Short‐term momentum patterns in stock and sectoral returns: evidence from India

Sehgal, Sanjay; Jain, Sakshi

doi:10.1108/09727981111129327

Cited by 32 publications

(25 citation statements)

References 71 publications

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“…In aggregate, the results suggest that four fundamental risk factors (MRKT, SMB, HML and UMD) are prominent for explaining the cross-section of stock return behaviour in the Indian stock market. Our result is consistent with the four factor pricing evidence of Sehgal and Jain (2011) in the Indian stock market, Her et al (2004) findings for Canadian stock market and Keene and Peterson's (2007) findings for the US stock market. However, in contrast to the findings of Lam and Tam (2011) in the case of the Korean stock market, we find evidence of significant momentum pricing in the context of the Indian stock market.…”

Section: Source: Authorssupporting

confidence: 94%

Investor Sentiment and Stock Return: Do Industries Matter?

Dash

Mahakud

2013

Margin: The Journal of Applied Economic Research

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The basic objective of this article is to evaluate the pricing implications of market-wide investor sentiment risk for cross-sectional return variations of Indian listed companies across industry groups. A multivariate time-series regression approach has been used to examine the impact of sentiment risk on stock return behaviour in the presence of other market-wide systematic risk factors. Our results suggest that the role of sentiment risk in the determination of a cross-section of stock returns is not uniform across the test asset portfolios formed on the basis of size, book-to-market equity, liquidity and momentum characteristics. For all portfolios, the impact of sentiment risk on the cross-section of stock returns behaviour has been disproportionately negative. The effect holds even after controlling for systematic market-wide risk factors. Although the impact of sentiment risk on industry-shorted portfolio returns persists in accordance with the theoretical argument, the cross-sectional variation with respect to different industries has been heavily dependent on the availability of stocks in that particular industry. The commonality of the sentiment effect across industry is not similar, as it is for the aggregate market. The results suggest that generalisation of the hard-to-value and difficult-to-arbitrage argument must be judged with caution, keeping the industry effects in mind.

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Section: Source: Authorssupporting

confidence: 94%

Investor Sentiment and Stock Return: Do Industries Matter?

Dash

Mahakud

2013

Margin: The Journal of Applied Economic Research

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“…Next to evaluate if sector factor plays an additional role in explaining returns, we add a sector momentum factor as an additional risk factor in the liquidity augmented FF model (see Sehgal and Jain(2011) for details on factor construction). The sector factor has been formed as the difference of winner sector and loser sector, (WML).…”

Section: Methodsmentioning

confidence: 99%

A Search for Rational Sources of Stock Return Anomalies: Evidence from India

Sehgal¹,

Subramaniam²,

Morandière³

2012

IJEF

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In this paper we investigate the presence of the following asset pricing anomalies viz. size, value, momentum, liquidity, accruals, profitability and net stock issues in India. Size effect is the strongest with a difference of 4.4 % per month between small and big stock returns. A positive relationship is reported between accruals, stock issues and returns and a negative relation between profitability and returns which is in contrast to prior research. CAPM is unable to explain these anomalies with the exception of net stock issues. The Fama French (FF) model is able to capture value, profitability and accruals. While liquidity anomaly is explained by a liquid augmented FF model, the sector and earnings momentum factors do not contribute significantly towards explaining returns. Size and short term momentum are persistent and hence continue to pose challenge to rational asset pricing in India. Our findings shall be highly useful for investment analysts and portfolio managers. The research contributes to asset pricing literature especially for emerging markets.

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“…Fama and French skip one year between portfolio formation and holding windows to control for short-term effects so that long-term stock return patterns can be clearly observed. Sehgal and Jain (2011) report strong short-term prior return patterns (up to 12 months) in India. Hence we skip 12 months between portfolio formation and holding windows to control for these short-term momentum effects.…”

Section: Long-term Prior Return Patterns In Stock Returnsmentioning

confidence: 94%

Long-term prior return patterns in stock and sector returns in India

Sehgal

Jain

2014

Journal of Advances in Management Research

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to analyze long-term prior return patterns in stock returns for India. Design/methodology/approach -The methodology involves portfolio generation based on company characteristics and long-term prior return (24-60 months). The characteristic sorted portfolios are then regressed on risk factors using one factor (capital asset pricing model (CAPM)) and multi-factor model (Fama-French (FF) model and four factor model involving three FF factors and an additional sectoral momentum factor). Findings -After controlling for short-term momentum (up to 12 months) as documented by Sehgal and Jain (2011), the authors observe that weak reversals emerge for the sample stocks. The risk model CAPM fails to account for these long-run prior return patterns. FF three-factor model is able to explain long-term prior return patterns in stock returns with the exception of 36-12-12 strategy. The value factor plays an important role while the size factor does not explain cross-section of average returns. Momentum patterns exist in long-term sector returns, which are stronger for long-term portfolio formation periods. Further, the authors construct sector factor and observe that prior returns patterns in stock returns are partially absorbed by this factor. Research limitations/implications -The findings are relevant for investment analysts and portfolio managers who are continuously tracking global markets, including India, in pursuit of extra normal returns. Originality/value -The study contributes to the asset pricing and behavioral literature from emerging markets.

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Short‐term momentum patterns in stock and sectoral returns: evidence from India

Cited by 32 publications

References 71 publications

Investor Sentiment and Stock Return: Do Industries Matter?

Investor Sentiment and Stock Return: Do Industries Matter?

A Search for Rational Sources of Stock Return Anomalies: Evidence from India

Long-term prior return patterns in stock and sector returns in India

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