IS THE DISTRIBUTION OF BETAS STATIONARY?

The stationarity of the beta distribution for 1926–1985 is rejected for the entire period as a single sample. However, results for pairs of five-year estimation periods are more consistent with stationarity. Over all possible pairs of five-year periods, stationarity in the pair-wise tests is rejected more often than expected merely by chance. However, excluding two aberrant periods, the number of rejections of stationarity is consistent with chance. Therefore, the distribution of betas is nearly stationary in both the short run and long run. For practical purposes the distribution of betas may be regarded as stationary.     

An Unconditional Asset-Pricing Test and the Role of Firm Size as an Instrumental Variable for Risk

In an intertemporal economy where both risk (stock beta) and expected return are time varying, the authors derive a linear relation between the unconditional beta and the unconditional return under certain stationarity assumptions about the stochastic process of size-portfolio betas. The model suggests the use of long time periods to estimate the unconditional portfolio betas. The authors find that, after controlling for the betas thus estimated, a firm-size proxy, such as the logarithm of the firm size, does not have explanatory power for the averaged returns across the size-ranked portfolios.     

The going public decision and the structure of equity markets

The industries in which listed firms are concentrated in less developed equity markets are not random, nor entirely explained by the underlying composition of production. Listed firms and market capitalization are disproportionately concentrated in industries with low beta (measured with their beta with the market portfolio in the U.S.). We document a strong positive relationship between the industry-weighted country beta and the degree of market development across countries. Recent IPO activity confirms the result since new listings have higher betas than the average firm already in the market.     

RETURN INTERVAL,FIRM SIZE AND SYSTEMATIC RISK ON THE DUTCH STOCK MARKET

In this paper we investigate the behavior of betas of 50 Dutch firms as a function of the return measurement interval. We find beta estimates measured from different intervals differ significantly from each other. As the sample mainly contains stocks that are relatively thin compared to the index, beta estimates from short intervals are on average lower than those obtained from longer intervals. The results further indicate that there exists some variability in the beta coefficients for each interval length. Betas depend on the manner daily prices are juxtaposed to calculate the returns. A way to account for this variability is to average the different betas for each interval length. Asymptotic betas are also computed to show the appropriateness of this method. Finally we show that the size effect is reduced when the interval length is increased, although it remains statistically significant.     

Oil and stock market activity when prices go up and down: the case of the oil and gas industry

We examine the asymmetric effects of daily oil price changes on equity returns, market betas, oil betas, return variances, and trading volumes for the US oil and gas industry. The responses of stock returns associated with negative changes in oil prices are higher than that associated with positive changes in oil prices. Stock risk measured by market beta is influenced more due to oil price decreases than due to oil price increases. On the other hand, oil risk exposures (oil betas) and return variances are more influenced by oil price increases than oil price decreases. The results of our study indicate that oil and gas firm returns, market betas, oil betas, return variances respond asymmetrically to oil price changes. We also find that relative changes in oil prices along with firm-specific factors such as firm size, ROA, leverage, market-to-book ratio (MBR) are important in determining the effects of oil price changes on oil and gas firms’ returns, risks, and trading volumes.     

The Global CAPM and a Firm's Cost of Capital in Different Currencies

In an integrated global market, a firm's cost of capital expressed in one currency should be consistent with its cost of capital expressed in another currency. This article presents and illustrates a process for estimating consistent costs of capital in different currencies for a U.K. based multinational. In so doing, it uses a simple, easy-to-use version of the global CAPM that attempts to incorporate the effect of uncertain exchange rates by calculating exchange rate "betas." As argued in the previous article, at least part of a company's currency exposure is systematically related to the global market and thus should be treated as a component of the firm's systematic equity risk.
For example, the U.K. firm featured in this article is shown to have an exchange rate beta of 0.20 from the perspective of a U.S. investor. This implies that a 10% return on the global market in U.S. dollars tends to be associated with a 2% change in the U.S. dollar value of the British pound. One interesting consequence of incorporating exchange risk in this fashion is that two firms with identical U.S. global betas and costs of equity will have different expected returns expressed in another currency if they have different exposures to that currency.     

Markov Chains and Regression toward the Mean

Using the theory of stationary Markov chains, we uncover a previously unknown property of the behavior of betas. Specifically, if the cross-sectional distribution of betas is stationary over time, then the set of firms that remain in an arbitrarily chosen beta interval between one period and the next will not regress toward the mean. This surprising result occurs in spite of the well-known fact that the set of all the firms in the interval will exhibit the regression tendency. Our empirical tests indicate that betas behave in remarkable accordance with this prediction.     

The Beta Dilemma in Emerging Markets

In principle, emerging markets analysts employ the same analytical framework when estimating the value of businesses as their counterparts in developed economies: they forecast future cash flows and discount those to the present with appropriate costs of capital that are estimated using the Capital Asset Pricing Model (CAPM) framework. But in practice, emerging market analysts have a more complicated job because the task of estimating costs of equity in emerging markets is more difficult. Whereas developed economies have an abundance of historical data on overall stock market movements, industry share price behavior, and many individual share price histories, emerging market economies often do not. There may be no comparable local firms that are publicly traded—or if there are, their CAPM betas may be unreliable. And if analysts instead use the beta of a U.S. competitor as a surrogate for the emerging market beta, they face the question of whether domestic betas are equivalent across borders. As a consequence, appraisers of emerging market companies confront a “beta dilemma.” Part of this is a data problem stemming from shorter share price histories in emerging markets and the absence of publicly traded companies in some industries. In such cases, analysts may be inclined to use industry betas calculated with U.S. share prices as a substitute. But this creates an equivalence problem—the possibility, as confirmed by the author's research, that domestic U.S. and emerging market betas are not statistically equivalent for most industries. The author proposes a solution to this problem that involves grouping emerging markets into a single, distinctive asset class that allows for reliable calculations of industry betas. He also suggests ways of testing emerging market industry betas to determine whether they are statistically comparable.     

The Conditional Beta and the Cross-Section of Expected Returns

We examine the cross-sectional relation between conditional betas and expected stock returns for a sample period of July 1963 to December 2004. Our portfolio-level analyses and the firm-level cross-sectional regressions indicate a positive, significant relation between conditional betas and the cross-section of expected returns. The average return difference between high- and low-beta portfolios ranges between 0.89% and 1.01% per month, depending on the time-varying specification of conditional beta. After controlling for size, book-to-market, liquidity, and momentum, the positive relation between market beta and expected returns remains economically and statistically significant.     

Measuring risk in the mining sector with ARCH models with important observations on sample size

This paper uses the GARCH technique to estimate time-varying individual firm risk measures for the mining sector. In general, the mining industry is riskier than the market with estimated betas greater than one. The results also show that the level of risk in the industry is quite volatile and can be divided into three distinct time periods according to the magnitude and variability of the firm's betas. Additionally, the number of observations in a sample has a strong relationship to the detection and estimation of an ARCH effect in the data, which cannot be explained by firm financial size.     

Local Risk,Local Factors,and Asset Prices

Firm location affects firm risk through local factor prices. We find more procyclical factor prices such as wages and real estate prices in areas with more cyclical economies, namely, high “local beta” areas. While procyclical wages provide a natural hedge against aggregate shocks and reduce firm risk, procyclical prices of real estate, which are part of firm assets, increase firm risk. We confirm that firms located in higher local beta areas have lower industry‐adjusted returns and conditional betas, and show that the effect is stronger among firms with low real estate holdings. A production‐based equilibrium model explains these empirical findings.     

A Direct Test of Roll's Conjecture on the Firm Size Effect

Empirical research indicates that small firms earn higher average rates of return than large firms, even after accounting for beta risk. Roll conjectured that the small firm effect might be attributed to improper estimation of security betas. The evidence shows that while the direction of the bias in beta estimation is consistent with Roll's conjecture, the magnitude of the bias appears to be too small to explain the firm size effect.     

Predicting systematic risk: Implications from growth options

In accordance with the well-known financial leverage effect, decreases in stock prices cause an increase in the levered equity beta for a given unlevered beta. However, as growth options are more volatile and have higher risk than assets in place, a price decrease may decrease the unlevered equity beta via an operating leverage effect. This is because price decreases are associated with a proportionately higher loss in growth options than in assets in place. Most of the existing literature focuses on the financial leverage effect: This paper examines both effects. We show, with a simple option pricing model, the opposing effects at work when the firm is a portfolio of assets in place and growth options. Our empirical results show that, contrary to common belief, the operating leverage effect largely dominates the financial leverage effect, even for initially highly levered firms with presumably few growth options. We then link variations in betas to measurable firm characteristics that proxy for the fraction of the firm invested in growth options. We show that these proxies jointly predict a large fraction of future cross-sectional differences in betas. These results have important implications on the predictability of equity betas, hence on empirical asset pricing and on portfolio optimization that controls for systematic risk.     

The size effect in the Mexican stock market

This paper tests for a firm size effect in the Mexican stock market using data from January 1987 to December 1992. Our initial tests indicate that average stock returns are positively related to market betas. We also find, however, that average returns are negatively related to firm size. To measure the effects on average return of betas that are unrelated to firm size, we examine portfolios formed on the basis of size and beta We find that beta is priced in addition to firm size for the Mexican stock market, even after carefully separating the effects of beta and size.     

Estimating Systematic Risk Using Time Varying Distributions

This article proposes a dynamic vector GARCH model for the estimation of time-varying betas. The model allows the conditional variances and the conditional covariance between individual portfolio returns and market portfolio returns to respond asymmetrically to past innovations depending on their sign. Covariances tend to be higher during market declines. There is substantial time variation in betas but the evidence on beta asymmetry is mixed. Specifically, in 50% of the cases betas are higher during market declines and for the remaining 50% the opposite is true. A time series analysis of estimated time varying betas reveals that they follow stationary mean-reverting processes. The average degree of persistence is approximately four days. It is also found that the static market model overstates non-market or, unsystematic risk by more than 10%. On the basis of an array of diagnostics it is confirmed that the vector GARCH model provides a richer framework for the analysis of the dynamics of systematic risk.     

Real Estate Ownership, Leasing Intensity, and Value: Do Stock Returns Reflect a Firm’s Real Estate Holdings?

Little is known about the effects of real estate ownership and leasing on the stock return characteristics of public firms. In this study, we first examine the sensitivity of retail firm returns to a real estate factor over the period 1998?C2008. The retail industry is chosen because of the significant use of real estate in a typical retail firm??s production function. Consistent with our expectations, retail stocks exhibit positive real estate risk exposure, even after controlling for sensitivity to general market risk as well as other standard risk factors. The second part of our analysis examines whether the intensity of real estate ownership and the use of off-balance operating leases to finance real property holdings are reflected in the market and real estate betas of retail stocks. We find that greater use of off-balance sheet operating leases is associated with higher market betas. In fact, the use of operating leases appears to have a larger impact on sensitivity to market risk than does the use of on-balance sheet debt. Our findings also confirm our hypothesis that real estate intensive firms display significantly greater exposure to a real estate factor. Moreover, our results strongly suggest that investors are fully aware of the risk associated with off-balance sheet operating leases.     

EXAMINING MERGER SYNERGY WITH THE CAPITAL ASSET PRICING MODEL

This paper analyzes the impact of mergers on the alphas and betas of actual merged firms compared to those of the homemade mergers an investor could have created by buying proportional shares of the two firms. The results provide some evidence of merger synergy. Where alpha and beta shifts were observed, the evidence did not indicate that either the relative size of target firms or concurrent capital structure changes were related to these shifts as current theory suggests. There is weak evidence that nonconglomerate mergers were more frequently synergistic.     

Investment analysis and the adjustment of stock prices to common information

In this article we are concerned with the effect of the numberof investment analysts following a firm on the speed of adjustmentof the firm's stock price to new information that has commoneffects across firms. It is found that returns on portfoliosof firms that are followed by many analysts tend to lead thoseof firms that are followed by fewer analysts, even when thefirms are of approximately the same size. Many analyst firmsalso tend to respond more rapidly to market returns than dofew analyst firms, adjusting for firm size. This relation, however,is nonlinear, and the marginal effect of the number of analystson the speed of price adjustment increases with the number ofanalysts.     

Managerial ownership and firm performance: A re-examination using productivity measurement

The role of productivity in firm performance is of fundamental importance to the US economy. Consistent with the corporate finance approach, this paper uses the ownership stake of a firm's managers as an argument in estimating the firm's production function. Accordingly, this paper brings together the corporate finance and productivity literature. Using a large sample of randomly selected manufacturing firms that does not suffer from any survivorship or large firm size biases, we find that managerial ownership changes are positively related to changes in productivity. We also find a higher sensitivity of changes in managerial ownership to changes in productivity for firms who experience greater than the median change in managerial ownership. These results are robust to including lagged estimates of production inputs, year dummies and separate dummies for each firm to control for unobservable firm characteristics. In addition, we find that the stock market rewards firms with increases in firm value when these firms increase their level of productivity.     

Accounting Earnings Announcements and Differential Predisclosure Information

Recent studies have detected an inverse association between a firm's size and the stock price reaction to the firm's accounting earnings announcements, which has been interpreted as evidence that larger firms have relatively richer information sets. This study expands on this work, using two firm-specific factors to capture both the time and flow-per-period elements of information production (period of listing and firm size respectively) and examines whether these variables are a better information proxy than is size alone. After controlling for firm size, a statistically significant inverse relationship between a firm's period of listing and the information content of its annual earnings announcement is detected. The findings have implications for standard-setters as well as for auditors'assessment of the risk associated with audits of newly listed firms.