Can Anyone Really Beat the Market Consistently?
by Chris Brown, Ph.D., MBA, CFP® and Ron A. Rhoades, JD, CFP®
This is Part 3 of Scholar Financial’s “Evidence-Based Investing” series. To view the entire series, click here. To receive bi-weekly updates on the rest of this series, please join our email newsletter by clicking here.
Dr. Patricia Chen had spent her career as a physics professor, teaching students that the universe operates according to predictable laws. When she turned 59 and began seriously planning for retirement, she assumed the investment world would work similarly. Surely, with enough analysis – the right charts, the right research, the right expert, and even the use of artificial intelligence – someone could predict which investments would outperform.
She was about to discover something that humbled her: when it comes to beating the market, even the smartest people on Wall Street struggle. Her discovery would also reveal a surprising silver lining – one that would fundamentally change how she approached investing.
The Efficient Market Hypothesis
In the 1960s, economist Eugene Fama developed what would become one of the most influential—and controversial—ideas in finance: the Efficient Market Hypothesis (EMH).(1) In its semi-strong form, EMH suggests that all publicly available information about investments is already reflected in their prices.(2)
Think about what this means. When a company announces strong earnings, that information is almost instantly incorporated into the stock price, often within milliseconds (due to the utilization of sophisticated and powerful computers and algorithms). When economic data suggests a recession, markets adjust – often within seconds. In a world of algorithmic trading, satellite imagery of parking lots, and armies of analysts, new information spreads and is acted upon with remarkable speed.
The implication is startling: if prices already reflect all available information, then no amount of analysis can consistently give an investor an edge over the entire market. The semi-strong form of EMH suggests that technical analysis (charting), fundamental security analysis (stock and bond analysis in search of intrinsic values), and tactical asset allocation (market timing) are unlikely to consistently outperform.(3)
The Professional Track Record
If beating the market were possible with skill, we would expect professional asset managers – with their advanced degrees, sophisticated tools, and full-time focus – to do it consistently. But research tells a different story.
Study after study shows that most actively managed mutual funds underperform their benchmark indices over longer periods of time, especially after accounting for fees and taxes. The few that do outperform in any given period rarely repeat their success. Past performance, as the disclaimers honestly state, really isn’t a reliable predictor of future results.
This doesn’t mean markets are perfectly efficient – some anomalies exist. But for the average investor, the research strongly suggests that trying to beat the market through stock picking or market timing is an uphill battle with long odds.
If You Can’t Beat the Market, What Can You Do?
Here’s where Patricia’s discovery took an encouraging turn. While consistently beating the market may be impractical, Evidence-Based Investing suggests focusing on what you can control: capturing market returns through broad diversification, controlling costs, minimizing taxes, and maintaining discipline during market volatility.
Moreover, academic research has identified something fascinating: while predicting which stocks will outperform is nearly impossible, certain characteristics of stocks have been associated with higher returns over long periods. These characteristics are called “factors.”
The Factor Revolution
A “factor” is a trait or condition that can affect how an investment performs. A factor can also be viewed as the spread between the return of one set of securities with defined characteristics versus another set of securities without those characteristics.(4)
In 1992 and 1993, Eugene Fama and Kenneth French published groundbreaking papers introducing their three-factor model.(5) They discovered that stock returns are primarily driven by exposures of the investment portfolio to market risk (equities), size (smaller companies tend to outperform larger ones over long periods of time), and value (stocks that are inexpensive relative to their fundamentals tend to outperform more expensive ones over long periods of time).
Later research expanded this framework. Additional factors that academic research supports include profitability (companies with high profits relative to their assets tend to outperform), investment patterns (companies that invest less heavily in capital expenditures tend to outperform), and momentum (investments performing well recently often continue performing well in the near term).
Research reveals that the current Fama-French six-factor model can explain about 85% to 93% of a diversified portfolio’s return.(6) This is remarkable – it means the vast majority of the gross returns of an investment portfolio can be understood through a handful of well-documented characteristics.
Navigating the Factor Zoo
Economist John Cochrane famously referred to the proliferation of alleged factors as a “zoo of factors.”(7) Hundreds of factors have been proposed over the years, but many were based on data mining rather than solid economic theory. Today, research indicates that only about a dozen or so well-established factors are sufficient to explain most investment returns – and some of these factors overlap each other.(8)
For practical investors, this means focusing on the factors that have strong theoretical foundations and have been verified across multiple time periods and markets. The size, price (value), profitability (or quality), and momentum factors appear to possess the strongest research support, followed by low-volatility, investment, and carry factors.
Patricia’s New Perspective
As Patricia learned about the scientific evolution in the investment community from her new financial and investment advisers, she eventually embraced what the evidence was telling her. “As a physicist, I had to follow where the data led,” she explained, “and the data said that trying to pick winning stocks or time the market was a fool’s errand. Instead, my advisors showed me that there were systematic ways to tilt a portfolio toward characteristics associated with higher returns.”
At age 59½, Patricia took advantage of the little-known rule allowing educators in many universities and school systems to roll over their 403(b) accounts to an IRA while still employed. While she was able to continue to contribute to her 403(b) plan, this gave her access to lower-cost, factor-based investment options that were not available in her university’s retirement plan – with the assistance of fiduciary, fee-only advisors who specialized in evidence-based investment approaches.
Can anyone consistently beat the market? The evidence says no – at least not through traditional stock picking or market timing. But that doesn’t mean investors are helpless. By understanding market efficiency and harnessing the power of well-documented factors, you can build a portfolio designed to capture the returns the market offers – and potentially a bit more.
About the Authors
Ron A. Rhoades, JD, CFP®
Ron Rhoades is an Associate Professor of Finance at the Gordon Ford College of Business, Western Kentucky University. He also serves as a financial advisor at Scholar Financial, a practice within XY Investment Solutions LLC. With a background as both an attorney and a CERTIFIED FINANCIAL PLANNER™ professional, Ron is a nationally recognized authority on the fiduciary duties of financial advisors.
Chris Brown, Ph.D., CFP®
Chris Brown is a faculty member in the Department of Finance at the Gordon Ford College of Business, Western Kentucky University, and a financial advisor at Scholar Financial, a practice within XY Investment Solutions, LLC. He holds the CERTIFIED FINANCIAL PLANNER™ designation and a Ph.D. in Personal Financial Planning. His research and teaching focus is on behavioral finance, retirement planning, and evidence-based investment strategies.
Endnotes
1. Fama, E. F. (1970). “Efficient capital markets: A review of theory and empirical research.” The Journal of Finance, 25(2), 383-417.
2. See, e.g., Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. Journal of Finance, 25(2), 383-417; Fama, E. F. (1991). Efficient capital markets: II. Journal of Finance, 46(5), 1575-1617; Jensen, M. C. (1978). Some anomalous evidence regarding market efficiency. Journal of Financial Economics, 6(2-3), 95-101; Malkiel, B. G. (1973). A random walk down Wall Street. W.W. Norton & Company; Samuelson, P. A. (1965). Proof that properly anticipated prices fluctuate randomly. Industrial Management Review, 6(2), 41-49.
3. Ibid.
4. Sheeraz Raza, Cliff Asness — Smart Beta: The Siren Song of Factor Timing, ValueWalk (Feb. 2, 2020).
5. Fama, E. F., & French, K. R. (1992). “The Cross-Section of Expected Stock Returns.” The Journal of Finance, 47(2), 427-465; Fama, E. F., & French, K. R. (1993). “Common risk factors in the returns on stocks and bonds.” Journal of Financial Economics, 33(1), 3-56.
6. Fama, E. F., & French, K. R. (2018). ”Choosing factors.“ Journal of Financial Economics, 128(2), 257-279.
7. John Cochrane of the University of Chicago coined the term “zoo of factors” in his 2011 presidential address to the American Finance Association. Cochrane, John H. 2011. “Presidential Address: Discount Rates.” Journal of Finance, vol. 66, no. 4 (August):1047- 1108.
8. Swade, Alexander and Hanauer, Matthias Xaver and Lohre, Harald and Blitz, David, Factor Zoo (.zip) (October 18, 2023).
This article is for educational purposes only. It should not be construed as financial, legal, tax, or investment advice, nor as a recommendation to implement any specific strategy, product, or investment. Consult with a qualified financial professional before making investment decisions.
