Implied Cost Of Capital Research Articles

LEVERAGE, COST OF CAPITAL AND BANK VALUATION

In this paper, we present a model that demonstrates the effect of debt on cost of capital and value in the case of banking firms. Using a static partial equilibrium setting, both in a steady state and steady growth scenario, we derive a bank-specific valuation metric which separately attributes value to assets and debt cash flows in the form of a liquidity premium and tax-shield. We run our model on a sample of the largest 26 European banks from 2003 to 2016 finding that the value contribution of debt benefits to enterprise value is large and persistent. Further from our model, we derived an implied cost of capital (ICC) measure finding consistent results with capital asset pricing model (CAPM). The theoretical framework we present is helpful to address bank debt benefits valuation and to reconcile equity and asset side approaches.

Estimating the Equity Risk Premium Using Implied Cost of Capital

Research on the implied cost of capital (ICC) has found that the equity risk premium is approximately 3%, on average, much lower than estimates based on the mean of historical stock market returns. The validity of such ICC estimates, however, faces both theoretical and empirical challenges. The theoretical equivalence between ICC and expected return requires the stringent condition that the latter is a constant, which is inconsistent with theory and empirical evidence. The empirical estimation of ICC depends on short-run and long-run earnings forecasts, whose biases can severely limit the validity of the estimates. By employing a forecasting procedure that induces little bias in both short-run and long-run forecasts and taking into account the stochastic nature of expected returns, we show that the average market risk premium ranges between 3% and 6%. We also demonstrate that the results of prior research are affected by input errors that are partially self-canceling.

Estimating the implied risk premium of U.S.-listed shipping firms

ABSTRACTWhile the water transportation industry is perceived as risk-laden, expected return estimates for shipping firms, based on the capital asset pricing model (CAPM), are found to be ‘remarkably low.’ We apply the implied cost of capital (ICC), defined as the constant discount rate that equates share prices and future cash flows, as an alternative means of shipping expected returns and use these estimates instead, as well as in conjunction with the CAPM to provide fresh evidence on the risk and return characteristics of the shipping industry. An aggregate measure of ICC reveals that the median risk premium of shipping firms between 1983 and 2013 is in the range of 0.94% to 0.08%. The expected return of shipping firms tracks a long-term moving average of the S&P 500 index; nevertheless, shipping returns are below the index return at similar, and at times lower, levels with the 10-year treasury yield. The expected equity premium of the shipping industry implied in the cross-section of ICC estimates and CAPM betas ranges between 1.4% and 0.2%. The persistence of a ‘shipping return paradox’ against a variant of expected return methodologies may indicate the pricing of higher moments in the return distribution of shipping firms beyond the mean-variance framework.

International asset allocation using the market implied cost of capital

The Black and Litterman (Financ Anal J 48(5):28–43, 1992) (BL) approach to portfolio optimization requires investor views on expected asset returns as an input. I demonstrate that the market implied cost of capital (ICC) is ideal for quantifying those views on a country level. I benchmark this approach against a BL optimization using time-series models as investor views, the equally weighted portfolio, and allocation methods based on stock market capitalization and GDP. I find that the ICC portfolio offers an increase in average return of 2.1 percentage points (yearly) as compared to the value-weighted portfolio, while having a similar standard deviation. The resulting difference in Sharpe ratios is statistically significant and robust to the inclusion of transaction costs, varying BL parameters, and a less strictly defined investment universe.

Implied Cost of Capital versus Fundamental Valuation Efficiency: A Clarification and Empirical Implications

As the proxy for expected return, the implied cost of capital (ICC) is subject to a mispricing-driven measurement error because the price of a stock used to compute ICC can deviate from its intrinsic value. For undervalued stocks, the mispricing-driven measurement error is positive and increases with the degree of undervaluation while for overvalued stocks, the mispricing-driven measurement error is negative and decreases with the degree of overvaluation. Therefore, ceteris paribus, lower ICC is equivalent to higher (lower) fundamental valuation efficiency (FVE) for undervalued (overvalued) stocks. Furthermore, our evidence, based on 11 constructs, shows that the estimated relation of an FVE-associated construct with ICC is a potentially biased estimate of its relation with expected return because its estimated relation with ICC also captures its relation with the mispricing-driven measurement error, the sign of which switches between undervalued and overvalued stocks. Existing methods do not seem able to address the bias.

The Performance of Mechanical Earnings Forecasts

We analyze three different mechanical models to forecast earnings and compare their forecasts with those of analysts. Moreover, we evaluate implied cost of capital (ICC) estimates that are based on these forecasts. With our analyses we answer three open questions in the literature. 1) Do model forecasts or analysts’ forecasts perform better? 2) Are ICCs derived from analysts’ forecasts more reliable than ICCs based on model forecasts? And 3) does higher forecast performance also translate into more reliable ICCs? First, we find that analysts’ forecasts are even more accurate than the most accurate model forecasts. However, second, we find that model-based ICCs are always more reliable than analyst-based ICCs. Moreover, model-based ICCs are particularly reliable for a sample of firms for which no analysts’ forecasts are available. While the lack of reliability of analyst-based ICCs seems to indicate a missing link between forecast performance and ICC reliability, in fact, third, we find that ceteris paribus higher forecast performance translates into more reliable ICCs, that is, within one earnings definition the most accurate forecasts also yield the most reliable ICCs.

Accounting-Based Estimates of the Cost of Capital: A Third Way

This paper offers an approach for estimating the cost of capital from observed accounting information and compares the resulting estimates to so-called implied cost of capital (ICC) calculations and those from asset pricing models. The approach is based on two ideas. First, buying expected earnings growth is risky; thus, any variable that predicts expected earnings growth that is at risk of not being realized is potentially an indicator of the cost of capital. Second, accounting principles induce earnings growth that ties to risk; thus, an accounting number generated under these principles potentially indicates of the cost of capital. The paper combines such numbers into a cost-of-capital estimate. The estimates perform well in validation tests, in contrast to the alternatives that are the current standards.

Using the Implied Cost of Capital to Assess the Impact of Heightened Capital Requirements

Critics of recent regulation to increase minimum bank capital requirements contend that this policy will increase the cost of doing business for banks. This argument runs counter to the Miller and Modigliani’s (1958) theory (henceforth M-M). We examine the implied cost of capital (ICC) as a measure of cost of equity. The analysis of a sample of banks during the period 1996-2013 suggests that regulation to heighten bank capital would reduce their cost of equity, but by less than predicted by the M-M Proposition II so the overall cost of capital would increase as a result. However, investors seem to be more aware of the risk implied by relatively low levels of capital after the outbreak of the financial crisis. In the post-financial crisis period we find a stronger association between leverage and cost of equity, and a flat or negative relationship between regulatory capital and banks’ cost of capital.

Asset Pricing Anomalies: A Multidimensional Analysis

I examine the predictive power of Implied Cost of Capital (ICC) in time-series of expected returns. For that purpose, I develop a time-series approach of Fama-Macbeth in order to evaluate the relation between ICC and expected returns at the firm level. I find that ICC is able to predict returns over time, not only at the aggregate level but also at the firm level. Based on the power of ICC to forecast returns, measured by regression R², the Claus and Thomas (CT, 2001) approach is the most suitable to predict the returns at the aggregate level, while the Gebhardt et al. (GLS, 2001) approach is the most suitable at the firm level.

Investment Propensity and Implied Cost of Capital

본 연구는 기업의 과잉투자성향과 자기자본비용의 관련성을 검증하고자 하였다. 기업의 과잉투자로 인해 기업의 재원이 주주로의 배당이 아닌 투자로 이어진다면 그 만큼 자본비용의 상승이 발생할 수 있으며 기업의 과잉투자는 일련의 연구들에서 지적한 바와 같이 경영자의 기회주의적 의사결정에 따른 결과로 기업과 투자자간의 정보비대칭을 심화시키며 감사위험을 증가시키는 요인이 될 수 있다. 본 연구에서는 선행연구를 바탕으로 기업의 투자의사결정과 주주의 요구수익률과의 관계를 실증 분석하고자 하였다. 2002년부터 2011년까지의 유가증권 시장을 대상으로 자기자본비용에 미치는 위험요소를 통제한 후에도 기업의 과잉투자성향이 증가할수록 자기자본비용이 커지는 양(＋)의 관련성이 나타나는 것으로 나타났다. 이러한 결과는 기업의 과잉투자에 대한 주식 투자자의 추가적인 요구가 반영된 결과로 이해할 수 있다. 과잉투자기업과 과소투자기업 집단으로 구분한 분석에서 효율적인 투자에서 과잉투자로 증가할수록 주주의 요구수익률은 증가하나 과소투자에서 정상투자로 회복할 때에는 자기자본비용이 감소하지 않았다. 이는 투자자가 과잉투자로 인한 정보위험에 대하여 더 민감하게 반응하기 때문에 추가적인 자본비용이 더 발생한다는 것을 의미한다. 본 연구는 투자효율성이 자본시장에 미치는 영향에 관한 소수의 연구에 추가적인 연구로써 주주의 요구수익률을 상승시키는 요인으로써 과잉투자가 작용할 수 있음을 제시하였다는 데 의의가 존재한다.

Accounting-Based Estimates of the Cost of Capital: A Third Way

This paper offers an approach for estimating the cost of capital from observed accounting information and compares the resulting estimates to so-called implied cost of capital (ICC) calculations and those from asset pricing models. The approach is based on two ideas. First, buying expected earnings growth is risky; thus, any variable that predicts expected earnings growth that is at risk of not being realized is potentially an indicator of the cost of capital. Second, accounting principles induce earnings growth that ties to risk; thus, an accounting number generated under these principles potentially indicates of the cost of capital. The paper combines such numbers into a cost-of-capital estimate. The estimates perform well in validation tests, in contrast to the alternatives that are the current standards.

Implied Cost of Capital in the Cross-Section of Stocks

Recent research shows that the implied cost of capital (ICC), measured from analyst forecasts and current stock prices, predicts market returns. This paper studies the cross-section of stocks and finds that ICC negatively predicts returns. An investment strategy that goes long low-ICC stocks and short high-ICC stocks provides an alpha of 6% per year. Evidence suggests that the negative relation is due to the fact that stocks with a high level of ICC are systematically related with overly optimistic earnings forecasts. High-ICC stocks are also associated with a low probability of survival. Investors fail to incorporate this bias, leading to more negative earnings surprises. The findings highlight the need to exercise caution when using ICC as a measure of cost of capital for individual firms.

Discussion of “Evaluating cross-sectional forecasting models for implied cost of capital”

An estimate of the implied cost of capital (ICC) is useful in valuation, investment, and capital budgeting. The computation of ICC requires earnings forecasts, for which prior studies generally use analyst forecasts to proxy. Hou et al. (2012) generate earnings forecasts using a cross-sectional model and thus estimate ICC for a large sample of firms, including those not covered by analysts. Li and Mohanram (2014) extend Hou et al. by considering two other cross-sectional earnings forecast models (RI and EP models). Li and Mohanram compare their models with the one in Hou et al. in two ways. First, they show that the earnings forecasts generated from their models outperform those from the Hou et al. model on forecast accuracy, forecast bias, and earnings response coefficients. Second, the ICC computed based on the earnings forecasts generated from the Hou et al. model exhibits lower correlations with future returns and more abnormal correlations with risk factors than the ICCs from the R

Evaluating cross-sectional forecasting models for implied cost of capital

The computation of implied cost of capital (ICC) is constrained by the lack of analyst forecasts for half of all firms. Hou et al. (J Account Econ 53:504–526, 2012, HVZ) present a cross-sectional model to generate forecasts in order to compute ICC. However, the forecasts from the HVZ model perform worse than those from a naive random walk model and the ICCs show anomalous correlations with risk factors. We present two parsimonious alternatives to the HVZ model: the EP model based on persistence in earnings and the RI model based on the residual income model from Feltham and Ohlson (Contemp Account Res 11:689–732, 1996). Both models outperform the HVZ model in terms of forecast bias, accuracy, earnings response coefficients, and correlations of the ICCs with future returns and risk factors. We recommend that future research use the RI model or the EP model to generate earnings forecasts.

Model Uncertainty and Expected Return Proxies

Over the last two decades, alternative expected return proxies have been proposed with substantially lower variation than realized returns. This helped to reduce parameter uncertainty and to identify many seemingly robust relations between expected returns and variables of interest, which would have gone unnoticed with the use of realized returns. In this study, I argue that these findings could be spurious due to the ignorance of model uncertainty: because a researcher does not know which of the many proposed proxies is measured with the least error, any inference conditional on only one proxy can lead to overconfident decisions. As a solution, I introduce a Bayesian model averaging (BMA) framework to directly incorporate model uncertainty into the statistical analysis. I employ this approach to three examples from the implied cost of capital (ICC) literature and show that the incorporation of model uncertainty can severely widen the coverage regions, thereby leveling the playing field between realized returns and alternative expected return proxies.

The Usefulness of Z-Score Model on Bankruptcy Forecast

The purpose of this study examines whether Z-Score model suggested by Altman is the useful of Korean firms’ bankruptcy classification criteria through the empirical test of Altman’s Z-Score model on the financial performance. From analytical results, this study develops the hypothesis by comparing the financial performance between good financial health and bankruptcy score by Altman’s data using a sample of 374 Korean firms through Korean bankruptcy classification criteria of Altman’s Z-Score model during 2001-2010 period. The empirical results indicate that the Altman’s Z-Score model is significantly the firm’s financial performance as measured by the firm’s profitability(ROA) and ICC(Implied Cost of Capital). These results hold up even after controlling for the differences in the financial leverage and size. Overall, the findings provide directly support to the evidence that the Altman’s Z-Score model is able to measure as a bankruptcy classification criteria on Korean firms.

Evaluating Cross-Sectional Forecasting Models for Implied Cost of Capital

The computation of implied cost of capital (ICC) is constrained by the lack of analyst forecasts for half of all firms. Hou, van Dijk, and Zhang (2012, HVZ) present a cross-sectional model to generate forecasts in order to compute ICC. However, the forecasts from the HVZ model perform worse than those from a naive random walk model and the ICCs show anomalous correlations with risk factors. We present two parsimonious alternatives to the HVZ model: the EP model based on persistence in earnings and the RI model based on the residual income model from Feltham and Ohlson (1996). Both models outperform the HVZ model in terms of forecast bias, accuracy, earnings response coefficients, and correlations of the ICCs with future returns and risk factors. We recommend that future research use the RI model or the EP model to generate earnings forecasts.

Predicting market returns using aggregate implied cost of capital

Theoretically, the implied cost of capital (ICC) is a good proxy for time-varying expected returns. We find that aggregate ICC strongly predicts future excess market returns at horizons ranging from one month to four years. This predictive power persists even in the presence of popular valuation ratios and business cycle variables, both in-sample and out-of-sample, and is robust to alternative implementations. We also find that ICCs of size and book-to-market portfolios predict corresponding portfolio returns.

Implied cost of capital investment strategies: evidence from international stock markets

Investors can generate excess returns by implementing trading strategies based on publicly available equity analyst forecasts. This paper captures the information provided by analysts by the implied cost of capital (ICC), the internal rate of return that equates a firm’s share price to the present value of analysts’ earnings forecasts. We find that U.S. stocks with a high ICC outperform low ICC stocks on average by 6.0 % per year. This spread is significant when controlling the investment returns for their risk exposure as proxied by standard pricing models. Further analysis across the world’s largest equity markets validates these results.

A New Look at the Fama-French-Model: Evidence Based on Expected Returns

We test the Fama-French three-factor model for a large international data set ranging from 1990 to 2011 using an alternative proxy for expected returns, the implied cost of capital (ICC). The implied risk premiums of the three factors over all countries are all highly significant. Also, the risk premiums for the three factors lie within a much smaller range compared to their counterparts based on realized returns. For all countries, we find the cross-sectional variation in expected stock returns not only to depend on the stock’s market risk, but also to be driven by its exposure towards the size and value factor. Moreover, even though portfolio intercepts for the three-factor model display significant alphas, they are very small from an economic perspective. We conclude that the Fama-French three-factor model is an appropriate asset pricing model using this alternative proxy for expected returns.