The Excess Returns Of Quality Stocks: A Behavioral Anomaly
[buffett]
Capital Fund Management
Capital Fund Management
Toulouse School of Economics
Capital Fund Management
HEC Paris – Finance Department
January 15, 2016
Abstract:
This note investigates the causes of the quality anomaly, which is one of the strongest and most scalable anomalies in equity markets. We explore two potential explanations. The “risk view”, whereby investing in high quality firms is somehow riskier, so that the higher returns of a quality portfolio are a compensation for risk exposure. This view is consistent with the Efficient Market Hypothesis. The other view is the “behavioral view”, which states that some investors persistently underestimate the true value of high quality firms. We find no evidence in favor of the “risk view”: The returns from investing in quality firms are abnormally high on a risk-adjusted basis, and are not prone to crashes. We provide novel evidence in favor of the “behavioral view”: In their forecasts of future prices, and while being overall overoptimistic, analysts systematically underestimate the future return of high quality firms, compared to low quality firms.
The Excess Returns Of Quality Stocks: A Behavioral Anomaly
Motivation
1.1 The Quality Anomaly
The so-called “quality anomaly” is one of the capital markets’ strongest reported anomalies and has a long tradition among investors (Greenblatt and Tobias (2010), and more recently Asness et al. (2014) Novy-Marx (2013)). It chiefly amounts to ranking firms in terms of their ratio of operating cash-flows (OCF) to total assets or alternatively of their returns to total assets (ROA), as indicators of the profitability (or quality) of the firms. The portfolio is long high-quality stocks and short low-quality stocks, in a market neutral way (see Appendix for more details on the portfolio construction). Figure 1 illustrates the past performance of such a strategy for US stocks. Quite surprisingly, this performance is quite high: even absent cross-country diversification (this is US data only), one already obtains a Sharpe Ratio of 1:2 over the period 1990-2012, corresponding to a highly significant t-stat ~ 6. The same strategy is statistically significant in all geographical zones, and the corresponding signal moves sufficiently slowly so that large amounts of capital can be invested without suffering from prohibitive transaction costs – see (Landier et al., 2015). The quality anomaly is therefore economically significant and works surprisingly well compared to other well-documented anomalies. We report the performance of 8 other anomalies in US equity markets in Table 1. Over the same period (1990-2012), on the same set of stocks, Momentum (Barroso and Santa-Clara, Forthcoming), Low Vol (Ang et al., 2009), Net Repurchasers (Pontiff and Woodgate, 2008) and Industry Leaders (Hou, 2007) all have a Sharpe ratio ~ 0:5; well below the Sharpe ratio of 1.2 for cash-flows to total assets. In addition, signals such as Industry Leaders or Momentum mean-revert more quickly, leading to larger transaction costs and smaller capacities (Landier et al., 2015).
1.2 Risk Premium or Behavioral Anomaly?
The strength, universality and persistence of the quality anomaly cries for an explanation. After all, the information about operating cash-flows is public and can hardly be seen as complex or difficult to process. A possibility – consistent with the Efficient Markets Hypothesis (EMH) – is that these excess returns would be somehow related to a risk premium. High quality stocks could be inherently exposed to a risk factor that investors care about. One possible story could be the following: firms can choose between safe and moderately profitable projects, and risky and more profitable ones. High average cash-flow to assets might indicate that the corresponding firms are themselves, on average, operating on very profitable but riskier segments of the economy and therefore riskier to own. Alternative stories have been proposed, based on the fact that investments cannot be costlessly reversed (see e.g. Zhang (2005), Kisser (2014)). However, while well-known risk premia strategies are indeed rewarding investors for carrying a significant negative skewness risk (see e.g. Harvey and Siddique (2000), Lemperiere et al. (2014)), quality strategies are in fact found to have a positive skewness and a very small propensity to crash – see at the 5% significance level. This shows that analysts, at best, neglect the information contained in cash-flow statements – or even weight it with the wrong sign. In Bouchaud et al. (2015), we study expected earnings by analysts (rather than expected prices) and relate the “stickiness” of analysts’ beliefs to asset mispricing. We believe that these two widespread behavioral biases (misplaced focus and “stickiness”) are at the heart of the quality anomaly.
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