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 Backand 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

Houston Voices

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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Houston universities launch summer 2025 accelerators for student ventures

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OwlSpark, a startup and small business accelerator for Rice University-affiliated ventures, has named the latest 11 companies to its program that focus on challenges across technology, health care, consumer products and other sectors. The program is hosted in tandem with the University of Houston’s RED Labs and will take place at the Ion.

The early-stage accelerator runs for 12 weeks and culminates at The Bayou Startup Showcase on July 31.

According to a news release from Rice, “the accelerator cultivates a vibrant environment where founders are empowered to build, test, and scale their ideas in a setting built for entrepreneurship.”

The program is divided into two tracks: one for high-growth tech startups and another for small businesses.

The latest OwlSpark class includes:

  • Web and mobile platform EasilyBEE, which boosts family and community engagement in K-12 schools
  • Diagnos, a wearable-integrated wellness platform that monitors health and prevents injuries in college athletes
  • Johnnie, an AI-powered records management software for rural and midsize first responder agencies
  • JustKindHumility, which offers faith-based travel journals
  • Klix, whichautomates early-stage clinical trial management from document screening to AI-driven patient outreach and eligibility checks
  • Lizzy’s Gourmet Gains, which offers high-protein, flavor-forward dips and dressings
  • NextStep, an AI-powered multilingual assistant helping underserved communities navigate resources for health care
  • A catheter-integrated sensor device PeriShield, which detects early infection in peritoneal dialysis patients
  • Right Design, which connects creatives with vetted employers, mentors and projects via job matching and commissions
  • UCoreAlly, which provides business support for biotech startups in marketing, business development, customer support, human resources and accounting
  • Ultrasound-based ablation system VentriTech that treats ventricular arrhythmias

The Owl Spark accelerator has supported 229 founders and launched 104 ventures with participants raising more than $116 million in funding since 2013, according to Rice.

Tesla's robotaxi service 'tentatively' to launch in Austin in June, Musk says

Tesla Talk

Elon Musk says Tesla is “tentatively” set to begin providing robotaxi service in Austin on June 22.

In a post on his X social media platform, Musk said the date could change because Tesla is “being super paranoid about safety.”

Investors, Wall Street analysts and Tesla enthusiasts have been anticipating the rollout of the driverless cabs since Musk said earlier this year that the service would launch in Austin sometime in June.

Last month, Musk told CNBC that the taxis will be remotely monitored at first and “geofenced” to certain areas of the city deemed the safest to navigate. He said he expected to initially run 10 or so taxis, increase that number rapidly and start offering the service in Los Angeles, San Antonio, San Francisco and other cities.

Musk has been promising fully autonomous, self-driving vehicles “next year” for a decade, but the pressure is on now as Tesla actually begins to operate a self-driving taxi service.

Sales of Tesla’s electric vehicles have sagged due to increased competition, the retooling of its most popular car, the Model Y, and the fallout from Musk’s turn to politics.

The Austin rollout also comes after Musk had a public blowup with President Donald Trump over the administration’s tax bill. Some analysts have expressed concern that Trump could retaliate by encouraging federal safety regulators to to step in at any sign of trouble for the robotaxis.