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28-10-2020 | Research Article

The role of market efficiency on implied cost of capital estimates: an international perspective

Author: David Schröder

Published in: Annals of Finance | Issue 4/2020

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Abstract

This study examines the role of market efficiency on international differences in the usefulness of the implied cost of capital (ICC) to measure expected stock returns. The analysis exploits cross-country differences in market efficiency around the world using a variety of empirical measures of market efficiency. A key methodological contribution of this paper is to assess the quality of the ICC as estimate of expected returns by evaluating its forecast error for subsequent stock returns. The results show that the accuracy of the ICC as measure of expected stock returns is positively associated with the countries’ level of market efficiency.

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Among others, Cornell (1999), Gebhardt et al. (2001) and Claus and Thomas (2001) use the ICC to estimate an expected equity risk premium. Botosan (1997) uses the ICC to analyze corporate finance decisions of firms. Lee et al. (2009) employs the ICC to test asset pricing models, while Pástor et al. (2008) and Chava and Purnanandam (2010) analyze the risk-return trade-off of shares. Li et al. (2013) and Esterer and Schröder (2014) use the ICC to predict stock returns.

For a detailed discussion of the various approaches, see, e.g., Easton and Monahan (2016) and Lee et al. (2020).

See, e.g., Francis et al. (2000), Easton and Sommers (2007), Guay et al. (2011), Hou et al. (2012), Larocque (2013) and Mohanram and Gode (2013). Kothari et al. (2016) provides an excellent review.

Alternative implementations of the RIM are by Claus and Thomas (2001), Gode and Mohanram (2003) or Easton (2004). Botosan and Plumlee (2005), Easton (2006) and Botosan et al. (2011) provide a good overview of the different formulae and model assumptions. Additional tests in Sect. 5.2 show that the main results of this paper are robust to alternative implementations of the RIM.

Instead of using equity analyst earnings forecasts, Hou et al. (2012) and Li and Mohanram (2014) suggest regression-based earnings forecasts. However, the relatively small data samples in many countries covered in this study do not allow to reliably estimating the forecasting model parameters, resulting in noisy earnings forecasts.

Since the market efficiency index by Kristoufek and Vosvrda (2013) is only available for a limited set of countries, a few important equity markets are not included in this study, such as Australia, Ireland, New Zealand, Norway, Sweden and Portugal. For more details on the efficiency index, see Sect. 4.1.

Hail and Leuz (2006) cover the period from 1992 to 2001 when average inflation and interest rates were higher.

This study uses the terms cost of capital, required return, and expected rate of return interchangeably. Some authors, such as Lewellen (2010), consider the ICC as estimate of expected stock returns if markets are efficient, and as required rate of return if markets are not efficient. In the terminology of this paper, the latter would be a biased estimate of expected stock returns.

Easton and Monahan (2005) propose an empirical approach to isolate expected stock returns from cash-flow and discount-rate news. Yet, this approach is only feasible when using regression analysis to assess the ICC’s ability to predict the cross-section of stock returns.

The ICC is—similar to a bond’s yield to maturity—the constant rate of return that an investor would receive by holding the equity share until infinity. Put differently, the ICC is a long-term, constant expected rate of return. If true short-term expected returns are time-varying, the ICC is not an unbiased estimate of expected returns (Hughes et al. 2009). Since expected returns of individual stocks are mainly time-varying due to market-wide, aggregate information surprises, such biases are unlikely to have a significant effect on the results of this paper.

Expected returns (i.e., the ICC) and realised returns are expressed over different time horizons. While the ICC is an annual expected return estimate, stock returns are measured over one month. To make the two measures comparable, the firms’ ICC estimate is divided by 12.

Different from the forecast error metrics, portfolio sorts and cross-sectional regressions assess whether the ICC is on average positively or negatively related to stock returns or not.

Monthly mean errors can cancel out over time. In this case, the time-series average mean error is close to zero, while the time-series average squared mean error can still be substantial.

See also Rusticus (2014) for more discussion.

Another source of errors of the ICC can be the valuation model used to extrapolate expected earnings after the initial period of earnings forecasts (Rusticus 2014). There is also a possibility that pricing errors and analyst forecast errors are correlated. However, if market participants believe in erroneous analyst forecasts, pricing and forecast errors cancel out, such that the ICC is an unbiased estimate of expected stock returns.

Common measures of efficiency mainly exploit short-term and long-term autocorrelation patterns of stock returns. Examples include the size of short-term reversals (Jegadeesh 1990), momentum strategies (Jegadeesh and Titman 1993), and variance ratios (Lo and MacKinley 1988).

This study only presents the regression results when measuring the ICC’s forecast accuracy by the mean squared error (MSE), and its two components, error variance (EV) and squared mean error (\({\hbox {ME}}^2\)). The results are quantitatively and qualitatively very similar to the mean squared error (MSE) when using the mean absolute error (MAE) and the root mean squared error (RMSE) to measure the ICC’s forecast quality. The results are available on request.

This panel data analysis excludes two countries, the United States and China. The U.S. is the largest equity market by far and therefore may be fundamentally different from all other countries. China has seen a tremendous transition over the last decades, which makes it less comparable to other countries analysed. However, the results do not change substantially when including the United States and China.

The results are qualitatively similar when using panel regression with standard errors clustered by country (cross-sectional dimension) and year (time-series dimension) following Rogers (1993), or when using country fixed-effects regressions.

Hail and Leuz (2006), Gianetti and Koskinen (2010) and Cao et al. (2017) use similar disclosure requirement indices.

The only exception is the association between squared mean error and the index of judicial efficiency. Yet, the coefficient is not significant.

Since Claus and Thomas (2001) require the IBES consensus long-term earnings growth rate, the sample of ICC estimates using the Claus and Thomas (2001) model is smaller in some countries. While forecasting the long-term earnings growth rate has a long tradition in the U.S., estimates for the long-term growth rate are less common in other countries.

Since the firms’ ICC estimates obtained from different ICC models tend to be highly correlated (Botosan and Plumlee 2005), including more ICC models is unlikely to change the results.

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Title: The role of market efficiency on implied cost of capital estimates: an international perspective
Author: David Schröder
Publication date: 28-10-2020
Publisher: Springer Berlin Heidelberg
Published in: Annals of Finance / Issue 4/2020
Print ISSN: 1614-2446
Electronic ISSN: 1614-2454
DOI: https://doi.org/10.1007/s10436-020-00374-0

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