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Review of Accounting Studies

Erschienen in:

01.03.2012

Using residual income to refine the relationship between earnings growth and stock returns

verfasst von: Sudhakar Balachandran, Partha Mohanram

Erschienen in: Review of Accounting Studies | Ausgabe 1/2012

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Abstract

We use residual income (RI) to decompose earnings growth into growth in RI, growth in invested capital and other components and use this decomposition to explain stock returns. Our approach provides a significant increase in explanatory power vis-à-vis a regression of returns on levels and changes in earnings. While the market values growth in RI more than growth in invested capital, it still undervalues growth in RI and overvalues growth in invested capital. Earnings growth from growth in RI is more persistent, while earnings growth from growth in invested capital is more likely to reverse. Future returns are positively associated with growth in RI and negatively associated with growth in invested capital. A trading rule based on these findings generates significant hedge returns that persist after controlling for known risk factors. Hence, RI, a measure long recommended by accountants, allows investors to differentiate and evaluate different sources of earnings growth.

Vorheriger Artikel The effect of stock price on discretionary disclosure

Nächster Artikel Hong Kong stock listing and the sensitivity of managerial compensation to firm performance in state-controlled Chinese firms

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While decomposing the growth in RI further into a component driven by the increase in profitability of existing assets and a component driven by the high profitability of new investments is likely to be insightful, it is also potentially intractable without making even more ex ante assumptions regarding the profitability of existing assets and new investments. Untabulated results however indicate that growth in RI is positively associated with increase in asset turnover and profit margins and negatively associated with new investment.

Our results are not affected if we use the effective tax rate, defined as Income Tax Expense (Compustat TXT) divided by Income before Extraordinary Items and Tax (IB + TXT).

WACC is calculated by (1) estimating a CAPM cost of equity using 60 past monthly returns, (2) inferring after-tax cost of debt from interest expense, total interest bearing debt, and the tax rate, and (3) using market value of equity and book value of total debt for their relative weights. We estimate β using at least 24 months and up to 60 months of lagged returns. β below 0.4 are set to 0.4, while β above 3 are set to 3. If β cannot be estimated, we use the contemporaneous median β for firms with the same 2-digit SIC code.

We rerun all tests using fiscal year returns as well as 16 month returns (from beginning of prior year to 4 months after current fiscal year) to control for the fact that firms often make forecasts and preannouncements in the first quarter. The results are very similar and are not tabulated.

Deleting instead of winsorizing outliers yields similar results.

This could either indicate that payoffs to new investments occur with a lag or that capital is being raised without being deployed (i.e. uninvested cash). However, this negative correlation persists even when we net out financial assets in the computation of invested capital, suggesting that the latter explanation is improbable.

The p value for the Vuong (1989) test for the difference in adjusted R² is 0.0000 for the pooled regressions, both with and without fixed effects. For the annual regressions, the p value is less than 0.10 in 29 out of 34 years.

The p value for the Vuong (1989) test for difference in adjusted R² is 0.0000 for pooled regression both with and without fixed effects. For annual regressions, the p value is <0.10 in 27 out of 34 years.

In untabulated analyses, we find similar patterns when we partition the sample on the basis of the extent of analyst following or institutional investment, consistent with such a behavioral explanation.

Although there is debate about whether momentum is, indeed, a risk factor, we include it in our tests to ensure that the results are incremental to a momentum effect. This can also be viewed as a control for the post-earnings-announcement drift, which as Chordia and Shivakumar (2006) show, is strongly related to price momentum.

Consistent with Penman and Zhang (2002), we capitalize research and development (XRD) over a five-year amortization period and advertising expense (XAD) over a two-year amortization period, using the sum-of-years-digits method. If the data for R&D or advertising are missing, we set them to zero. Instead of net operating assets, we use total assets (AT) as our deflator, as the information to calculate net operating assets is either unavailable or net operating assets are negative for over 10% of all firms.

The growth rate in invested capital is measured over a five-year horizon. If 5 years of data are not available, a firm is classified as neither fast or slow (i.e. both FAST and SLOW are set to zero).

We run multi-factor estimation regressions to estimate firm specific factor loadings with respect to the Market Risk (R_m−R_f), Size (SMB) and Book-to-Market (HML). To estimate the cost of equity, we assume the following risk premium for each of these factors based on historical realized premium: R_m−R_f (6%), SMB (2%), HML (4%).

The insignificance of ΔIC_t–1 * WACC_t is likely driven by multicollinearity. For the RI based on NI, the change in invested capital ΔIC_t−1 equals change in book value, which is highly correlated with NI_t−1. Indeed, when we either drop NI_t−1 or replace it with NI_t, the coefficient on ΔIC_t–1 * WACC_t is significant and positive.

If lagged ROIC is negative, we continue to use WACC as the multiplier.

The insignificance of ΔIC_t−1 is also likely driven by multicollinearity. The correlation of ΔIC_t−1 with NI_t−1 (0.60 Pearson, 0.38 Spearman) is greater than the correlation between ΔIC_t–1 * WACC_t and NI_t−1 (0.53 Pearson, 0.31 Spearman). When we either drop NI_t−1 or replace it with NI_t, the coefficient on ΔIC_t−1 is significant and positive.

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Titel: Using residual income to refine the relationship between earnings growth and stock returns
verfasst von: Sudhakar Balachandran
Partha Mohanram
Publikationsdatum: 01.03.2012
Verlag: Springer US
Erschienen in: Review of Accounting Studies / Ausgabe 1/2012
Print ISSN: 1380-6653
Elektronische ISSN: 1573-7136
DOI: https://doi.org/10.1007/s11142-011-9168-1

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