Commission against companies for problematic financial reporting from 1970 to 2011 — although they noted that given the SEC's limited resources, the number of enforcement actions probably underestimates the actual amount of earnings manipulation in the market.

Their analysis revealed that firms with low earnings co-movements (meaning their earnings were out of sync with industry peers) were more likely to be accused by the SEC of reporting misdeeds. They concluded that the degree of earnings co-movement determines the probability of earnings manipulation. Put another way, earnings co-movements are a "causal factor" in the chances of earnings manipulations — and to a significant degree. The researchers found that firms who don't co-move with the market are more than 50 percent more likely to face an SEC enforcement action, compared with firms who are perfectly aligned with the market.

The researchers drilled deeper into the data to study whether the odds changed depending on the industry, since past research has indicated that the amount of competition in an industry works to constrain misreporting. That premise seems to hold true, the researchers concluded. In industries with more competitive markets, the impact of low co-movement on earnings manipulation is moderated.

They also studied whether the age of a firm played a part in the likelihood of earnings manipulation. Newer firms often rely more on stock compensation, which could be a motive for manipulating earnings reporting to drive up share price. Indeed, younger firms were more susceptible to misreporting when their earnings were out of whack with the rest of the marketplace.

Every firm faces some risk of misreporting, however. Even for public companies under analyst scrutiny, low co-movement proved to be a driver of earnings manipulation. But companies known for conservative reporting tend to be less likely to exaggerate their earnings, in general; these firms typically recognize losses in a more timely manner, the professors found.

These findings suggest a number of future lines of research. For example: When do executives underreport earnings? And can analyzing patterns related to cash flow reporting help better isolate earnings manipulation?

In the meantime, if you come across a company like CoolConsumerGoodsCo with an earnings report that's widely out of sync with the rest of its industry, you might think twice before rushing to buy in.

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This article originally ran on Rice Business Wisdom and is based on research from Brian R. Rountree, an associate professor of accounting at the Jones Graduate School of Business at Rice University, and Shiva Sivaramakrishnan is the Henry Gardiner Symonds Professor of Accounting at Rice Business.

John Berger, CEO of Houston-based Sunnova, is this week's Houston Innovators Podcast guest. Courtesy of Sunnova

Houston solar energy exec shines light on company growth and IPO

HOUSTON INNOVATORS PODCAST EPISODE 15

It was all about the timing for John Berger, founder and CEO of Sunnova, a Houston-based residential solar energy company.

When he founded his company in 2012 in Houston, solar energy wasn't the trendy sustainability option it is today, but Berger saw the potential for technology within the industry. So, with a lot of perseverance and the right team behind him, he scaled Sunnova through nationwide expansion, billions of money raised, and a debut on the stock market last July — something that also happened with great timing.

About 72 hours after Sunnova went public last July, the Federal Reserve System announced it was going to cut rates. Additionally, Sunnova's IPO occurred ahead of WeWork's failed IPO.

"We went public in a market that still isn't back open again, I think, for IPOs," Berger says on this week's episode of the Houston Innovators Podcast. "We had pretty good timing when we went out the door."

However great the timing was, Sunnova's success is built on the hard work and skills of the company's employees, Berger explains on the podcast, and now running a public company requires a dynamic leader.

"I really look at myself and how I can change myself," Berger says. "I'm a different CEO today than I was 12 months ago, and hopefully I'll be a different CEO in 12 months, because the company demands it."

In the episode, Berger lifts the curtain on Sunnova's IPO, explains where he sees the solar energy industry headed, how battery storage technology has evolved, and why he's not worried about who ends up in the White House. Listen to the full episode below — or wherever you get your podcasts — and subscribe for weekly episodes.


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Houston engineers develop breakthrough device to advance spinal cord treatment

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A team of Rice University engineers has developed an implantable probe over a hundred times smaller than the width of a hair that aims to help develop better treatments for spinal cord disease and injury.

Detailed in a recent study published in Cell Reports, the probe or sensor, known as spinalNET, is used to explore how neurons in the spinal cord process sensation and control movement, according to a statement from Rice. The research was supported by the National Institutes of Health, Rice, the California-based Salk Institute for Biological Studies, and the philanthropic Mary K. Chapman Foundation based in Oklahoma.

The soft and flexible sensor was used to record neuronal activity in freely moving mice with high resolution for multiple days. Historically, tracking this level of activity has been difficult for researchers because the spinal cord and its neurons move so much during normal activity, according to the team.

“We developed a tiny sensor, spinalNET, that records the electrical activity of spinal neurons as the subject performs normal activity without any restraint,” Yu Wu, a research scientist at Rice and lead author of the study said in a statement. “Being able to extract such knowledge is a first but important step to develop cures for millions of people suffering from spinal cord diseases.”

The team says that before now the spinal cord has been considered a "black box." But the device has already helped the team uncover new findings about the body's rhythmic motor patterns, which drive walking, breathing and chewing.

Lan Luan (from left), Yu Wu, and Chong Xie are working on the breakthrough device. Photo by Jeff Fitlow/Rice University

"Some (spinal neurons) are strongly correlated with leg movement, but surprisingly, a lot of neurons have no obvious correlation with movement,” Wu said in the statement. “This indicates that the spinal circuit controlling rhythmic movement is more complicated than we thought.”

The team said they hope to explore these findings further and aim to use the technology for additional medical purposes.

“In addition to scientific insight, we believe that as the technology evolves, it has great potential as a medical device for people with spinal cord neurological disorders and injury,” Lan Luan, an associate professor of electrical and computer engineering at Rice and a corresponding author on the study, added in the statement.

Rice researchers have developed several implantable, minimally invasive devices to address health and mental health issues.

In the spring, the university announced that the United States Department of Defense had awarded a four-year, $7.8 million grant to the Texas Heart Institute and a Rice team led by co-investigator Yaxin Wang to continue to break ground on a novel left ventricular assist device (LVAD) that could be an alternative to current devices that prevent heart transplantation.

That same month, the university shared news that Professor Jacob Robinson had published findings on minimally invasive bioelectronics for treating psychiatric conditions. The 9-millimeter device can deliver precise and programmable stimulation to the brain to help treat depression, obsessive-compulsive disorder and post-traumatic stress disorder.

Houston clean hydrogen startup to pilot tech with O&G co.

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Gold H2, a Houston-based producer of clean hydrogen, is teaming up with a major U.S.-based oil and gas company as the first step in launching a 12-month series of pilot projects.

The tentative agreement with the unnamed oil and gas company kicks off the availability of the startup’s Black 2 Gold microbial technology. The technology underpins the startup’s biotech process for converting crude oil into proprietary Gold Hydrogen.

The cleantech startup plans to sign up several oil and gas companies for the pilot program. Gold H2 says it’s been in discussions with companies in North America, Latin America, India, Eastern Europe and the Middle East.

The pilot program is aimed at demonstrating how Gold H2’s technology can transform old oil wells into hydrogen-generating assets. Gold H2, a spinout of Houston-based biotech company Cemvita, says the technology is capable of producing hydrogen that’s cheaper and cleaner than ever before.

“This business model will reshape the traditional oil and gas industry landscape by further accelerating the clean energy transition and creating new economic opportunities in areas that were previously dismissed as unviable,” Gold H2 says in a news release.

The start of the Black 2 Gold demonstrations follows the recent hiring of oil and gas industry veteran Prabhdeep Singh Sekhon as CEO.

“With the proliferation of AI, growth of data centers, and a national boom in industrial manufacturing underway, affordable … carbon-free energy is more paramount than ever,” says Rayyan Islam, co-founder and general partner at venture capital firm 8090 Industries, an investor in Gold H2. “We’re investing in Gold H2, as we know they’ll play a pivotal role in unleashing a new dawn for energy abundance in partnership with the oil industry.”

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This article originally ran on EnergyCapital.

3 Houston innovators to know this week

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Editor's note: Every week, I introduce you to a handful of Houston innovators to know recently making headlines with news of innovative technology, investment activity, and more. This week's batch includes an e-commerce startup founder, an industrial biologist, and a cellular scientist.

Omair Tariq, co-founder and CEO of Cart.com

Omair Tariq of Cart.com joins the Houston Innovators Podcast to share his confidence in Houston as the right place to scale his unicorn. Photo via Cart.com

Houston-based Cart.com, which operates a multichannel commerce platform, has secured $105 million in debt refinancing from investment manager BlackRock.

The debt refinancing follows a recent $25 million series C extension round, bringing Cart.com’s series C total to $85 million. The scaleup’s valuation now stands at $1.2 billion, making it one of the few $1 billion-plus “unicorns” in the Houston area.

Cart.com was co-founded by CEO Omair Tariq in October 2020. Read more.

Nádia Skorupa Parachin, vice president of industrial biotechnology at Cemvita

Nádia Skorupa Parachin joined Cemvita as vice president of industrial biotechnology. Photo courtesy of Cemvita

Houston-based biotech company Cemvita recently tapped two executives to help commercialize its sustainable fuel made from carbon waste.

Nádia Skorupa Parachin came aboard as vice president of industrial biotechnology, and Phil Garcia was promoted to vice president of commercialization.

Parachin most recently oversaw several projects at Boston-based biotech company Ginkjo Bioworks. She previously co-founded Brazilian biotech startup Integra Bioprocessos. Read more.

Han Xiao, associate professor of chemistry at Rice University

The funds were awarded to Han Xiao, a chemist at Rice University.

A Rice University chemist has landed a $2 million grant from the National Institute of Health for his work that aims to reprogram the genetic code and explore the role certain cells play in causing diseases like cancer and neurological disorders.

The funds were awarded to Han Xiao, the Norman Hackerman-Welch Young Investigator, associate professor of chemistry, from the NIH's Maximizing Investigators’ Research Award (MIRA) program, which supports medically focused laboratories. Xiao will use the five-year grant to advance his work on noncanonical amino acids.

“This innovative approach could revolutionize how we understand and control cellular functions,” Xiao said in the statement. Read more.

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