There is a heated academic debate about the degree to which market prices of financial assets reflect underlying fundamental values, well summarized by this paper. There are two main schools of thought on the topic: behavioural finance and efficient-market theory. According to the first school of thought, market prices are the result of the interactions of imperfectly rational individuals and therefore subject to potential distortions. According to the efficient-market theory, competition resulting from the presence of many players, each intending to maximize profits, results in market prices reflecting all publicly-available information. My recent article falls somewhere between the two theories. I found that companies with better fundamentals have significantly higher stock (relative) prices, as predicted by the efficient market theory. However, this is true only on average, and there are many stocks that seem to be mispriced. I studied stock returns and found that portfolios of stocks that appear to be undervalued (i.e., with good fundamentals but low prices) have an excess return of about twenty percent per year over portfolios of stocks that appear to be overvalued. Despite this may seem intuitive, it is a result strongly at odds with efficient-market theory, since it means that prices do not reflect publicly available information.
There is then a further fact that fuels the debate about market efficiency. In 2013, the Nobel Prize in economics was awarded to both Eugene F. Fama and Robert J. Shiller, respective exponents of efficient-market theory and behavioural finance and authors of two sharply contrasting Nobel-Prize lectures. Fama wrote ‘‘Two Pillars of Asset Pricing’’, while Shiller wrote ‘‘Speculative Asset Prices’’.
The debate on market efficiency has given rise to a whole line of studies known as ‘‘asset pricing’’. This name leads one to think that the goal of this studies is to determine equilibrium prices. However, almost all of these studies do not attempt to explain prices. The latter are considered only as an independent variable that influences stock returns. However, it should be remembered that, simplifying, returns are price changes over a given period. Thus, in fact, market efficiency depends on prices, more than on returns.
The then President of the American Finance Association, John H. Cochrane, lamented the tendency of most researchers in the field of asset pricing to use prices as an independent variable instead of being the variable to be explained. From his presidential address:
‘‘When did our field stop being “asset pricing” and become “asset expected returning?” (…) What sense does it make to “explain” expected returns by the covariation of expected return shocks with market expected return shocks? Market/book ratios should be our left-hand variable, the thing we’re trying to explain, not a sorting characteristic for expected returns.’’
A study using an elaborate econometric technique (Asness et al. 2019) found that, other things being equal, the stocks of firms that are more profitable, growing at higher rates, and less risky tend to trade at higher relative prices. Nevertheless, when prices are regressed against fundamentals, the authors found that the adjusted coefficient of determination (adjusted R2) is low and about ten percent. The authors then studied the performance of some quality-sorted portfolios and found that portfolios of high-quality stocks tended to offer significantly better absolute and risk-adjusted returns than portfolios of low-quality stocks. In other words, these results would point to a tendency for the market to under-reward stock fundamentals. My recent paper aims to extend the study of Asness et al. (2019), as their findings have important implications in the market efficiency debate and their econometric methodology – illustrated in the next paragraph – was very innovative. While keeping basically the same econometric methodology, I have done some changes and additions to this study, in order to improve results.
First, I illustrated theoretically, through the extension of the Gordon growth model, how firm fundamentals influence firm value (and consequently should influence price). Other things being equal, investors should be willing to pay higher prices for firms that are more profitable, rapidly growing, less risky, with more liquid securities, and have better governance. The empirical analysis is conducted on a global sample of more than five thousand securities of non-financial firms from June 2004 through June 2021. To perform the empirical analysis, I constructed six scores that capture the characteristics of firms for which investors should be willing to pay higher prices, as demonstrated in theory. In particular, I constructed a profitability score, a growth score, a risk score, a liquidity score, a governance score, and a synthetic quality score obtained as a simple average of all the previous score. The liquidity score and governance score are new compared to Asness et al. (2019), while the growth score is determined differently. To determine each score, I used the average of several accounting ratios or market measures. For instance, to compute the profitability score, I used Return on Equity, Return on Invested Capital, Gross Margin, Operating Cash Flow on Assets, and Gross Profits on Assets. In calculating the scores, each variable was first ranked and then standardized to obtain results that are easily interpretable and not influenced by extreme values. This methodology has several advantages. It minimizes firms to be discarded from the sample due to lack of data, since when a single measure is missing, I consider the average of the remaining to compute the score. If, for example, for a firm, Return on Equity is missing, I calculate the profitability score simply using Return on Invested Capital, Gross Margin, and so on. If, on the other hand, the profitability score had depended only on Return on Equity, I would have had to discard the company from the sample. Furthermore, combining more similar measures into a single score avoids multicollinearity problems and allows not to focus too much on a single measure, as each has its own limitations. After defining the scores for each security in all periods, the prices (relative to the book value, i.e., the price to book ratio) were regressed against the scores.
Empirical evidence is consistent with theory, as stocks of companies that are more profitable, rapidly growing, less risky, more liquid, and with better governance tend to be more expensive. In my paper, firm fundamentals explain about thirty percent of the cross-sectional variability in stock prices, compared to the ten percent obtained by Asness et al. (2019). By modifying the definition of the growth component and adding the liquidity score and governance score, I was able to improve on that study. The way firm fundamentals are reflected in market prices varies over time. In particular, consistent with the findings of Asness et al. (2019), market prices were less affected by fundamentals just before the great financial crisis. Indeed, until just before the outbreak of the financial crisis, all else being equal, more liquid stocks and stocks of less risky firms were traded, on average, at lower relative prices. This evidence is strongly at odds with what is predicted by the theory of efficient market.
Another interesting piece of evidence concerns more recent times: market prices have significantly increased over the entire period studied, but the same trend is not observed for fundamentals, which seem to have worsened when we compare them with pre-COVID data from 2019.
Asness et al. (2019) studied the performance of some portfolios composed of stocks sorted by quality. In my paper, portfolios are constructed through a process of sorting by two characteristics: quality and price. Sorting only by quality means composing a portfolio regardless of prices. Since quality and prices are correlated, the portfolio of the highest quality securities is usually also the most expensive one. Sorting by quality and prices means composing portfolios of securities that present the best quality/price ratio. Since the portfolios resulting from the two construction methodologies are very different from those of Asness et al. (2019), it is reasonable to expect new results. I have divided the stocks into deciles, where the first decile is composed of the stocks with the worst measured fundamentals and highest prices, while the last decile is composed of the stocks with the best measured fundamentals and lowest prices. In other words, the first decile is composed of apparently overvalued securities, while the last decile is composed of apparently undervalued securities. Finally, I considered a country-neutral portfolio that funds a long position on the last decile of securities through a short position on the first decile of securities.
The performance of these portfolios is remarkable. First, returns increase almost monotonically across the ten deciles of stocks, while almost the opposite happens for risk. The long-short portfolio offered very high returns with low riskiness. Specifically, this portfolio has offered an annual return of about 19%, whose annualized volatility is less than 7%. The annual return is almost three times that of the market portfolio, while volatility is almost half. As a result, risk-adjusted performance measures are also significantly better than that of the market portfolio. Again, out of 204 total monthly observations, the long-short portfolio offered positive returns in 163 months (i.e., 80% of the months), while it offered positive annual returns in all years under study. In more technical terms, this strategy generated abundantly positive and statistically significant alpha against the main asset pricing models known in the academic literature. This strategy has a negative market exposure, i.e., it tends to move in the opposite direction with respect to the market portfolio, proving to be an interesting tool in portfolio management.
My work is thus a further piece in the asset pricing puzzle. The empirical results show that the market rewards, in terms of pricing, firms with the best fundamentals, consistent with efficient markets theory. However, the excellent performance of the long-short investment strategy seems to challenge the efficient-market theory, because according to the theory there should be a strictly positive relationship between risk and return.
One possible interpretation of these two pieces of evidence is that observed prices in equity markets are generally quite efficient and tend to converge to fundamental values. However, in the short term, prices of some stocks may deviate significantly from fundamentals. The excellent performance of the long-short strategy described above could result from the process of price adjustment over time.
Fabio Pulcini is a graduate student studying Finance at the Università degli studi Roma TRE.
This post is adapted from the author’s paper, “Do Stock Prices Reflect Firms Fundamentals? An Empirical Analysis of a Large Global Sample,” available on SSRN.
The views expressed in this post are those of the author and do not represent the views of the author’s firm, the Global Financial Markets Center or Duke Law.