scholarly journals Capturing Profitability in Asset Pricing Models for Japanese Equities 1994-2016

2018 ◽  
Vol 10 (5) ◽  
pp. 254
Author(s):  
Dong Liu ◽  
Hiroshi Yadohisa

We follow Ball et al. (2015) to investigate and compare firms’ gross profit, operating profit, and net income as predictors of returns for a cross-section of traded Japanese equities spanning 1994-2016. We test the predictive power of profit measures on cross-sectional stock returns using portfolio tests and Fama-MacBeth regressions, find that gross-profit-to-book-equity significantly predict returns on sampled stocks. Consistent with Novy-Marx (2013), we also find that sorting portfolios by gross profitability and book-to-market ratios outperform in the Japanese market. Hence, we create a Market-Profitability-Value model that captures value and profitability premium among returns of sampled stocks. Based on Gibbons-Ross-Shanken test and economic value, we demonstrate that our enhanced model outperforms Fama–French multiple-factor model in isolating influences on equity returns.

2018 ◽  
Vol 4 (2) ◽  
pp. 118
Author(s):  
Dong Liu

<p><em>I follow Novy Marx (2011, 2013) to investigate and compare firms’ gross profit, operating leverage as predictors of returns for a cross-section of traded Chinese equities spanning from1996-2016. I use portfolio tests and Fama-MacBeth regressions, find that gross-profit-to-market-capitalization ratios significantly predict returns on sampled stocks. I also find that sorting portfolios by gross profitability and size outperforms in the Chinese market. Hence, I create a Market-Profitability-Size model that captures profitability and size premium among returns of sampled stocks. Based on Gibbons-Ross-Shanken test and economic value, I demonstrate that my enhanced model outperforms Fama-French multiple-factor model in isolating influences on equity returns.</em></p>


2017 ◽  
Vol 30 (4) ◽  
pp. 379-394 ◽  
Author(s):  
Raheel Safdar ◽  
Chen Yan

Purpose This study aims to investigate information risk in relation to stock returns of a firm and whether information risk is priced in China. Design/methodology/approach The authors used accruals quality (AQ) as their measure of information risk and performed Fama-Macbeth regressions to investigate association of AQ with future realized stock returns. Moreover, two-stage cross-sectional regression analysis was performed, both at firm level and at portfolio level, to test if the AQ factor is priced in China in addition to existing factors in the Fama French three-factor model. Findings The authors found poor AQ being associated with higher future realized stock returns. Moreover, they found evidence of market pricing of AQ in addition to existing factors in the Fama French three-factor model. Further, subsample analysis revealed that investors value AQ more in non-state owned enterprises than in state owned enterprises. Research limitations/implications The study sample comprises A-shares only and the generalization of the findings is limited by the peculiar institutional and economic setup in China. Originality/value This study contributes to market-based accounting literature by providing further insight into how and if investors value information risk, and it seeks to fill gap in empirical literature by providing evidence from the Chinese capital market.


2020 ◽  
Vol 12 (22) ◽  
pp. 9721
Author(s):  
Ana Belén Alonso-Conde ◽  
Javier Rojo-Suárez

Using stock return data for the Japanese equity market, for the period from July 1983 to June 2018, we analyze the effect of major nuclear disasters worldwide on Japanese discount rates. For that purpose, we compare the performance of the capital asset pricing model (CAPM) conditional on the event of nuclear disasters with that of the classic CAPM and the Fama–French three- and five-factor models. In order to control for nuclear disasters, we use an instrument that allows us to parameterize the linear stochastic discount factor of the conditional CAPM and transform the classic CAPM into a three-factor model. In this regard, the use of nuclear disasters as an explanatory variable for the cross-sectional behavior of stock returns is a novel contribution of this research. Our results suggest that nuclear disasters account for a large fraction of the variation of stock returns, allowing the CAPM to perform similarly to the Fama–French three- and five-factor models. Furthermore, our results show that, in general, nuclear disasters are positively related to the expected returns of a large number of assets under study. Our results have important implications for the task of estimating the cost of equity and constitute a step forward in understanding the relationship between equity risk premiums and nuclear disasters.


Author(s):  
Steve Fan ◽  
Linda Yu

Stock market anomalies representing the predictability of cross-sectional stock returns are one of most controversial topics in financial economic research. This chapter reviews several well-documented and pervasive anomalies in the literature, including investment-related anomalies, value anomalies, momentum and long-term reversal, size, and accruals. Although anomalies are widely accepted, much disagreement exists on the underlying reasons for their predictability. This chapter surveys two competing theories that attempt to explain the presence of stock market anomalies: rational and behavioral. The rational explanation focuses on the improvement of the existing asset pricing models and/or searching for additional risk factors to explain the existence of anomalies. By contrast, the behavioral explanation attributes the predictability to human behavioral biases in collecting and processing financial information, as well as in making investment decisions.


2019 ◽  
Vol 22 (02) ◽  
pp. 1950012
Author(s):  
Thomas Gramespacher ◽  
Armin Bänziger

In two-pass regression-tests of asset-pricing models, cross-sectional correlations in the errors of the first-pass time-series regression lead to correlated measurement errors in the betas used as explanatory variables in the second-pass cross-sectional regression. The slope estimator of the second-pass regression is an estimate for the factor risk-premium and its significance is decisive for the validity of the pricing model. While it is well known that the slope estimator is downward biased in presence of uncorrelated measurement errors, we show in this paper that the correlations seen in empirical return data substantially suppress this bias. For the case of a single-factor model, we calculate the bias of the OLS slope estimator in the presence of correlated measurement errors with a first-order Taylor-approximation in the size of the errors. We show that the bias increases with the size of the errors, but decreases the more the errors are correlated. We illustrate and validate our result using a simulation approach based on empirical data commonly used in asset-pricing tests.


2018 ◽  
Vol 17 (1) ◽  
pp. 78-108 ◽  
Author(s):  
Tatiana Fedyk ◽  
Natalya Khimich

Purpose The purpose of this paper is to link valuation of different accounting items to research and development (R&D) investment decisions and investigate how suboptimal R&D choices during initial public offering (IPO) are linked to future operating and market underperformance. Design/methodology/approach For firms with substantial growth opportunities, accounting net income is a poor measure of the firm’s performance (Smith and Watts, 1992). Therefore, other metrics such as R&D intensity are used by investors to evaluate firms’ performance. This leads to a coexistence of two strategies: if earnings are the main value driver, firms tend to underinvest in R&D; and if R&D expenditures are the main value driver, firms tend to overinvest in R&D. Findings The authors show that the R&D investment decision varies systematically with cross-sectional characteristics: firms that are at the growth stage, unprofitable or belong to science-driven industries are more likely to overinvest, while firms that are able to avoid losses by decreasing R&D expenditure are more likely to underinvest. Finally, they find that R&D overinvestment leads to future underperformance as evidenced by poor operating return on assets, lower product market share, higher frequency of delisting due to poor performance and negative abnormal stock returns. Originality/value While prior literature concentrates on R&D underinvestment as a tool of reporting higher net income, the authors demonstrate the existence of an alternative strategy used by many IPO firms – R&D overinvestment.


2019 ◽  
Vol IV (I) ◽  
pp. 30-38
Author(s):  
Maria Sultana ◽  
Muhammad Imran ◽  
Muhammad Amjad Saleem

The fundamental structure of the present theory of asset pricing underscored clarifying the path as to how the systematic risk is estimated and how investors are adapted to behavior for such risk. The mixed expense of debt and equity that an association should procure to raise funds for its assignments impacts its stock returns through investment choices and is an additional significant segment of business valuation work on the grounds that for putting resources into more risky resources, investors request better yields or higher returns, for legitimizing better yields this risk premium emerging from such risks is included in the returns. Hence, in clarifying portfolio returns, the three-factor model is increased with WACC to analyze its logical force that if WACC is estimated by the market or not through multivariate regressions. Two principle results are deduced by the examination; first; the findings attest to the presence of market premium, size impact, value impact, WACC premium in the equity market of Pakistan. Second, however generally exciting with exceptional interest, when contrasted with FF unique 3-factor model, the models which join WACC outperformed, which also affirmed from Adj.R2 results.


2004 ◽  
Vol 2 (2) ◽  
pp. 183
Author(s):  
Luciano Martin Rostagno ◽  
Gilberto De Oliveira Kloeckner ◽  
João Luiz Becker

This paper examines the hypothesis of asst return predictability in the Brazilian Stock Market (Bovespa). Evidence suggests that seven factors explain most of the monthly differential returns of the stocks included in the sample. Within the factors that present statistically significant mean, two are liquidity factors (market capitalization and trading volume trend), three refer to price level of stocks (dividend to price, dividend to price trend, and cash flow to price), and two relate to price history of stocks (3 and 12 months excess return). Contradicting theoretical assumptions, risk factors present no explanatory power on cross-sectional returns. Using an expected return factor model, it is contended that stock returns are quite predictable. An investment simulation shows that the model is able to assemble portfolios with statistically significant higher returns. Additional tests indicate that the winner portfolios are not fundamentally riskier suggesting mispricing of assets in the Brazilian stock Market.


2019 ◽  
Vol 10 (2) ◽  
pp. 290-334 ◽  
Author(s):  
Chris Kirby

Abstract I test a number of well-known asset pricing models using regression-based managed portfolios that capture nonlinearity in the cross-sectional relation between firm characteristics and expected stock returns. Although the average portfolio returns point to substantial nonlinearity in the data, none of the asset pricing models successfully explain the estimated nonlinear effects. Indeed, the estimated expected returns produced by the models display almost no variation across portfolios. Because the tests soundly reject every model considered, it is apparent that nonlinearity in the relation between firm characteristics and expected stock returns poses a formidable challenge to asset pricing theory. (JEL G12, C58)


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yann Ferrat ◽  
Frédéric Daty ◽  
Radu Burlacu

PurposeThe growth of socially responsible assets has been exponential over the last decade, they now account for almost a third of professional investments. As the growth persists, faith and conviction investors reshape the equity markets. To fully comprehend the impact of socially conscious participants on security returns, this paper attempts to provide insights on how responsible investment growth has impacted the returns of sustainable stocks. The examination is split by investment horizon to account for short and long effects.Design/methodology/approachUsing an exclusive dataset of non-financial ratings, provided by MSCI ESG research, the authors examine the cross-sectional returns of US and European sustainability-leading and lagging corporations between 2007 and 2019. Panel models robust to country, firm-year and industry effects were then employed to examine the impact of responsible investment growth on future stock returns.FindingsThe authors find evidence that the impact of responsible investment growth is dual contingent upon the timeframe considered. In the short run, sustainability-leading and lagging firms display similar stock returns. However, the spread in returns is negative over long horizons and increasing over time.Originality/valueThe examination performed in this study highlights the significant effect of responsible investment growth on future stock returns. Overall, the authors’ findings are consistent with the price pressure hypothesis in the short run and the cost of capital alteration over longer horizons.


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