The Cost of Capital of Cross‐listed Firms

This paper analyses the cost of capital of firms with foreign equity listings. Our purpose is to shed light on the question whether international and domestic asset pricing models yield a different estimate of the cost of capital for cross‐listed stocks. We distinguish between (i) the multifactor ICAPM of Solnik (1979) and Sercu (1980) including both the global market portfolio and exchange rate risk premia and (ii) the single factor domestic CAPM. We test for the significance of the cost of capital differential in a sample of 336 cross‐listed stocks from nine countries in the period 1980–99. Our hypothesis is that the cost of capital differential is substantial for firms with international listings, as these are often large multinationals with a strong international orientation. We find that the asset pricing models yield a significantly different estimate of the cost of capital for only 12% of the cross‐listed companies. The size of the cost of capital differential is around 50 basis points for the US, 80 basis points for the UK and 100 basis points for France.     

Estimating the Cost of Equity for Property-Liability Insurance Companies

Due to the highly skewed and heavy‐tailed distributions associated with the insurance claims process, we evaluate the Rubinstein‐Leland (RL) model for its ability to improve the cost of equity estimates of insurance companies because of its distribution‐free feature. Our analyses show that there is as large as a 94‐basis‐point difference in the estimated cost of insurance equity between the RL model and the capital asset pricing model (CAPM) for the sample of property‐liability insurers with more severe departures from normality. In addition, consistent with our hypotheses, significant differences in the market risk estimates are found for insurers with return distributions that are asymmetrically distributed, and for small insurers. Third, we find significant performance improvements from using the RL model by showing smaller values of excess return of the expected return of the portfolio to the model return for a portfolio of insurers with returns that are more skewed and for a portfolio of small insurers. Finally, our panel data analysis shows the differences in the market risk estimates are significantly influenced by firm size, degree of leverage, and degree of asymmetry. The implication is that insurers should use the RL model rather than the CAPM to estimate its cost of capital if the insurer is small (assets size is less than $2,291 million), and/or its returns are not symmetrical (the value of skewness is greater than 0.509 or less than ?0.509).     

What Cost of Capital Should You Use? The Market Has an Answer

The most widely used means of estimating a company's cost of equity capital is the Capital Asset Pricing Model (CAPM). But as a growing number of academics and practitioners have suggested, use of the CAPM produces estimates that often fail to reflect the risks of the companies as perceived by current and potential investors. The authors' work, together with other research, also suggests that the cost of equity produced by the CAPM is often too high. To the extent this is so, companies are discounting investment projects at rates of return that may be leading them to pass up value‐adding opportunities. The authors advocate the use of a simple and practical alternative to the CAPM that does not use either an assumed market risk premium or a beta. It uses instead an equity premium that is implied by the current market price of a company's stock and, as such, is implicitly derived from investors' assessments of the firm's risk that are reflected in that price. More specifically, the alternative approach solves for the internal rate of return that equates the present value of expected future cash flows to the current market price. In support of this approach, studies have shown that such market‐implied measures are better predictors than CAPM‐based estimates of future stock returns, both at the individual‐firm and aggregate market levels.     

Beyond CAPM: estimating the cost of equity considering idiosyncratic risks

The present study proposes a new evaluation approach aimed at estimating the cost of equity through standardized models which consider an innovative set of firm-specific information on the main unsystematic risks which are typical of any business. Our objective is extending the Capital Asset Pricing Model (CAPM) by defining a standard formula for quantifying the premium for certain idiosyncratic risks as a function of a new set of firm-specific quantitative information. We define two econometric models, for listed and non-listed firms respectively, which consider five idiosyncratic risk factors: firm size, value factor, operating risks, financial structure and stock market price volatility. The models were tested on a sample of European non-financial companies. The empirical results show that while the CAPM systematically underestimates the cost of equity, the proposed models correctly estimate its expected value; furthermore, they show a slight improvement also in terms of estimates’ volatility. Due to their efficacy and ease of use, the proposed models represent a valid practical tool for investors, analysts and professional evaluators. This work contributes to the existing literature by proposing a typologically innovative extension of the CAPM set of explanatory variables, defining and testing new models for the estimation of the unsystematic risks’ spread of the cost of equity based on an original set of firm-specific accounting and market information.     

Estimating the Cost of Equity Capital for Property-Liability Insurers

This article presents new evidence on the cost of equity capital by line of insurance for the property‐liability insurance industry. To do so we obtain firm beta estimates and then use the full‐information industry beta (FIB) methodology to decompose the cost of capital by line. We obtain full‐information beta estimates using the standard one‐factor capital asset pricing model and extend the FIB methodology to incorporate the Fama–French three‐factor cost of capital model. The analysis suggests the cost of capital for insurers using the Fama–French model is significantly higher than the estimates based upon the CAPM. In addition, we find evidence of significant differences in the cost of equity capital across lines.     

Accounting‐based Risk Management and the Capital Asset Pricing Model: An Empirical Comparison

Accounting‐based risk management (ABRM) is a theoretically consistent and practical tool for calculating the cost of capital from underlying financial ratios. In this paper, a sample of ABRM‐generated discount factors is used to generate risk‐adjusted returns, which are compared to CAPM equivalent discount factors. In view of the debates about CAPM's validity, alternative models, the nature and scale of the equity risk premium, and the importance of discount rates in capital budgeting and asset valuation, ABRM's characteristics and resulting discount rates offer a potentially useful alternative. Results suggest that although average discount rates are comparable, their cross‐sectional distributions are dissimilar, so that investors in an average risky firm are overcompensated for systematic risk when using CAPM discount rates, because CAPM discount factors overestimate risk arising from fixed costs in most firms.     

GOLBALIZATION, CORPORATE FINANCE, AND THE COST OF CAPITAL

International financial markets are progressively becoming one huge, integrated, global capital market—a development that is contributing to higher stock prices in developed as well as developing economies. For companies that are large and visible enough to attract global investors, having a global shareholder base means having a lower cost of capital and hence a greater equity value for two main reasons: First, because the risks of equity are shared among more investors with different portfolio exposures and hence a different “appetite” for bearing certain risks, equity market risk premiums should fall for all companies in countries with access to global markets. Although the largest reductions in cost of capital resulting from globalization will be experienced by companies in liberalizing economies that are gaining access to the global markets for the first time, risk premiums can also be expected to fall for firms in long-integrated markets as well. Second, when firms in countries with less-developed capital markets raise capital in the public markets of countries (like the U.S.) with highly developed markets, they get more than lower-cost capital; they also import at least aspects of the corporate governance systems that prevail in those markets. For companies accustomed to less-developed markets, raising capital overseas is likely to mean that more sophisticated investors, armed with more advanced technologies, will participate in monitoring their performance and management. And, in a virtuous cycle, more effective monitoring increases investor confidence in the future performance of those companies and so improves the terms on which they raise capital. Besides reducing market risk premiums and improving corporate governance, globalization also affects the systematic risk, or “beta,” of individual companies. In global markets, the beta of a firm's equity depends on how the stock contributes to the volatility not of the home market portfolio, but of the world market portfolio. For companies with access to global capital markets whose profitability is tied more closely to the local than to the global economy, use of the traditional Capital Asset Pricing Model (CAPM) will overstate the cost of capital because risks that are not diversifiable within a national economy can be diversified by holding a global portfolio. Thus, to reflect the new reality of a globally determined cost of capital, all companies with access to global markets should consider using a global CAPM that views a company as part of the global portfolio of stocks. In making this argument, the article reviews the growing body of academic studies that provide evidence of the predictive power of the global CAPM as well as the reduction in world risk premiums.     

A Comparison of the Efficacy of Liquidity,Momentum, Size and Book‐to‐Market Value Factors in Equity Pricing on a Heterogeneous Sample: Evidence from Asia

This paper compares the size and book‐to‐market value factors of Fama and French (1993) alongside Momentum of Jagadeesh and Titman ( 1993 ) with two Liu ( 2006 ) liquidity factors formed from 1 year rebalancing and 1 month rebalancing respectively. A heterogeneous and comprehensive sample of the top blue chip stocks of all national Asian equity markets with further differentiation undertaken between sub samples formed for Japan only and Asia excluding Japan for period January 2000 to August 2014. Our empirical results suggest that multifactor time invariant pricing models based on augmented capital asset pricing model (CAPM) framework are ineffective in explaining the cross section of stock returns in the presence of significant inter and intra‐market segmentation. However an alternative model specification based on a time varying parameter specification and using same sets of factors yields significant enhancements in explaining cross section of stock returns across universe. We find that momentum factor largely lacks significance while a time varying two factor model, based on CAPM plus liquidity factor, is optimal. The liquidity factor being that of Liu (2006) and annually rebalanced. Our findings are important for investment managers seeking appropriate factors and modelling techniques to hedge against risks as well as firm's financial managers seeking to reduce costs of equity capital.     

Divergence of US and Local Returns in the After‐market for Equity Issuing ADRs

We study one‐year post‐listing prices and returns to equity issuing ADRs that listed in the US between January 1991 and October 2000. ADRs from countries that impose restrictions on capital flows are priced at a premium to their home market ordinaries. While the mean premium for the full sample is statistically indistinguishable from zero, after an adjustment for asynchronous trading, the magnitude of the premium to ADRs from restricted markets is 11.33% at the 300‐day post listing interval, which is statistically significant. In the short run (30 days) following listing, the magnitude of the premium is larger for ADRs with larger excess demand from US investors. At the longer 300‐day horizon, Nasdaq listed ADRs earn a larger premium than their NYSE/AMEX listed counterparts. Time‐series regressions and two‐stage cross‐sectional regressions establish that the premium to foreign equity issuers is greater if the US listing attracts liquidity and if US returns have a lower correlation with the local country index.     

Industry Costs of Equity: Incorporating Prior Information

I examine whether incorporating economically motivated prior information yields more accurate forecasts of industry costs of equity. I find that incorporating the long‐run mean of the Capital Asset Pricing Model (CAPM) parameters and the industry characteristics in the cross section produces more accurate parameter estimates, which subsequently translate into more accurate out‐of‐sample forecasts of industry costs of equity. The outperformance of this method over rolling‐window estimates becomes larger as the forecast horizon extends into the future. These findings provide evidence that the CAPM parameters have a long‐run mean‐reversion property and correlate with the industry characteristics in a systematic way.     

An empirical investigation of stock market behavior in the Middle East and North Africa

This paper analyzes excess market returns in the relatively understudied financial markets of nine Middle Eastern and North African (MENA) countries within the context of three variants of the Capital Asset Pricing Model: the static international CAPM; the constant-parameter intertemporal CAPM; and a Markov-switching intertemporal CAPM which allows for the degree of integration with international equity markets to be time-varying. On the whole we find that: (1) Israel and Turkey are most strongly integrated with world financial markets; (2) in most other MENA markets examined there is primarily local pricing of risk and evidence of a positive risk-return trade-off; and (3) there is substantial time variation in the weights on local and global pricing of risk for all of these markets. Our results suggest that investment in many of these markets over the sample studied would have provided returns uncorrelated with global markets, and thus would have served as financial instruments with which portfolio diversification could have been improved.     

Cross‐sectional Tests of Conditional Asset Pricing Models: Evidence from the German Stock Market

We study the performance of conditional asset pricing models and multifactor models in explaining the German cross‐section of stock returns. We focus on several variables, which (according to previous research) are associated with market expectations on future market excess returns or business cycle conditions. Our results suggest that the empirical performance of the Capital Asset Pricing Model (CAPM) can be improved when allowing for time‐varying parameters of the stochastic discount factor. A conditional CAPM using the term spread explains the returns on our size and book‐to‐market sorted portfolios about as well as the Fama‐French three‐factor model and performs best in terms of the Hansen‐Jagannathan distance. Structural break tests do not necessarily indicate parameter instability of conditional model specifications. Another major finding of the paper is that the Fama‐French model – despite its generally good cross‐sectional performance – is subject to model instability. Unconditional models, however, do a better job than conditional ones at capturing time‐series predictability of the test portfolio returns.     

Testing conditional asset pricing models: An emerging market perspective

The CAPM as the benchmark asset pricing model generally performs poorly in both developed and emerging markets. We investigate whether allowing the model parameters to vary improves the performance of the CAPM and the Fama–French model. Conditional asset pricing models scaled by conditioning variables such as Trading Volume and Dividend Yield generally result in small pricing errors. However, a graphical analysis reveals that the predictions of conditional models are generally upward biased. We demonstrate that the bias in prediction may be the consequence of ignoring frequent large variation in asset returns caused by volatile institutional, political and macroeconomic conditions. This is characterised by excess kurtosis. An unconditional Fama–French model augmented with a cubic market factor performs the best among some competing models when local risk factors are employed. Moreover, the conditional models with global risk factors scaled by global conditioning variables perform better than the unconditional models with global risk factors.     

Sources of risk and expected returns in global equity markets

This paper empirically examines multifactor asset pricing models for the returns and expected returns on eighteen national equity markets. The factors are chosen to measure global economic risks. Although previous studies do not reject the unconditional mean variance efficiency of a world market portfolio, our evidence indicates that the tests are low in power, and the world market betas do not provide a good explanation of cross-sectional differences in average returns. Multiple beta models provide an improved explanation of the equity returns.     

Alternative Models for Estimating the Cost of Equity Capital for Property/Casualty Insurers

This paper estimates the cost of equity capital for Property/Casualty insurers by applying three alternative asset pricing models: the Capital Asset Pricing Model (CAPM), the Arbitrage Pricing Theory (APT), and a unified CAPM/APT model (Wei (1988). The in-sample forecast ability of the models is evaluated by applying the mean squared error method, the Theil U2 (1966) statistic, and the Granger and Newbold (1978) conditional efficiency evaluation. Based on forecast evaluation procedures, the APT and Wei's unified CAPM/APT models perform better than the CAPM in estimating the cost of equity capital for the PC insurers and a combined forecast may outperform the individual forecasts.     

Estimation of expected return: CAPM vs. Fama and French

Most practitioners favour a one-factor model (CAPM) when estimating expected return for an individual stock. For estimation of portfolio returns, academics recommend the Fama and French three-factor model. The main objective of this paper is to compare the performance of these two models for individual stocks. First, estimates for individual stock returns based on CAPM are obtained using different time frames, data frequencies, and indexes. It is found that 5 years of monthly data and an equal-weighted index, as opposed to the commonly recommended value-weighted index, provide the best estimate. However, performance of the model is very poor; it explains on average 3% of differences in returns. Then, estimates for individual stock returns are obtained based on the Fama and French model using 5 years of monthly data. This model, however, does not do much better; independent of the index used, it explains on average 5% of differences in returns. These results therefore bring into question the use of either model for estimation of individual expected stock returns.     

The Rise of Accelerated Seasoned Equity Underwritings

Seasoned equity offerings (SEOs) executed through accelerated underwritings have recently seen significant increases in global market share, and now account for a majority of the proceeds from both U.S. and European SEOs. Based on their study of over 30,000 global SEOs during the period 1991‐2004, the authors conclude that accelerated offerings occur more rapidly (as their name suggests), raise more capital, and require fewer underwriters than conventional fully marketed SEOs. Accelerated transactions also typically involve larger, better‐known companies that tend to be selling substantial amounts of secondary as well as primary secondary shares (whereas traditional SEOs consist almost entirely of primary shares). Besides speed of execution, the growing popularity of accelerated deals is also attributed to lower spreads, the reduced price risk for issuers resulting from the brief underwriting period, and “market‐impact” costs that are no larger than those that accompany traditional SEOs. Indeed, according to the authors' estimates, accelerated deals reduce the total issuance costs of U.S. issuers—in the form of lower spreads, market‐impact costs, and underpricing—by 250 basis points, on average, while the cost reduction for European sellers is said to be close to 400 basis points. The authors also present an analysis of SEO investment banking syndicates that illustrates that accelerated deals yield much smaller, more capital‐intensive, and presumably riskier underwriting syndicates that generate comparable revenues over much shorter transactions periods. In so doing, they enable larger, more reputable banks to “buy” market share and league table rankings. The authors' findings underscore three major trends that are shaping global investment banking. First, the fact that accelerated deals are marketed almost exclusively to institutional investors, and that these underwriting methods are gaining market share, suggests the declining importance of retail investors in equity markets everywhere. Second, the rise of accelerated deals both promotes and reflects increasing concentration in the investment banking industry, since only the largest banks have the capital base and risk tolerance required to buy large share blocks outright and assume all or most of the price risk of later resale. Finally, the increasing use of accelerated underwritings for SEOs provides another case of the “commoditization” of financial transactions characterized by relatively low asymmetric information. Since ATs can be employed for shares of only large and well‐known companies, these offerings are executed very quickly and cheaply—in much the same way plain vanilla corporate bonds are sold—and with minimal need for the placement and marketing services that investment banks use for IPOs and other non‐transparent security offerings.     

APPLICABILITY OF THE FAMA‐FRENCH THREE‐FACTOR MODEL IN FORECASTING PORTFOLIO RETURNS

For the model‐based estimation of the equity cost of capital, evidence shows that the common practice of using the average historical factor premiums as the estimates of the next‐period factor premiums generates inaccurate estimates. I propose an alternative way to estimate factor premiums by using the structural variables that are important predictors of future asset returns. Based on the out‐of‐sample results from a trading strategy with four in‐sample model‐selection criteria, I find that my estimation procedure performs better than the common practice even when transaction costs are considered.     

Does It Pay to Bet Against Beta? On the Conditional Performance of the Beta Anomaly

Prior studies find that a strategy that buys high‐beta stocks and sells low‐beta stocks has a significantly negative unconditional capital asset pricing model (CAPM) alpha, such that it appears to pay to “bet against beta.” We show, however, that the conditional beta for the high‐minus‐low beta portfolio covaries negatively with the equity premium and positively with market volatility. As a result, the unconditional alpha is a downward‐biased estimate of the true alpha. We model the conditional market risk for beta‐sorted portfolios using instrumental variables methods and find that the conditional CAPM resolves the beta anomaly.     

TRANSITORY MARKET STATES AND THE JOINT OCCURRENCE OF MOMENTUM AND MEAN REVERSION

In this article we derive and investigate the implications of the Fama–French and Poterba–Summers model—in which the market price of equity contains permanent and temporary components—to explain cross‐sectional differences in equity risk premia and returns. Shocks to the transitory component are regarded a Merton risk factor. We obtain estimates from a simple Kalman decomposition of the market price. The transitory component estimate is used in a conditional capital asset pricing model to test implications of the model related to predictability, cross‐sectional performance, and the existence of momentum and mean reversion.