Academic research has proved that one of the most available pieces of business data—the growth in the book value of assets could be very valuable for investors. The aforementioned data can be utilized in a popular trading strategy based on the growth effect anomaly. There is a strong asset growth effect in U.S. stock returns, and this paper updates the previous results of Cooper, Gulen, and Schill. The idea is simple; on a risk-adjusted basis, low asset growth stocks significantly outperform high asset growth stocks. This effect is consistent over time with the returns of low asset growth stocks exceed those of high asset growth stocks in 90% (equal-weighted) or 72% (value-weighted) of the calendar years in the sample of the paper. Additionally, despite the fact that a return differential is larger among small-capitalization stocks, the authors have shown that the effect is still economically and statistically large also among large-capitalization stocks. Therefore, the strategy could be easily implemented with only small trading and slippage costs.
Interestingly, the authors state that a firm’s growth rate in assets is at least as powerful in explaining returns as other well-known effects such as size, book-to-market, return momentum and reversals. Moreover, the proposed strategy, which consists of buying low asset growth stocks and selling the high asset growth stocks has a low correlation to the equity market factor.
Similar results can be found for example in the work of Watanabe, Xu, Yao and Yu: “The Asset Growth Effect: Insights from International Equity Markets”. The authors say that stocks with higher asset growth rates experience lower future returns in 40 international equity markets, consistent with the U.S. evidence documented by Cooper et al. (2008). This negative effect of asset growth on stock return is stronger in developed markets and in markets where stocks are more efficiently priced.
A variety of papers suggest that the return premium achieved by low asset growth stocks is consistent with compensation for risk (for example Gomes, Kogan, and Zhang, 2003; and Li, Livdan, Zhang, 2008). Firms maintain a mix of growth options and assets in place, but growth options are inherently more risky than assets in place. As firms exercise growth options, the asset mix of the firm becomes less risky as assets in place displace growth options. The systematic reduction in risk following the exercise of growth options induces a negative correlation between investment and subsequent returns. However, empirical findings are all also consistent with systematic mispricing across asset growth as a firm characteristic. Therefore, the authors are unable to recognize whether the return premium for low growth stocks is due to systematic variation in risk or the return reversal caused by systematic overcapitalization of high growth stocks and undercapitalization of low growth stocks. Building on that, another past research has concluded that the asset growth effect is not fully explained by variations in risk.
However, there is a possibility that the effect is at least partially due to the systematic market mispricing of growing businesses. That source of mispricing could be caused by the extrapolation of past gains to growth for high asset growth companies. A good insight on the reasons for functionality could be found in the work of Kam and Wei: “Asset Growth Reversals and Investment Anomalies”. Quoting the authors: “We simultaneously test the prominent rational and behavioral explanations of the negative relations between corporate asset growth or investments and subsequent stock returns by extensively examining the effects of realized and predicted subsequent growth on the relations. We find: (i) returns on low growth firms with low subsequent growth are not higher than those on high growth firms with subsequent high growth; (ii) high growth firms that have subsequent high growth do not underperform and the return spreads between low and high growth firms are lower when high growth firms have higher subsequent growth; (iii) the relations between growth and returns are weak or even in opposite direction when subsequent growth tend not to reverse but are significantly negative when subsequent growth tend to reverse and are stronger when the reversals are more extreme. Our findings are consistent with the hypothesis based on extrapolation and growth-based style investing but less consistent with the other explanations.”
Confidence in anomaly's validity
Backtest period from source paper
Notes to Confidence in Anomaly's Validity
Period of Rebalancing
Notes to Indicative Performance
per annum, annualized (geometrically) monthly return 1,59% from table 2
Notes to Period of Rebalancing
Number of Traded Instruments
Notes to Estimated Volatility
estimated from t-statistic, data from table 2
Notes to Number of Traded Instruments
more or less, it depends on investor’s need for diversification
Notes to Maximum drawdown
Notes to Complexity Evaluation
Simple trading strategy
The investment universe consists of all non-financial U.S. stocks listed on NYSE, AMEX, and NASDAQ. Stocks are then sorted each year at the end of June into ten equal groups based on the percentage change in total assets for the previous year. The investor goes long decile with low asset growth firms and short decile with high asset growth firms. The portfolio is weighted equally and rebalanced every year.
Cooper, Gulen, Schill: The Asset Growth Effect in Stock Returns
We document a strong negative relationship between the growth of total firm assets and subsequent firm stock returns using a broad sample of U.S. stocks. Over the past 40 years, low asset growth stocks have maintained a return premium of 20% per year over high asset growth stocks. The asset growth return premium begins in January following the measurement year and persists for up to five years. The firm asset growth rate maintains an economically and statistically important ability to forecast returns in both large capitalization and small capitalization stocks. In the cross-section of stock returns, the asset growth rate maintains large explanatory power with respect to other previously documented determinants of the cross-section of returns (i.e., size, prior returns, book-to-market ratios). We conclude that risk-based explanations have some difficulty in explaining such a large and consistent return premium.
Strategy's implementation in QuantConnect's framework (chart+statistics+code)
Cooper, Gulen, Schill: Asset Growth and the Cross-Section of Stock Returns
We test for firm-level asset investment effects in returns by examining the cross-sectional relation between firm asset growth and subsequent stock returns. As a test variable, we use the year-on-year percentage change in total assets. Asset growth rates are strong predictors of future abnormal returns. Asset growth retains its forecasting ability even on large capitalization stocks, a subgroup of firms for which other documented predictors of the cross-section lose much of their predictive ability. When we compare asset growth rates with the previously documented determinants of the cross-section of returns (i.e., book-to-market ratios, firm capitalization, lagged returns, accruals, and other growth measures), we find that a firm’s annual asset growth rate emerges as an economically and statistically significant predictor of the cross-section of U.S. stock returns.
Watanabe, Xu, Yao, Yu: The Asset Growth Effect: Insights from International Equity Markets
Stocks with higher asset growth rates experience lower future returns in 40 international equity markets, consistent with the U.S. evidence documented by Cooper et al. (2008). This negative effect of asset growth on stock return is stronger in developed markets and in markets where stocks are more efficiently priced. For each country, we estimate a parsimonious model to quantify the cash flow channel and the discount rate channel of the investment-return relationship proposed by the q-theory model of Li, Livdan, and Zhang (2008). The estimated cash flow beta and discount rate beta successfully explain the cross-country variation in the asset growth effect on future stock returns. In contrast, country characteristics related to corporate governance and investor protection, and measures of limits to arbitrage, do not explain such effect. This evidence suggests that the q-theory model does better than mispricing-based hypotheses in explaining the asset growth effect internationally.
Kam, Wei: Asset Growth Reversals and Investment Anomalies
We simultaneously test the prominent rational and behavioral explanations of the negative relations between corporate asset growth or investments and subsequent stock returns by extensively examining the effects of realized and predicted subsequent growth on the relations. We find: (i) returns on low growth firms with low subsequent growth are not higher than those on high growth firms with high subsequent growth; (ii) high growth firms that have high subsequent growth do not underperform and the return spreads between low and high growth firms are lower when high growth firms have higher subsequent growth; (iii) the relations between growth and returns are weak or even in opposite direction when subsequent growth tend not to reverse but are significantly negative when subsequent growth tend to reverse and are stronger when the reversals are more extreme. Our findings are consistent with the hypothesis based on extrapolation and growth-based style investing but less consistent with the other explanations.
Beneish, Lee, Nichols: In Short Supply: Equity Overvaluation and Short Selling
We use detailed security lending data to examine the relation between short sale constraints and equity overvaluation. We find that stocks’ “special” status exhibits a non‐linear (U‐shaped) relation with their short interest ratio (SIR), and that a stock’s special status, rather than its SIR, predicts negative returns. We show that short‐sellers trade on a variety of firm characteristics and against high sentiment. Specifically, we find: (1) the abnormal returns to the short‐side of nine market ‘anomalies’ identified in prior work are attributable to special stocks; and (2) future negative returns to special stocks are directly related to the lendable inventory in each stock rather than to its shares borrowed. Overall, our results suggest returns to the short side of documented ‘anomalies’ may not be obtainable without significant cost, and that the supply (available inventory) of lendable shares is the primary binding constraint to informational arbitrage in the case of equity overvaluation.
Fu: What Is behind the Asset Growth and Investment Growth Anomalies?
Existing studies show that firm asset and investment growth predict cross-sectional stock returns. Firms that shrink their assets or investments subsequently earn higher returns than firms that expand their assets or investments. I show that the superior returns of the low asset and investment growth portfolios are due to the omission of delisting returns in CRSP monthly stock return file and that the poor returns of the high asset and investment growth portfolios are largely driven by the subsample of firms that have issued large amounts of debt or equity in the previous year. Controlling for the effects of the delisting bias and external financing, I do not find an independent effect of asset or investment growth on stock returns.
Fan, Opsal, Yu: Equity Anomalies and Idiosyncratic Risk Around the World
In this study, we examine how idiosyncratic risk is correlated with a wide array of anomalies, including asset growth, book-to-market, investment-to-assets, momentum, net stock issues, size, and total accruals, in international equity markets. We use zero-cost trading strategy and multifactor models to show that these anomalies produce significant abnormal returns. The abnormal returns vary dramatically among different countries and between developed and emerging countries. We provide strong evidence to support the limits of arbitrage theory across countries by documenting a positive correlation between idiosyncratic risk and abnormal return. It suggests that the existence of these well-known anomalies is due to idiosyncratic risk. In addition, we find that idiosyncratic risk has less impact on abnormal return in developed countries than emerging countries. Our results support the mispricing explanation of the existence of various anomalies across global markets.
Prombutr, Phengpis, Lam: Anatomy of the Mispricing Theory: Evidence from Growth Anomalies
This paper investigates corporate growth anomalies in asset pricing from behavioral perspectives. Cross-sectional analyses indicate that a long-term 3-year investment growth is statistically significant in explaining subsequent stock returns, but the first 1-year growth that is closest to the formation is priced by investors the most, followed by the second and third ones, monotonically. We find that the evidence is driven by myopic mispricing in that investors tend to put more weights on recent information since the evolution of the firm’s prospects around the formation year consistently shows that the growth closest (farthest) to the formation has the most (least) severe mispricing. Further investigations show that the mispricing evolution is directly amplified by limits to arbitrage and that benchmark-adjusted returns on short positions are affected more than those on long positions. However, the farther growth is less sensitive to the limit-to-arbitrage because of the extrapolation is myopic. The asset growth anomaly also shows the same pattern as the investment growth anomaly.
Lu, Stambaugh, Yuan: Anomalies Abroad: Beyond Data Mining
A pre-specified set of nine prominent U.S. equity return anomalies produce significant alphas in Canada, France, Germany, Japan, and the U.K. All of the anomalies are consistently significant across these five countries, whose developed stock markets afford the most extensive data. The anomalies remain significant even in a test that assumes their true alphas equal zero in the U.S. Consistent with the view that anomalies reflect mispricing, idiosyncratic volatility exhibits a strong negative relation to return among stocks that the anomalies collectively identify as overpriced, similar to results in the U.S.