This page reviews "The Other Side of Value: The Gross Profitability Premium," a 2013 paper by Robert Novy-Marx. The researcher found that profitable companies, measured by gross profits divided by total assets, earn significantly higher stock returns than unprofitable companies. This "gross profitability premium" is roughly as strong as the value premium, meaning the researcher documented that profitability served as a statistically significant predictor of returns, comparable in magnitude to the value factor.

Published in the Journal of Financial Economics, 108(1), 1–28, the paper revealed a surprising twist: profitable companies tend to be "growth" stocks (expensive on traditional value measures like price-to-book). This makes the profitability strategy a natural complement to value investing. A portfolio that combines cheap stocks with profitable stocks performs much better than either approach alone, because the two strategies pick fundamentally different types of companies.

Key Findings

The paper's central contribution is demonstrating that a simple accounting measure, gross profitability, predicts stock returns with the same power as the value factor. This finding expanded the set of known return drivers and directly influenced how researchers and investors think about factor-based investing.

The Gross Profitability Premium

Novy-Marx sorted all U.S. stocks into five groups (quintiles) based on their gross profitability, defined as gross profits (revenue minus cost of goods sold) divided by total assets. The most profitable quintile outperformed the least profitable quintile by about 0.31% per month, which translates to roughly 3.7% annually. This spread is statistically significant and economically meaningful: the premium was both statistically significant and economically meaningful within the study's framework.

The premium held up after controlling for known factors. Even after accounting for market risk, company size, and the value factor using the Fama-French three-factor model (a standard framework for measuring stock returns beyond what the overall market explains), gross profitability still produced a significant extra return. This means profitability captures something about stock returns that existing models were missing.

Why Gross Profits?

The researcher argued that gross profit (revenue minus cost of goods sold) provides a more transparent view of a company's economic productivity than net income or operating income. The reason is that items further down the income statement are more easily manipulated through accounting choices. Companies can change the way they record depreciation, restructure charges, tax provisions, and one-time items to make bottom-line earnings look better or worse than the underlying business warrants.

Gross profit sits near the top of the income statement and is harder to game. It captures the fundamental relationship between what a company earns from its products and what those products cost to produce. By scaling gross profit by total assets, the measure also accounts for how efficiently the company uses its resources. A company that generates high gross profits relative to its asset base is converting its resources into revenue more effectively than its peers.

The "Other Side of Value"

Traditional value investing focuses on buying cheap stocks: companies whose stock price is low relative to their book value, earnings, or cash flow. But cheap stocks are often unprofitable companies in financial trouble. The profitability premium captures the opposite side of the equation: companies that are fundamentally healthy and productive, generating strong revenue relative to their costs.

The paper showed that when both factors are used together, they identify different types of mispricing in the market. Value finds stocks the market has priced too low. Profitability finds stocks whose fundamental quality the market has not fully rewarded. Because these two signals point at different sets of companies, combining them produces a more diversified and more powerful portfolio than either signal alone.

Subsumes Other Predictors

One of the paper's strongest results is that gross profitability has more predictive power than many other commonly cited return predictors. The researcher tested gross profitability against earnings-to-price, cash flow-to-price, and dividend yield, among others. In head-to-head comparisons, gross profitability explained more of the variation in stock returns than these alternatives. This suggests that the simplest and most transparent measure of profitability is also the most useful for predicting returns.

Profitability and Value as Complements

The relationship between profitability and value is one of the paper's most practically important findings. Profitable firms tend to have high valuations because the market recognizes their strong fundamentals and bids up their stock prices. As a result, highly profitable companies often appear "expensive" on traditional value measures like price-to-book. Conversely, cheap stocks (the ones value strategies buy) tend to have weak profitability because they are often struggling businesses.

This means profitability and value strategies naturally pick different stocks. A value portfolio is concentrated in beaten-down companies trading at low multiples. A profitability portfolio is concentrated in healthy, productive companies that may trade at higher multiples. Because they select from different parts of the market, combining the two approaches provides genuine diversification: when one strategy underperforms, the other tends to hold up.

Novy-Marx demonstrated that a portfolio combining cheap stocks with profitable stocks earned higher risk-adjusted returns (returns relative to the amount of risk taken) than either strategy on its own. The combined approach captured two distinct sources of extra return while reducing the overall variability of the portfolio. This insight had a lasting impact on the field. Fama and French (2015) added a profitability factor (called RMW, for "Robust Minus Weak") to their original three-factor model, creating the now widely used five-factor model. The direct influence of Novy-Marx's work on this expansion is well documented.

Practical Implications

Multi-Factor Enhancement

Adding profitability to a value strategy directly addresses what investors call the "value trap" problem. Value traps are stocks that look cheap on accounting measures but stay cheap (or get cheaper) because the underlying business is in decline. These companies may have low price-to-book ratios precisely because their earnings are deteriorating.

The researcher demonstrated that incorporating a profitability filter historically reduced exposure to many of these traps. Stocks that are both cheap and profitable are companies where the market appears to have underpriced a fundamentally sound business. This combination identifies a more promising set of value stocks than cheapness alone and has historically produced better risk-adjusted returns.

Smart Beta Applications

The paper's findings have directly influenced the design of "smart beta" and "quality" Exchange-Traded Funds (ETFs). Many rules-based index products now incorporate profitability as a factor weight, either on its own or alongside value, momentum, and low volatility. These products translate the academic finding into investable strategies accessible to individual investors.

The transparency of gross profitability as a metric makes it particularly well-suited for rules-based strategies. Unlike complex proprietary signals, gross profitability can be calculated from publicly available financial statements using a straightforward formula. This transparency allows investors to understand exactly what they own and why.

A Simple Screening Tool

For investors who build their own stock portfolios, gross profitability provides a simple, transparent screening metric. It requires only two data points from a company's financial statements: revenue, and cost of goods sold (COGS). Dividing gross profit (revenue minus COGS) by total assets produces the ratio. No complex modeling, no proprietary data, and no specialized software is needed.

The research suggests that utilizing this metric as a first-pass filter may assist in identifying companies with stronger fundamentals. Investors who already screen for cheap stocks can add a profitability filter to tilt their selections toward companies with stronger fundamentals, potentially avoiding the weakest businesses in their value screens.

Persistence Across Markets and Time Periods

Subsequent research has confirmed that the profitability premium appears across different time periods, market conditions, and international markets. It is not limited to the specific U.S. sample Novy-Marx studied. This persistence is important because patterns that show up in only one market or one time period could be statistical coincidences. A pattern that repeats across multiple independent datasets is more likely to reflect a genuine economic relationship.

How the Researcher Tested This

Data and Time Period

The study used data on all stocks listed on the New York Stock Exchange (NYSE), American Stock Exchange (AMEX), and NASDAQ with available accounting data from Compustat, covering the period from 1963 to 2010. This nearly five-decade span includes very different market environments: the stagflation of the 1970s, the bull market of the 1980s and 1990s, the dot-com bubble and crash, and the 2008 financial crisis. Testing across such varied conditions strengthens the case that the profitability premium is a persistent phenomenon, not an artifact of one particular era.

Measurement and Sorting

The key measure is gross profitability: gross profits (revenue minus cost of goods sold) divided by total assets. Each year, all stocks were sorted into quintiles (five groups of equal size) based on this ratio. The researcher then tracked the returns of each quintile over the following year. The main test portfolio bought the highest-profitability quintile and sold (shorted) the lowest-profitability quintile, isolating the return difference attributable to profitability alone.

Controlling for Known Factors

To ensure the profitability premium was not simply a repackaging of an already known pattern, Novy-Marx controlled for the three Fama-French factors: market risk (the tendency of all stocks to move with the overall market), size (the tendency of smaller companies to earn higher returns), and value (the tendency of cheap stocks to outperform expensive ones). After adjusting for all three factors, the profitability premium remained statistically significant.

The researcher also tested the premium within subgroups: large stocks versus small stocks, and growth stocks versus value stocks. The profitability effect appeared in both large and small companies, and in both growth and value universes, though with some variation in magnitude. This broad applicability strengthens the finding because it rules out explanations that depend on a single market segment.

Why Does It Work?

The paper offers several potential explanations for why the market does not fully price in the information contained in gross profitability. Understanding these explanations matters because it helps assess whether the premium is likely to persist or to shrink as more investors try to capture it.

Investor Attention

One explanation is that investors may focus too much on bottom-line earnings (net income) and not enough on gross profitability. Earnings per share is the most widely followed accounting number in financial media and analyst reports. Gross profit receives comparatively little attention. If investors systematically overlook this metric, stocks with high gross profitability may be underpriced relative to their fundamental quality.

Growth Expectations

Profitable companies may have conservative growth expectations priced in by the market. If investors assume that current high profitability will mean-revert (return to average levels), they may not pay the full price that the profitability warrants. When profitability proves more persistent than the market expects, the resulting positive surprises drive higher returns over time.

Quality Mispricing

The market may not fully price the persistence of high gross profitability. Companies with strong gross margins often maintain them for years because they reflect durable competitive advantages: brand strength, cost efficiencies, or proprietary technology. If investors treat these margins as temporary, profitability stocks will be systematically undervalued.

Valuation Theory

The paper also provides a theoretical framework linking profitability to expected returns through the dividend discount model (a standard valuation equation that prices a stock based on its future cash flows). At a given price level, a more profitable firm generates higher cash flows and therefore offers a higher expected return. This relationship holds mechanically in valuation models, but the empirical finding is stronger than the theory alone would predict, suggesting additional behavioral or informational factors are at play.

Limitations and Caveats

Related Research

Further Reading

• Novy-Marx, R. (2013). "The Other Side of Value: The Gross Profitability Premium." Journal of Financial Economics, 108(1), 1–28.
• Fama, E.F. and French, K.R. (2015). "A Five-Factor Asset Pricing Model." Journal of Financial Economics, 116(1), 1–22.
• Fama, E.F. and French, K.R. (1993). "Common Risk Factors in the Returns on Stocks and Bonds." Journal of Financial Economics, 33(1), 3–56.
• Novy-Marx, R. (2014). "Quality Investing." Working Paper.
• Asness, C.S., Frazzini, A., and Pedersen, L.H. (2019). "Quality Minus Junk." Review of Accounting Studies, 24(1), 34–112.