A new, data-intensive technique can create a better profile of a firm and its profit forecast. Photo via Pexels

Earnings summaries are the corporate version of a Magic 8 Ball, something used to forecast future performance and profit. But Rice Business professor Brian Rountree has found that magic has its limits, and that by delving into a few additional areas of interest, investors can get a more accurate prediction of a company's future earnings than current techniques allow.

Plenty of studies analyze how to use performance summaries to calculate a firm's potential and future profits. Building on the abundant literature around this approach, Rountree, working with colleagues Andrew B. Jackson of the UNSW Australia Business School and Marlene Plumlee of the University of Utah, devised a new, additional technique for forecasting profits. By dissecting an assortment of operating details, the researchers discovered, it's possible to create a more precise forecast of a company's financial future.

Rather than replacing prior work on the subject, Rountree's team delved deeper into the significance of details within existing data. Their focus: whether including a firm's market, its overall industry and any unique activity specific to the firm makes for a more reliable profit forecast. Their conclusion: Firms can indeed improve their predictions if they separate returns on net operating assets (RNOA) into separate components and use those figures in their projections.

Normally, firms use market and industry related data to create future profit predictions. For example, a major oil company might use data on market conditions and the overall state of the oil industry to build its profits prediction. The resulting financial literature might be peppered with statements such as, "Like the rest of big oil…" or "The overall market for oil remains soft."

While this type of data is typically used to make projections, Rountree and his colleagues used the market and industry information more formally by creating the equivalent of stock return betas — a statistical measure of risk — for corporate earnings. In addition, they allowed for adding firm-specific information to market and industry information to help forecast earnings.

To conduct their study, Rountree's team used Compustat quarterly data to calculate firm, industry and market RNOAs from 1976 to 2014. Next, they broke these figures down and separated the results into different categories.

Their resulting formula differs from the conventional approach because it doesn't rely on one average set of market and industry-related data for each firm. Instead, it assumes varying factors for each company. The devil is in these details: Calculating specific market, industry and firm-idiosyncratic components improves the chances of forecasting profits correctly.

Correctly breaking down and separating profitability details to plug into the new formula is no small task. Separating company data into just three components requires up to 20 quarters of figures about prior profitability.

Once the information is processed, a researcher must then be vigilant for "noise" — incidental, irrelevant data that can lead to errors. Finally, Rountree warns, the breakdown process may not work as well for forecasting bankruptcy as it does for profits.

Used correctly, however, the technique is a practical new tool. By breaking down profitability into market, industry and firm-specific idiosyncrasies, researchers can improve forecasts strikingly compared to conventional calculations of total RNOAs.

The most accurate profit forecasts in other words, demand more than just a figurative shake of an industry Magic 8 Ball. To find the most reliable information about future earnings, a company instead has to flawlessly juggle years' worth of specific details about their particular firm. But the reward of planning based on a correct forecast can pay for itself.

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This story originally ran on Rice Business Wisdom. It's based on research by Brian Rountree, an associate professor of accounting at Jones Graduate School of Business at Rice University.

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How Houston innovators played a role in the historic Artemis II splashdown

safe landing

Research from Rice University played a critical role in the safe return of U.S. astronauts aboard NASA’s Artemis II mission this month.

Rice mechanical engineer Tayfun E. Tezduyar and longtime collaborator Kenji Takizawa developed a key computational parachute fluid-structure interaction (FSI) analysis system that proved vital in NASA’s Orion capsule’s descent into the Pacific Ocean. The FSI system, originally developed in 2013 alongside NASA Johnson Space Center, was critical in Orion’s three-parachute design, which slowed the capsule as it returned to Earth, according to Rice.

The model helped ensure that the parachute design was large enough to slow the capsule for a safe landing while also being stable enough to prevent the capsule from oscillating as it descended.

“You cannot separate the aerodynamics from the structural dynamics,” Tezduyar said in a news release. “They influence each other continuously and even more so for large spacecraft parachutes, so the analysis must capture that interaction in a robustly coupled way.”

The end result was a final parachute system, refined through NASA drop tests and Rice’s computational FSI analysis, that eliminated fluctuations and produced a stable descent profile.

Apart from the dynamic challenges in design, modeling Orion’s parachutes also required solving complex equations that considered airflow and fabric deformation and accounted for features like ringsail canopy construction and aerodynamic interactions among multiple parachutes in a cluster.

“Essentially, my entire group was dedicated to that work, because I considered it a national priority,” Tezduyar added in the release. “Kenji and I were personally involved in every computer simulation. Some of the best graduate students and research associates I met in my career worked on the project, creating unique, first-of-its-kind parachute computer simulations, one after the other.”

Current Intuitive Machines engineer Mario Romero also worked on Orion during his time at NASA. From 2018 to 2021, Romero was a member of the Orion Crew Capsule Recovery Team, which focused on creating likely scenarios that crewmembers could encounter in Orion.

The team trained in NASA’s 6.2-million-gallon pool, using wave machines to replicate a range of sea conditions. They also simulated worst-case scenarios by cutting the lights, blasting high-powered fans and tipping a mock capsule to mimic distress situations. In some drills, mock crew members were treated as “injured,” requiring the team to practice safe, controlled egress procedures.

“It’s hard to find the appropriate descriptors that can fully encapsulate the feeling of getting to witness all the work we, and everyone else, did being put into action,” Romero tells InnovationMap. “I loved seeing the reactions of everyone, but especially of the Houston communities—that brought me a real sense of gratitude and joy.”

Intuitive Machines was also selected to support the Artemis II mission using its Space Data Network and ground station infrastructure. The company monitored radio signals sent from the Orion spacecraft and used Doppler measurements to help determine the spacecraft's precise position and speed.

Tim Crain, Chief Technology Officer at Intuitive Machines, wrote about the experience last week.

"I specialized in orbital mechanics and deep space navigation in graduate school,” Crain shared. “But seeing the theory behind tracking spacecraft come to life as they thread through planetary gravity fields on ultra-precise trajectories still seems like magic."

UH breakthrough moves superconductivity closer to real-world use

Energy Breakthrough

University of Houston researchers have set a new benchmark in the field of superconductivity.

Researchers from the UH physics department and the Texas Center for Superconductivity (TcSUH) have broken the transition temperature record for superconductivity at ambient pressure. The accomplishment could lead to more efficient ways to generate, transmit and store energy, which researchers believe could improve power grids, medical technologies and energy systems by enabling electricity to flow without resistance, according to a release from UH.

To break the record, UH researchers achieved a transition temperature 151 Kelvin, which is the highest ever recorded at ambient pressure since the discovery of superconductivity in 1911.

The transition temperature represents the point just before a material becomes superconducting, where electricity can flow through it without resistance. Scientists have been working for decades to push transition temperature closer to room temperature, which would make superconducting technologies more practical and affordable.

Currently, most superconductors must be cooled to extremely low temperatures, making them more expensive and difficult to operate.

UH physicists Ching-Wu Chu and Liangzi Deng published the research in the Proceedings of the National Academy of Sciences earlier this month. It was funded by Intellectual Ventures and the state of Texas via TcSUH and other foundations. Chu, founding director and chief scientist at TcSUH, previously made the breakthrough discovery that the material YBCO reaches superconductivity at minus 93 K in 1987. This helped begin a global competition to develop high-temperature superconductors.

“Transmitting electricity in the grid loses about 8% of the electricity,” Chu, who’s also a professor of physics at UH and the paper’s senior author, said in a news release. “If we conserve that energy, that’s billions of dollars of savings and it also saves us lots of effort and reduces environmental impacts.”

Chu and his team used a technique known as pressure quenching, which has been adapted from techniques used to create diamonds. With pressure quenching, researchers first apply intense pressure to the material to enhance its superconducting properties and raise its transition temperature.

Next, researchers are targeting ambient-pressure, room-temperature superconductivity of around 300 K. In a companion PNAS paper, Chu and Deng point to pressure quenching as a promising approach to help bridge the gap between current results and that goal.

“Room-temperature superconductivity has been seen as a ‘holy grail’ by scientists for over a century,” Rohit Prasankumar, director of superconductivity research at Intellectual Ventures, said in the release. “The UH team’s result shows that this goal is closer than ever before. However, the distance between the new record set in this study and room temperature is still about 140 C. Closing this gap will require concerted, intentional efforts by the broader scientific community, including materials scientists, chemists, and engineers, as well as physicists.”

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This article originally appeared on EnergyCapitalHTX.com.