Houston research: Can predictive tools help forecast the stock market?

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The stock market has always been hard, if not impossible, to forecast. Image via Getty Images

What do you think the Standard & Poor’s 500 index will do over the next year?

When Rice Business finance professor Kevin Crotty asks his MBA students this question, the answers are all over the map. Some students expect the overall return on the stock market to be 10 percent, while others predict a loss of 20 percent.

This guessing game is closer to real life than many people realize. Experienced investors, people who have watched the stock market ebb and flow for many years, know that making predictions is a risky business. “Many money managers are more confident choosing individual stocks than trying to time the market,” says finance professor Kevin Crotty.

For most of the past century, academics have applied their power of analysis to understanding and predicting the stock market. Recently, some finance researchers have taken a closer look at option prices—the price paid for the right to buy or sell a security (like a stock or bond) at a specified price in the future. Combining economic theory with high-frequency options price data, they argued that they could estimate the expected return on the market in real-time, which would represent a tremendous development for finance practitioners and academics alike.

Crotty teamed up with Kerry Back, a fellow Rice Business professor, and Seyed Mohammad Kazempour, a finance Ph.D. student at the Jones Graduate School of Business, to evaluate whether the new predictors based on option prices really are a valuable forecasting tool. “Options are essentially a forward-looking contract, so it’s possible that they could be used to create a forward-looking measure of expected returns,” says Kazempour.

Economic theory suggests that the new predictors might systematically underestimate expected returns. The team set out to test if this may be the case, and if so, whether the predictors are useful as a forecasting tool. In their paper, “Validity, Tightness, and Forecasting Power of Risk Premium Bounds,” the Rice Business researchers ran the predictors through a more rigorous set of statistical tests that provide more power to detect whether the predictors systematically underestimate expected returns. The statistical tests used in previous research on the topic were less stringent, leading to conclusions that the predictors do not underestimate expected returns.

In short, the new predictors didn’t pass the more stringent tests. The researchers found that forecasts built on stock options consistently underestimated market returns. Moreover, the predictors are enough of an underestimate that they are not very useful as forecasts of market returns.

The results were somewhat anticlimatic, the researchers admit. If the option-based predictors had panned out, it could have become an innovative new tool for thinking about market timing for asset managers as well as investment decision-making for corporate finance projects. “Trying to estimate expected market returns is closely related to whether corporations decide to invest in projects,” notes Crotty. “The expected market return is an input in estimating the cost of capital when evaluating projects, and I explain in my MBA courses that we don’t have very precise estimates for this input. During this research project, I kept thinking about how cool it would be if we really had a better estimate,” he says.

Their research doesn’t end here. Crotty and Back have already begun brainstorming ways to potentially improve the option-based forecasting tool so that it can become more accurate.

At best, though, using option prices as a forecasting tool will only be one ingredient out of many that investors use to make decisions. “This tool may inform money management, but it will never drive it,” says Back.

For now, at least, the Rice researchers believe that trying to predict the stock market is still a very risky game.

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This article originally ran on Rice Business Wisdom and was based on research from Rice Professors Kerry Back and Kevin Crotty.

Investors might be drawn to active fund investing, but index funds might be less risky, according to Rice University researchers. Getty Images

Rice University research finds how index funds can be a good investment opportunity for the risk adverse

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It's easy to assume that investing, like cooking, requires skill to get the right mix of ingredients. But that's not the case with index funds. Effort goes into building them, but these ready-made investments need minimal intervention. Yet the outcomes are appetizing indeed.

In the past few decades, use of index funds has exploded. So have media coverage and advertisements questioning if they can truly compete with active funds. A recent study by Alan Crane and Kevin Crotty, professors at the business school, provides a resounding "yes." These humble investment recipes, it turns out, are richer than they might seem.

Index funds track benchmark stock indexes, from the familiar Dow Jones Industrial Average to the widely followed Standard & Poor's 500. Like viewers following a cooking show, index fund managers buy stocks in the same companies and same proportions as those listed in a stock index. The best-known indices are traditionally based on the size of the companies.

The idea is that the index fund's returns will match those of its model. An S&P 500 index fund, for example, includes stocks in the same 500 major companies included in the Standard & Poor index, ranging from Apple to Whole Foods.

Index funds are part of the broad range of investment products called mutual funds. Like cooks making a stew, mutual fund managers add shares of various stocks into one single concoction, inviting investors to buy portions of the whole mixture.

While some mutual funds are active, meaning professional managers regularly buy and sell their assets, index funds are passive. Their managers theoretically just need to keep an eye on any changes in the index they're copying. Not surprisingly, active index funds tend to charge more than passive ones.

Curiously, not all index funds perform at the same level. So what should that mean for investors? To study these variations and their implications, Crane and Crotty expanded on past research about skill and index fund management, analyzing the full cross section of funds.

This wasn't possible to do until fairly recently: there simply weren't enough index funds to study. The first index fund, which tracked the S&P 500, was developed by Vanguard in the 1970s. To do their research, the Rice Business scholars looked at performance information for both index and active funds, starting their sample in 1995 with 29 index funds. The sample expanded to include a total of 240 index funds, all at least two years old with at least $5 million in assets, mostly invested in common stocks. They also analyzed 1,913 actively managed funds.

Using several statistical models, Crane and Cotty found that outperformance in index-fund returns was greater than it would be by chance. The discovery suggests that passive funds, although they require little skill to run, have almost as much upside as active funds.

In fact, the professors found, the best index funds perform surprisingly closely to the best active funds, but at a lower cost to the investor. The worst active funds perform far worse than the worst index funds–even before management fees.

The findings topple the conventional wisdom that only actively managed funds stand a chance of beating the market. While active-fund managers often measure their success against that of passive funds, the data show investors who are risk averse would do better to choose passive funds over more expensive active ones.

More adventurous investors, of course, will always be tempted by what's cooking in actively managed funds. But overall, investing in plain index funds is as good a meal at a lower price.

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This story originally ran on Rice Business Wisdom.

Alan D. Crane and Kevin Crotty are associate professors of finance at the Jones Graduate School of Business at Rice University.

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Intuitive Machines lands $148M as part of NASA Moon Base funding

to the moon

Houston-based Intuitive Machines has been awarded $148.3 million to deliver its Nova-C lander to the moon by 2028. The funding is part of $600 million that NASA recently awarded to three companies as part of the agency’s Moon Base Program.

The contracts aim to support sustained human presence and commercial operations on the Moon. Austin-based Firefly Aerospace was awarded $144.2 million by NASA for one mission and Pittsburgh-based Astrobotic netted $297.9 million for two lunar landings. Intuitive Machine's award is the company's sixth task order under NASA's Commercial Lunar Payload Services (CLPS) program.

“We’re building a proving ground for Moon Base operations,” Ryan Stephan, NASA’s Moon Base acting director of cargo landers, said in a news release. “Accelerating our Moon mission ordering cadence and launch opportunities enable us to move quickly to learn, iterate, and improve.”

Under the latest task order, Intuitie Machines will deliver three scientific and operational payloads to the moon, which include a:

Linear Energy Transfer Spectrometer (LETS) radiation monitor to gather critical environmental safety data
Advanced stereo cameras to analyze surface-plume interactions (SCALPSS)
Laser retroreflector array (LRA) for precise cislunar positioning

The funding breakdown includes a $68.6 million base contract and a $79.7 million performance incentive for Intuitive Machines.

The company says the funding will allow it to create a standardized and repeatable "lunar utility pipeline" for delivering cargo to the moon.

"We are shifting the paradigm from custom aerospace engineering to commercial mass production of lunar infrastructure," Steve Altemus, CEO of Intuitive Machines, said in a separate news release. "Our flight-proven Nova-C platform allows us to build, test, and deploy multiple landers in parallel using Industry 4.0-powered manufacturing. This contract directly advances our core mission to provide persistent, reliable, and commercial baseline of transport, connectivity, and operations that allows our customers to stay longer and achieve more on the Moon."

NASA also shared that it is exploring plans to send PROMISE, a rover based on the Mars Perseverance and Curiosity rovers, to the moon and it plans to seek proposals for additional lunar lander missions, technology demonstrations, a communications and navigation satellite network, and new science payloads to support its lunar outpost. NASA is developing its Moon Base near the lunar South Pole. The agency expects it to come to fruition sometime after 2032.

Intuitive Machines had received its last CLPS award for $180.4 million in March 2026. It will be the first mission to utilize the company's larger cargo lunar lander, Nova-D. The company was also recently awarded a $1 million grant from Maryland Gov. Wes Moore to expand its robotics operations in the state.

UT team develops wearable technology for atmospheric water harvesting

In The Air

Engineers at the University of Texas at Austin have developed a prototype jacket that harvests clean drinking water directly from the atmosphere, and it works even in the driest desert conditions.

The research, published in Science Advances, marks the latest milestone in nearly a decade of work by materials scientist and chair professor Guihua Yu and his team at the Cockrell School of Engineering's Walker Department of Mechanical Engineering and Texas Materials Institute. The wearable technology marks a significant leap: instead of a bulky, stationary machine, this jacket does the work.

Photo courtesy of UT Austin

"We have been working on atmospheric water harvesting technology for a number of years," Yu says. "This current version is even more wearable. We're transitioning from conventional, more stationary water harvesting to something truly portable and personal."

Yu's lab first published work on hydrogel-based water harvesting around 2019, and the jacket is the latest evolution of that platform, now called AirGel. Last year, the broader AirGel invention won the top prize in the graduate category of the National Collegiate Inventors Competition.

The jacket is woven with specially engineered hydrogel fibers; ultra-porous materials that attract and absorb moisture from the surrounding air much like a household desiccant. Unlike a desiccant, the material doesn't require intense heat to release that water. The hydrogel is thermally responsive, meaning a modest rise in temperature — even from mild solar heating — is enough to release the water it has captured.

So, somebody would be wearing the jacket, or perhaps carrying this gel-like textile as a blanket, as it passively absorbs moisture from the air. Then they would detach the textile panels and place them into a small, portable collector unit; essentially a compact heater. The water evaporates out of the textile, condenses inside the collector, and drips out as clean, drinkable water.

"It immediately becomes drinkable because it already goes through the distillation process," Yu explains.

In trials, the jacket produced between 400 and 900 milliliters of water per day depending on humidity, or roughly 14-30 ounces, nearly a quart, depending on the air's humidity. With one kilogram of the textile, the researchers found they could generate approximately 3.7-4 liters of water in arid conditions, and potentially double that in humid ones. So far, the team has tried the jacket out in very dry, semi-dry, and humid areas, and the jacket was able to pull water from each climate.

Lead researcher Chuxin Lei, a postdoctoral researcher on Yu's team and co-author on the paper, says the goal was to rethink who this technology could serve.

"Many current [atmospheric water harvesting] systems are still built as rigid or stationary platforms, making them less suitable for people who are moving, working outdoors, or operating in some remote environment. This lead us to ask whether we could build a water harvesting system that could become more like clothing — light, wearable, flexible, and naturally suited for personal use," Lei says.

The potential applications are wide-ranging. Yu's team has previously worked with the Department of Defense on water solutions for soldiers, where water logistics can be dangerous and costly. The technology could also serve hikers, emergency responders, disaster relief workers, and agricultural and field workers. Anyone who needs clean water on the go and far from infrastructure.

The team also sees a potential future where the technology complements large-scale centralized water systems rather than replacing them.

"Our solution cannot be a universal solution for all," Yu acknowledges. "But I think it's an extremely important alternative."

For now, the jacket is still a laboratory prototype, but Yu and Lei are optimistic. With the right industry partnerships, they say, the technology could realistically reach commercial scale within three to five years.

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This article originally appeared on CultureMap.com, written by Natalie Grigson.

Houston ranks among world’s top 30 emerging startup ecosystems

Startup Status

Long known as the Energy Capital of the World, Houston also ranks among the world’s top 30 emerging startup ecosystems, according to a new report.

The report from Startup Genome, a research and advisory organization, doesn’t assign a specific numeric ranking to Houston’s startup ecosystem. Rather, it puts Houston in the ranking range of 21 to 30 for emerging ecosystems. Startup Genome weighed factors such as early-stage funding, performance and talent to identify the top emerging ecosystems.

Houston also gained notice for being one of the world’s 20 emerging ecosystems with at least four unicorn startups in the past 10 years. Houston and nine other ecosystems each had four unicorns.

According to StartupBlink, a startup research platform, Houston’s startup ecosystem grew 24 percent in 2025, with over 1,300 startups and total startup funding exceeding $808 million. StartupBlink places Houston at No. 46 among the world’s top 100 startup ecosystems.

In a recent post on LinkedIn, David Horsup, executive in residence at the Rice Alliance Clean Energy Accelerator, wrote that Houston “has all the ingredients to be wildly successful if it stays true to its differentiated pillars that drive the economy — energy, medical, and aerospace.”

Mumbai topped Startup Genome’s list of emerging ecosystems, followed by Istanbul, Madrid, Salt Lake City-Provo and Barcelona. After Salt Lake City-Provo, the top U.S. ecosystems were Phoenix, Detroit, Minneapolis and Las Vegas.

Silicon Valley led Startup Genome’s ranking of the world’s top established ecosystems, followed by New York City, London, Tel Aviv and Boston. Austin landed at No. 18 in this category and Dallas at No. 27.

“For much of the past decade, this report has chronicled the welcome dispersion of opportunity beyond the traditional hubs,” Startup Genome writes. “That trend has not died — but it has been complicated. Capital and scale are consolidating once more, particularly in the United States, and the gap between leading and emerging ecosystems is widening.”

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