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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2 Houston startups selected by US military for geothermal projects

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Two clean energy companies in Houston have been recruited for geothermal projects at U.S. military installations.

Fervo Energy is exploring the potential for a geothermal energy system at Naval Air Station Fallon in Nevada.

Meanwhile, Sage Geosystems is working on an exploratory geothermal project for the Army’s Fort Bliss post in Texas. The Bliss project is the third U.S. Department of Defense geothermal initiative in the Lone Star State.

“Energy resilience for the U.S. military is essential in an increasingly digital and electric world, and we are pleased to help the U.S. Army and [the Defense Innovation Unit] to support energy resilience at Fort Bliss,” Cindy Taff, CEO of Sage, says in a news release.

A spokeswoman for Fervo declined to comment.

Andy Sabin, director of the Navy’s Geothermal Program Office, says in a military news release that previous geothermal exploration efforts indicate the Fallon facility “is ideally suited for enhanced geothermal systems to be deployed onsite.”

As for the Fort Bliss project, Michael Jones, a project director in the Army Office of Energy Initiatives, says it’ll combine geothermal technology with innovations from the oil and gas sector.

“This initiative adds to the momentum of Texas as a leader in the ‘geothermal anywhere’ revolution, leveraging the robust oil and gas industry profile in the state,” says Ken Wisian, associate director of the Environmental Division at the U.S. Bureau of Economic Geology.

The Department of Defense kicked off its geothermal initiative in September 2023. Specifically, the Army, Navy, and Defense Innovation Unit launched four exploratory geothermal projects at three U.S. military installations.

One of the three installations is the Air Force’s Joint Base San Antonio. Canada-based geothermal company Eavor is leading the San Antonio project.

Another geothermal company, Atlanta-based Teverra, was tapped for an exploratory geothermal project at the Army’s Fort Wainwright in Alaska. Teverra maintains an office in Houston.

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This article originally ran on EnergyCapital.

Houston investor calls for all angels to move the ecosystem forward

houston innovators podcast episode 233

One of the biggest components of a well-functioning startup ecosystem is inarguably access to capital, and Mitra Miller is dedicated to enhancing education around investment and growing Houston's investor base.

As vice president and board member of the Houston Angel Network, the oldest angel network in Texas and one of the most active angel networks in the country, Miller strives to provide guidance to new and emerging angel investors as well as founders seeking to raise money from them.

"Most founders have no idea or understanding of how investors think — we are not an ATM," Miller says on the Houston Innovators Podcast. "We are really partners you are getting married to for the next 5, 8, 10 years — sometimes longer. We need to bring your allies in every sense of the word."



HAN, a nonprofit, provides a unique opportunity for its members, as Miller explains. The group consists of around 100 individuals from all business backgrounds, so evaluating companies together brings more than just a wealth of capital — but also a wealth of knowledge.

"What HAN provides is access to investments," Miller says, adding that members have the benefit in evaluating companies together with people from different backgrounds. "Inside a group like HAN, we have extraordinary expertise."

In addition to educating both founders and investors in the process, Miller has dedicated herself to providing opportunities for students in low-income parts of Houston to learn about the startup world. Eight years ago, she founded Eagle Investors, an organization that provides a year-long program that culminates in a group of students participating as judges for the Rice Business Plan Competition.

"They spend a year learning about innovation, entrepreneurship, and investing by meeting local investors, entrepreneurs, and service providers. They go around Houston to get to visit and ... experience all of the ecosystem," Miller says.

At RBPC, the cohort of high school students evaluate the pitches and select a company to provide a $5,000 prize.

Miller herself has been a judge at RBPC for 20 years now, and she's had a front row seat for watching Houston develop as an ecosystem. She's seen the city make real progress, but has one major call to action.

"The piece that I am most aware of that I would like to see grow is activating more accredited investors who are interested in this asset class of early-stage companies and plugging in," Miller says. "They can also invest their time and knowledge to help companies in our region grow and scale."

Report: Houston secures spot on list of top 50 startup cities

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A new ranking signals great promise for the growth of Houston’s startup network.

Houston ranks among the world’s top 50 startup cities on a new list from PitchBook, a provider of data and research about capital markets. In fact, Houston comes in at No. 50 in the ranking. But if you dig deeper into the data, Houston comes out on top in one key category.

The city earns a growth score of 63.8 out of 100 — the highest growth score of any U.S. city and the seventh highest growth score in the world. In the growth bucket, Houston sits between between Paris (64.4) and Washington, D.C. (61.7).

The PitchBook growth score reflects short-term, midterm, and long-term growth momentum for activity surrounding venture capital deals, exits, and fundraising for the past six years.

PitchBook’s highest growth score (86.5) goes to Hefei, a Chinese manufacturing hub for electric vehicles, solar panels, liquid crystal displays, home appliances, and Lenovo computers.

The overall ranking is based on a scoring system that relies on proprietary PitchBook data about private companies. The system’s growth and development scores are based on data related to deals, exits, fundraising and other factors.

Houston earns a development score of 34.1 out of 100, which puts it in 50th place globally in that regard. This score measures the size and maturity of a city’s startup network.

Topping the overall list is San Francisco, followed by New York City and Beijing. Elsewhere in Texas, Austin appears at No. 16 and Dallas at No. 36.

The ranking “helps founders, operators, and investors assess locations when deciding where to expand or invest,” says PitchBook.

“Network effects matter in venture capital: Investors get more than half of their deals through referrals, according to research led by Harvard professor Paul Gompers,” PitchBook goes on to say. “So it stands to reason that dealmakers should seek these networks out when deciding where to do business.”

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