Empirical evidence of conditional asset pricing in the Indian stock market

Das, Sudipta

doi:10.1016/j.ecosys.2014.07.003

Cited by 18 publications

(8 citation statements)

References 33 publications

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“…Among all the factors considered here, the book-to-market effect is most pervasive. These both findings (negative size effect and positive value effect) are in conformity with the existing literature (Aziz & Ansari, 2014;Das, 2015).…”

Section: Empirical Findingssupporting

confidence: 93%

Idiosyncratic Risk and Stock Returns: A Quantile Regression Approach

Aziz¹,

Ansari²

2016

Proceedings of the 5th Economic &Amp; Finance Conference, Miami

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The relation between idiosyncratic risk and stock returns is currently a topic of debate in the academic literature. So far the evidence regarding the relation is mixed. This study aims to investigate the cross-sectional relation between idiosyncratic risk and stock returns in the Indian stock market employing quantile regressions. Using quantile regressions, this study demonstrates that idiosyncratic volatility and stock returns relation is quantile dependent. The relation between idiosyncratic volatility and stock returns is parabolic. The high idiosyncratic risk is associated with high (low) excess returns at the upper (lower) quantile of the conditional distribution. This partially explains the inconclusive evidence on the idiosyncratic volatility and the stock returns relation in the literature.

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Section: Empirical Findingssupporting

confidence: 93%

Idiosyncratic Risk and Stock Returns: A Quantile Regression Approach

Aziz¹,

Ansari²

2016

Proceedings of the 5th Economic &Amp; Finance Conference, Miami

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“…As far as literary work on Indian stock market is concerned, the stock price fluctuations have been looked into through differentlenses. For example, Das (2015) proposed that the cross-sectional variation in expected stock returns was a response of two driving factors, viz. firm size and book-to-market ratio.…”

Section: Introductionmentioning

confidence: 99%

Psychology of Indian Stock Market: An Evidence of Seasonal Affected Disorder

Raut

Kumar

2020

Asia-Pacific Journal of Management Research and Innovation

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This article examines the association between daylight hours as a proxy for the seasonal affective disorder (SAD) and stock market return. Past studies have documented different decision-making mechanisms induced by investors’ cognition mainly influenced by greed and fear. However, this study appears to be different from evidence where investors’ mood is affected by seasonality, which plays a vital role in risk-taking propensity. Data have been taken from three indexes of Bombay Stock Exchange (BSE), for the period between April 2003 and December 2016. The impact of SAD on stock market return was examined by using naïve ordinary least square (OLS) model. This study reports a negative relationship between daylight hours and pattern of midcap as well as smallcap indexes, which are in alignment with mood maintenance hypothesis (MMH). The result of negative correlation suggests a summer-type SAD, which is an addition to the findings of the existing literature.

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“…Balakrishnan (2014) found that the three factors of Fama-French performed better in explaining average returns as compared to the single factor CAPM. Das (2015) showed that the size of the firm and the value factor played a major role in explaining the stock returns in India. Sreenu (2018) found that the Fama-French three-factor model provides a better explanation as compared to the CAPM for the risk-return variations in the Indian capital market.…”

Section: Review Of Literaturementioning

confidence: 99%

Role of leverage and liquidity risk in asset pricing: evidence from Indian stock market

Jain

Singla

2021

XJM

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Purpose Asset pricing revolves around the core aspects of risk and expected return. The main objective of the study is to test different asset pricing models for the Indian securities market. This paper aims to analyse whether leverage and liquidity augmented five-factor model performs better than Capital Asset Pricing Model (CAPM), Fama and French three-factor model, leverage augmented four-factor model and liquidity augmented four-factor model. Design/methodology/approach The data for the current study comprises records on prices of securities that are part of the Nifty 500 index for a time frame of 14 years, that is, from October 2004 to September 2017 consisting of 183 companies using time series regression. Findings The results indicate that the five-factor model performs better than CAPM and the three-factor model. The model outperforms leverage augmented and liquidity augmented four-factor models. The empirical evidence shows that the five-factor model has the highest explanatory power among the entire asset pricing models considered. Practical implications The present study bears certain useful implications for various stakeholders including fund managers, investors and academicians. Originality/value This study presents a five-factor model containing two additional factors, that is, leverage and liquidity risk along with the Fama-French three-factor model. These factors are expected to give more value to the model in comparison to the Fama-French three-factor model.

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Empirical evidence of conditional asset pricing in the Indian stock market

Cited by 18 publications

References 33 publications

Idiosyncratic Risk and Stock Returns: A Quantile Regression Approach

Idiosyncratic Risk and Stock Returns: A Quantile Regression Approach

Psychology of Indian Stock Market: An Evidence of Seasonal Affected Disorder

Role of leverage and liquidity risk in asset pricing: evidence from Indian stock market

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