The survivorship bias, share price effect, and small firm effect in Canadian markets

After controlling for survivorship bias, we examine the relation between average returns, firm size, and price levels for Canadian stocks during the 1975-1994 period. Our findings indicate that there is a significant inverse share price level effect in Canadian markets. When we compare the results of the overall sample with the groups of surviving firms and delisted stocks, the latter group shows strong performance for large-size, high-priced stocks. Evidence that supports an independent size effect is less clear for Canadian stocks. A small size effect exists only among the higher share price denominations, which suggests a confounded size-price effect. Although the delisted group returns are statistically different from those of the survivor and the overall groups, which implies some evidence of survivorship bias, the difference between the survivor group and the overall group is weak at best.     

Noisy Prices and Inference Regarding Returns

Temporary deviations of trade prices from fundamental values impart bias to estimates of mean returns to individual securities, to differences in mean returns across portfolios, and to parameters estimated in return regressions. We consider a number of corrections, and show them to be effective under reasonable assumptions. In an application to the Center for Research in Security Prices monthly returns, the corrections indicate significant biases in uncorrected return premium estimates associated with an array of firm characteristics. The bias can be large in economic terms, for example, equal to 50% or more of the corrected estimate for firm size and share price.     

Interaction of size,book‐to‐market and momentum effects in Australia

This study seeks to disentangle the effects of size, book‐to‐market and momentum on returns. Initial results show that each characteristic has a role in explaining returns, but that there is interaction between size and momentum, as well as between size and book‐to‐market. Three key findings emerge. First, the size premium is the strongest, particularly in the loser portfolios. Second, the value premium is generally limited to the smallest portfolios. Third, the momentum premium is evident for the large‐ and middle‐sized portfolios, but loser stocks significantly outperform winner stocks in the smallest size portfolio. When these interactions are controlled with multivariate regression, we find a significant negative average relation between size and returns, a significant positive average relation between book‐to‐market and returns, and a significant positive average relation between momentum and returns.     

The Return of the Size Anomaly: Evidence from the German Stock Market

This paper examines the size effect in the German stock market and intends to address several unanswered issues on this widely known anomaly. Unlike recent evidence of a reversal of the size anomaly this study documents a conditional relation between size and returns. I also detect strong momentum across size portfolios. The results indicate that the marginal effect of firm size on stock returns is conditional on the firm's past performance. I use an instrumental variable estimation to address Berk's critique of a simultaneity bias in prior studies on the small firm effect and to investigate the economic rationale behind firm size as an explanatory variable for the variation in stock returns. The analysis in this paper indicates that firm size captures firm characteristic components in stock returns and that this regularity cannot be explained by differences in systematic risk.     

Industry Concentration,Firm Efficiency and Average Stock Returns: Evidence from Australia

This study examines the relationship between industry concentration and level of firm efficiency and their effect on cross-sectional stock returns in Australian market. Our analysis shows that industry concentration and firm efficiency have independent effects on stock returns. By forming 25 double-sorted portfolios based on industry concentration and firm efficiency, INEFFICIENT firms in concentrated industry earn highest stock returns, while EFFICIENT firms in concentrated industry earn lowest stock returns. Also we find that industry concentration appears to be associated with market share while efficiency has a greater effect on firm earnings. In our cross-sectional regressions, industry concentration shows a positive relationship with average stock returns while firm efficiency shows a negative association with average stock returns. The concentration and efficiency effects are persistent throughout the sample period and is robust after controlling for size and book-to-market.     

The efficiency of the buy-write strategy: Evidence from Australia

We examine the performance of the buy-write option strategy (BWS) on the Australian Stock Exchange and analyse whether such an investment opportunity violates the efficient market hypothesis on the basis of its risk and returns. This study investigates the relationship between buy-write portfolios returns and past trading volume and other fundamental financial factors including dividend yield, firm size, book to market ratio, earnings per share (EPS), price earnings ratio and value stocks within these portfolios. We also test the profitability of the buy-write strategy during bull and bear markets. Consistent with the literature, it is observed that BWS offers superior risk adjusted returns for low levels of out-of-moneyness and contrary evidence is observed for deeper out-of-money portfolios. Consistent with a preference for options with a maturity of around 3 months in Australia, this research shows that quarterly rebalancing periods offer better returns for the BWS.     

THE INTRA-INDUSTRY EFFECTS OF OPEN MARKET SHARE REPURCHASES: CONTAGION OR COMPETITIVE?

We examine the extent to which announcements of open market share repurchase programs affect the valuation of competing firms in the same industry. On average, although firms announcing open market share repurchase programs experience a significantly positive stock price reaction at announcement, portfolios of rival firms in the same industry experience a significant and contemporaneous negative stock price reaction. This suggests that perceived changes in the competitive positions of the repurchasing firms occur at the expense of rival firms and dominate any signals of favorable industry conditions. Thus, the competitive intra-industry effects of open market repurchases outweigh any contagion effects. In addition, cross-sectional tests indicate that these competitive effects are more pronounced in industries characterized by a lower degree of competition and less correlation between the stock returns of the repurchasing firm and its rivals.     

THE CROSS-AUTOCORRELATION OF SIZE-BASED PORTFOLIO RETURNS IS NOT AN ARTIFACT OF PORTFOLIO AUTOCORRELATION

Prior studies find evidence of asymmetric size-based portfolio return cross-autocorrelations where lagged large firm returns lead current small firm returns. However, some studies question whether this economic relation is independent of the effect of portfolio return autocorrelation. We formally test for this independence using size-based portfolios of New York Stock Exchange and American Stock Exchange securities and, separately, portfolios of Nasdaq securities. Results from causality regressions indicate that, across all markets, lagged large firm returns predict current small firm returns, even after controlling for autocorrelation in small firm returns. These cross-autocorrelation patterns are stronger for Nasdaq securities.     

The pricing of firms with expected losses/profits: The role of January

We examine the role of January in the relation between expected losses/profits and future stock returns. We predict and find that the relation between expected losses/profits and future returns reverses from the usual positive relation in non‐January months to a negative one in January. The reverse January relation is consistent across sample years, is observed in the United States and international markets, and is incremental to other variables associated with January returns. At least part of the reverse January relation is explained by tax‐loss selling. Further analysis shows that the reverse January relation results in a temporary price drift away from fundamental value. In other words, we find that abnormal positive (negative) future returns do not always indicate past under(over)valuation. Overall, our results illustrate the importance of controlling for the effect of January when examining how investors price expected losses/profits.     

Earnings Yields,Market Values,and Stock Returns

Earlier evidence concerning the relation between stock returns and the effects of size and earnings to price ratio (E/P) is not clear-cut. This paper re-examines these two effects with (a) a substantially longer sample period, 1951–1986, (b) data that are reasonably free of survivor biases, (c) both portfolio and seemingly unrelated regression tests, and (d) an emphasis on the important differences between January and other months. Over the entire period, the earnings yield effect is significant in both January and the other eleven months. Conversely, the size effect is significantly negative only in January. We also find evidence of consistently high returns for firms of all sizes with negative earnings.     

行为模型新解及其实证检验

在以信息逐步扩散和投资者有限理性为主要假设的行为模型中,特定信息交易者和市场信息交易者的比例对股价行为有着重要影响：当特定信息交易者占多数时,个股收益更容易呈现正自相关;当市场信息交易者占多数时,个股收益更容易呈现负自相关。该模型可以解释成熟股市中存在基于总收益的动量效应,而中国股市中不存在基于总收益的动量效应,仅存在基于公司特定收益的动量效应;并解释了市场平均收益呈现负自相关等。另外,实证分析支持了传统的CAPM和APT定价模型中的带越小,动量效应越显著的结论。     

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.     

Information Transfer Effects of Bond Rating Downgrades

This paper investigates information transfer effects of bond rating downgrades measured by equity abnormal returns for industry portfolios. Industry rivals can be subject to two opposing effects, the contagion effect and the competition effect. We find that the net effect is strongly dependent on the original bond rating of the downgraded firm. For investment‐grade (speculative‐grade) firms, industry abnormal equity returns are negative (positive), which implies a predominant contagion (competition) effect. The analysis reveals a rich pattern of positive and negative correlations across negative credit events, which can be used to improve our understanding of portfolio credit risk models.     

Firm size,information acquisition and price efficiency

We present a model in a competitive market where traders choose between a small and a large firm to acquire costly private information, but they also obtain free public information by observing equilibrium share prices. Our major finding is the existence of a noisy rational expectation competitive equilibrium, in which there are more informed traders of the large firm than those of the small firm. As a result, share prices of the large firm are more informative than those of the small firm. Our empirical study supports the analytical results. By using a bivariate vector autoregressive regression, we are able to conduct a variance decomposition of share prices for different size portfolios. We find that prices of large-size portfolios are more informative because non-value-related price shocks are less important in driving price changes of large-size portfolios than in the case of small-size portfolios.     

What do the Fama–French factors add to C-CAPM?

This study extends standard C-CAPM by including two additional factors related to firm size (SMB) and book-to-market value ratio (HML) — the Fama–French factors. C-CAPM is least able to price firms with low book-to-market ratios. The explanation of these returns, as well as the returns on the SMB and HML portfolios, is significantly improved by the inclusion of the HML factor. The component of the risk premia explained by consumption varies across size. We suggest that a possible explanation for the role of HML is its association with the investment growth prospects of firms.     

Can stochastic discount factor models explain the cross-section of equity returns?

We propose a multivariate test of the capital asset pricing model (C-CAPM) of the cross-sectional variation in equity returns in which we compare cross-sectional variation in equity returns to the cross-sectional variation in their conditional covariance with stochastic discount factors. We use a multivariate generalized heteroskedasticity in mean model to estimate 25 portfolios that are formed on size and the book-to-market ratio. Each portfolio is allowed to have its own no-arbitrage condition. We find that although the conditional covariances of returns with consumption exhibit negative variation across size, they do not vary across the book-to-market ratio. Thus, C-CAPM can capture the size effect, but not the value effect. The fit is, however, improved by allowing the coefficients on the consumption covariances to be different. The value effect appears to be associated with the book-to-market ratio as well as size. On its own the book-to-market ratio does not generate additional information about average returns to C-CAPM. A possible explanation for these findings is that both small and low book-to-market ratio firms are expected to have higher rates of growth.     

New evidence on oil price and firm returns

In this paper, we examine the relationship between oil price and firm returns for 560 US firms listed on the NYSE. First, we find that oil price affects returns of firms differently depending on their sectoral location. Second, we find strong evidence of lagged effect of oil price on firm returns. Third, we test whether oil price affects firm returns based on different regimes and find that in five out of the 14 sectors this is indeed the case. Finally, we unravel that oil price affects firm returns differently based on firm size, implying strong evidence of size effects.     

The impact of board size on firm performance: evidence from the UK

We examine the impact of board size on firm performance for a large sample of 2746 UK listed firms over 1981–2002. The UK provides an interesting institutional setting, because UK boards play a weak monitoring role and therefore any negative effect of large board size is likely to reflect the malfunction of the board's advisory rather than monitoring role. We find that board size has a strong negative impact on profitability, Tobin's Q and share returns. This result is robust across econometric models that control for different types of endogeneity. We find no evidence that firm characteristics that determine board size in the UK lead to a more positive board size–firm performance relation. In contrast, we find that the negative relation is strongest for large firms, which tend to have larger boards. Overall, our evidence supports the argument that problems of poor communication and decision-making undermine the effectiveness of large boards.     

Accounting Ratios and the Cross‐section of Expected Stock Returns

Under clean‐surplus accounting, the log return on a stock can be decomposed into a linear function of the contemporaneous log return on equity, the contemporaneous log dividend–price ratio (if the stock pays a dividend), and both the contemporaneous and lagged values of the log book‐to‐market equity ratio. This paper studies the implications of this decomposition for the cross‐section of conditional expected stock returns. The empirical analysis reveals that the log accounting ratios capture cross‐sectional variation in both the conditional mean and conditional variance of log stock returns, which is consistent with the decomposition. It also brings fresh insights to the relation between firm size (market equity) and conditional expected stock returns. The evidence indicates that the conditional median return increases with firm size, while the conditional return skewness decreases with firm size. Empirically, the skewness effect outweighs the median effect, leading to the well‐documented inverse relation between size and average returns. The results of out‐of‐sample tests suggest that investors could use the information provided by the observed values of the log accounting ratios to formulate more effective portfolio strategies.