The Cross-Sectional Distribution of Stock Market Values

2010 ◽  
Author(s):  
Eduardo Friedman ◽  
Jorge Ricardo Friedman
2014 ◽  
Vol 15 (3) ◽  
pp. 441-459 ◽  
Author(s):  
Dar-Hsin Chen ◽  
Chun-Da Chen ◽  
Su-Chen Wu

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.


2014 ◽  
pp. 21-38 ◽  
Author(s):  
Hung T. Nguyen ◽  
Hang V. D. Pham ◽  
Nguyen Hung

This paper studies the cross-sectional profitability of moving average timing portfolios in the French stock market over the period from January 1, 1995 to December 31, 2012. The results provide strong evidence that the moving average timing outperforms the buy-and-hold strategy with higher returns and less risk exposure. On average, moving average portfolios generate an abnormal return of 3.72% per annum and always perform better than buy-and-hold benchmark portfolios across different lag length and volatility portfolios. Moreover, our results prevail after we control for transaction costs. Keywords:Technical analysis, moving average, cross-sectional profit


2013 ◽  
Vol 5 (4) ◽  
pp. 271-294 ◽  
Author(s):  
Saumya Ranjan Dash ◽  
Jitendra Mahakud

Purpose – The purpose of this paper is to investigate the firm-specific anomaly effect and to identify market anomalies that account for the cross-sectional regularity in the Indian stock market. The paper also examines the cross-sectional return predictability of market anomalies after making the firm-specific raw return risk adjusted with respect to the systematic risk factors in the unconditional and conditional multifactor specifications. Design/methodology/approach – The paper employs first step time series regression approach to drive the risk-adjusted return of individual firms. For examining the predictability of firm characteristics on the risk-adjusted return, the panel data estimation technique has been used. Findings – There is a weak anomaly effect in the Indian stock market. The choice of a five-factor model (FFM) in its unconditional and conditional specifications is able to capture the book-to-market equity, liquidity and medium-term momentum effect. The size, market leverage and short-run momentum effect are found to be persistent in the Indian stock market even with the alternative conditional specifications of the FFM. The results also suggest that it is naï argue for disappearing size effect in the cross-sectional regularity. Research limitations/implications – Constrained upon the data availability, certain market anomalies and conditioning variables cannot be included in the analysis. Practical implications – Considering the practitioners' prospective, the results indicate that the profitable investment strategy with respect to the small size effect is still persistent and warrants close-ended mutual fund investment portfolio strategy for enhancing the long-term profitability. The short-run momentum effect can generate potential profits given a short-term investment horizon. Originality/value – This paper provides the first-ever empirical evidence from an emerging stock market towards the use of alternative conditional multifactor models for the complete explanation of market anomalies. In an attempt to analyze the anomaly effect in the Indian stock market, this paper provides further evidence towards the long-short hedge portfolio return variations in terms of a wide set of market anomalies that have been documented in prior literature.


2018 ◽  
Vol 44 (4) ◽  
pp. 439-458 ◽  
Author(s):  
Houda BenMabrouk

Purpose The purpose of this paper is to investigate herding behavior around the crude oil market and the stock market and the possible cross-herding behavior between the two markets. The analysis examines also the herding behavior during financial turmoil and includes the investor sentiment and market volatility. Design/methodology/approach The authors use a modified version of the cross-sectional standard deviation and the cross-sectional absolute deviation to include investor sentiment, financial crisis and market volatility. Findings The authors find that the volatility of the stock market reduces the herding behavior around the oil market and boosts that around the stock market. However, the investors’ sentiment reduces the herding around the stock market and boosts that around the crude oil market. Consequently, the authors can conclude that the herding behavior around the two markets moves inversely and the herding in each market is enhanced by the lack of information in the other market. Research limitations/implications This paper is limited to the herding of stocks around the crude oil market and ignores the possible herding of commodities around the oil market. Originality/value The originality of the paper rests on the study of the possible cross-herding behavior between the oil market and the stock market especially during financial turmoil.


2016 ◽  
Vol 14 (2) ◽  
pp. 151
Author(s):  
Gyorgy Varga ◽  
Ricardo Dias de Oliveira Brito

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.


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