scholarly journals The Cross-Section of Expected Stock Returns in Brazil

2016 ◽  
Vol 14 (2) ◽  
pp. 151
Author(s):  
Gyorgy Varga ◽  
Ricardo Dias de Oliveira Brito
Keyword(s):  
Risk Factors ◽  
Stock Market ◽  
Stock Returns ◽  
Cross Section ◽  
Explanatory Power ◽  
Positive Relation ◽  
Cross Sectional ◽  
Expected Stock Returns ◽  
The Cross

In a sample of the Brazilian stock market from 1999 to 2015, this paper shows that the book-to-market and momentum of individual firms capture some of the cross-sectional variation in average stock returns, while the market β and size do not play a role. The positive relation of cross-section of returns with book-to-market is more evident earlier, while the positive relation with momentum is stronger later in the sample. However, because none of these characteristics show explanatory power for all the subsamples studied, we are not fully convinced that they capture fundamental risk factors.

scholarly journals VAR AND THE CROSS-SECTION OF EXPECTED STOCK RETURNS: AN EMERGING MARKET EVIDENCE

2014 ◽  
Vol 15 (3) ◽  
pp. 441-459 ◽  
Author(s):  
Dar-Hsin Chen ◽  
Chun-Da Chen ◽  
Su-Chen Wu
Keyword(s):  
At Risk ◽  
Risk Factor ◽  
Stock Market ◽  
Stock Returns ◽  
Value At Risk ◽  
Emerging Market ◽  
Explanatory Power ◽  
Cross Sectional ◽  
Expected Stock Returns ◽  
The Cross

In this paper we investigate the explanatory power of the market beta, firm size, and the book-to-market ratio, as well as Value-at-Risk regarding the cross-sectional expected stock returns in a less developed stock market – Taiwan's stock market. The main purpose is to examine whether the Value-at-Risk factor has marginal explanatory power related to the Fama-French three-factor model. The empirical results show that Value-at-Risk can account for the average stock returns at both 1% and 5% significance levels based on cross-sectional regression analysis. Moreover, from the perspective of the time series regression, the Value-at-Risk factor can also demonstrate the variation of the stock market, especially for the larger companies in the Taiwan stock market.

Idiosyncratic Volatility and the Cross Section of Expected Returns

2008 ◽  
Vol 43 (1) ◽  
pp. 29-58 ◽  
Author(s):  
Turan G. Bali ◽  
Nusret Cakici
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Idiosyncratic Volatility ◽  
Expected Returns ◽  
Cross Sectional ◽  
Monthly Data ◽  
Portfolio Returns ◽  
Expected Stock Returns ◽  
The Cross ◽  
Data Frequency

AbstractThis paper examines the cross-sectional relation between idiosyncratic volatility and expected stock returns. The results indicate that i) the data frequency used to estimate idiosyncratic volatility, ii) the weighting scheme used to compute average portfolio returns, iii) the breakpoints utilized to sort stocks into quintile portfolios, and iv) using a screen for size, price, and liquidity play critical roles in determining the existence and significance of a relation between idiosyncratic risk and the cross section of expected returns. Portfoliolevel analyses based on two different measures of idiosyncratic volatility (estimated using daily and monthly data), three weighting schemes (value-weighted, equal-weighted, inverse volatility-weighted), three breakpoints (CRSP, NYSE, equal market share), and two different samples (NYSE/AMEX/NASDAQ and NYSE) indicate that no robustly significant relation exists between idiosyncratic volatility and expected returns.

Predicting Equity Returns in Developed Markets

2021 ◽  
pp. 68-90
Author(s):  
A. Doruk Günaydin
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Developed Countries ◽  
Equity Returns ◽  
Market Returns ◽  
Short Term ◽  
Firm Level ◽  
Cross Sectional ◽  
Expected Stock Returns ◽  
The Cross

This chapter examines the relation between various firm-specific variables and the cross-section of equity returns in 26 developed countries. Univariate portfolio analyses using equal-weighted returns show that low beta, book-to-market equity, and momentum analysis are also priced in the cross-section of developed market returns, whereas short-term reversal and downside beta manifest themselves in the opposite direction. Univariate portfolio analysis based on value-weighted returns reveal that the predictive power of book-to-market equity and short-term reversal is driven by small stocks. Multivariate firm-level cross-sectional regression analysis document that momentum, short-term reversal, illiquidity, idiosyncratic volatility, hybrid tail risk, lower partial moment are related to expected stock returns. Overall, the most robust cross-sectional predictor in developed market is found to be return momentum.

scholarly journals Crash Sensitivity and the Cross Section of Expected Stock Returns

2018 ◽  
Vol 53 (3) ◽  
pp. 1059-1100 ◽  
Author(s):  
Fousseni Chabi-Yo ◽  
Stefan Ruenzi ◽  
Florian Weigert
Keyword(s):  
Risk Factors ◽  
Stock Returns ◽  
Cross Section ◽  
Tail Dependence ◽  
Lower Tail ◽  
Tail Risk ◽  
Expected Stock Returns ◽  
The Cross ◽  
Traditional Risk Factors ◽  
The Impact

This article examines whether investors receive compensation for holding crash-sensitive stocks. We capture the crash sensitivity of stocks by their lower-tail dependence (LTD) with the market based on copulas. We find that stocks with strong LTD have higher average future returns than stocks with weak LTD. This effect cannot be explained by traditional risk factors and is different from the impact of beta, downside beta, coskewness, cokurtosis, and Kelly and Jiang’s (2014) tail risk beta. Hence, our findings are consistent with the notion that investors are crash-averse.

scholarly journals The cross-section of expected stock returns and components of idiosyncratic volatility

2021 ◽  
Author(s):  
◽  
Seyed Reza Tabatabaei Poudeh
Keyword(s):  
Risk Factors ◽  
Stock Returns ◽  
Cross Section ◽  
Idiosyncratic Volatility ◽  
Firm Level ◽  
Cross Sectional ◽  
Expected Stock Returns ◽  
Book To Market Ratio ◽  
Alpha Risk ◽  
The Relationship

We examine the relationship between stock returns and components of idiosyncratic volatility—two volatility and two covariance terms— derived from the decomposition of stock returns variance. The portfolio analysis result shows that volatility terms are negatively related to expected stock returns. On the contrary, covariance terms have positive relationships with expected stock returns at the portfolio level. These relationships are robust to controlling for risk factors such as size, book-to-market ratio, momentum, volume, and turnover. Furthermore, the results of Fama-MacBeth cross-sectional regression show that only alpha risk can explain variations in stock returns at the firm level. Another finding is that when volatility and covariance terms are excluded from idiosyncratic volatility, the relation between idiosyncratic volatility and stock returns becomes weak at the portfolio level and disappears at the firm level.

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