Investor sentiment, risk factors and stock return: evidence from Indian non‐financial companies

doi:10.1108/17554191211252699

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Investor sentiment, risk factors and stock return: evidence from Indian non‐financial companies

Journal Article•DOI•

Investor sentiment, risk factors and stock return: evidence from Indian non‐financial companies

Saumya Ranjan Dash¹, Jitendra Mahakud•Institutions (1)

Indian Institute of Technology Kharagpur¹

17 Aug 2012-Journal of Indian Business Research (Emerald Group Publishing Limited)-Vol. 4, Iss: 3, pp 194-218

TL;DR: This article employed the Fama and French time series regression approach to examine the impact of market risk premium, size, book-to-market equity, momentum and liquidity as risk factors on stock return.

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Abstract: Purpose – The purpose of this paper is to evaluate the pricing implication of aggregate market wide investor sentiment risk for cross sectional return variation in the presence of other market wide risk factors.Design/methodology/approach – The paper employs the Fama and French time series regression approach to examine the impact of market risk premium, size, book‐to‐market equity, momentum and liquidity as risk factors on stock return. Given the importance of inherent imperfect rationality or sentiment risk, the paper further investigates the impact of investor sentiment on the cross section of stock return.Findings – The choice of a five factor model is apparently persuasive for consideration in investment decisions. Stocks are hard to value and difficult to arbitrage with characteristics which are significantly influenced with the sentiment risk. It is naive to argue for the universal pricing implication of sentiment risk in a multifactor model framework.Research limitations/implications – The test as...

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Journal Article•DOI•

Asymmetric relationship of investor sentiment with stock return and volatility: evidence from India

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Madhumita Chakraborty, Sowmya Subramaniam

18 Jun 2020-Review of Behavioral Finance

TL;DR: In this article, the authors examined the cross-sectional and asymmetric relationship of investor sentiment with the stock returns and volatility in India and found that lower sentiment induces fear-induced selling, thereby lowering the returns and high sentiment is followed by lower future returns as market reverts to fundamentals.

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Abstract: The study examines the cross-sectional and asymmetric relationship of investor sentiment with the stock returns and volatility in India.,The investor sentiment is captured using a market-based measure Market Mood Index (MMI) and a survey-based measure Consumer Sentiment Index (CSI). The asymmetric effect of the relationship is examined using quantile causality approach and cross-sectional effect is examined by considering indices such as the BSE Sensex, and the various size indices such as BSE Large cap, BSE Mid cap and BSE Small cap.,The result of the study found that investor sentiment (MMI) cause stock returns at extreme quantiles. Lower sentiment induces fear-induced selling, thereby lowers the returns and high sentiment is followed by lower future returns as market reverts to fundamentals. On the other hand, bullish shifts in sentiment lower the volatility. There exists a positive feedback effect of stock return and volatility in the formation of investor sentiment.,The study captures both asymmetric and cross-sectional relationship of investor sentiment and stock market in an emerging economy, India. The study uses a novel data set (i.e.) MMI which captures the sentiment based on market indicators and are widely disseminated to the public.

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13 citations

Journal Article•DOI•

Stylized patterns of implied volatility in India: a case study of NSE Nifty options

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Imlak Shaikh¹, Puja Padhi¹•Institutions (1)

Indian Institute of Technology Bombay¹

29 Aug 2014-Journal of Indian Business Research

TL;DR: In this paper, the authors examined the volatility smile of the Indian options market and the potential determinants of implied volatility are the degree of moneyness, time-to-expiration and the liquidity of the strikes.

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Abstract: Purpose – The aim of this study is to examine the “volatility smile” or/and “skew”, term structure and implied volatility surfaces based on those European options written in the standard and poor (S&P) Nifty equity index. The stochastic nature of implied volatility across strike price, time-to-expiration and moneyness violates the core assumption of the Black–Scholes option pricing model. Design/methodology/approach – The potential determinants of implied volatility are the degree of moneyness, time-to-expiration and the liquidity of the strikes. The empirical work has been expressed by means of a simple ordinary least squares (OLS) framework and presents the estimation results according to moneyness, time-to-expiration and liquidity of options. Findings – The options data give evidence of the existence of a classical U-shaped volatility smile for the Indian options market. Indeed, there is some evidence that the “volatility smirk” which pertains to 30-day options and also implied volatility remain higher...

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13 citations

Cites background from "Investor sentiment, risk factors an..."

...There is a substantial body of work (Dash and Mahakud, 2012; Chandra, 2012; Kumar and Pandey, 2013; Shaikh and Padhi, 2013; and Padhi and Shaikh, 2014) that deals with market efficiency, stock returns and capital flow, investor sentiment and the information content of option prices....
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Journal Article•DOI•

Investor Sentiment and Stock Return: Do Industries Matter?:

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Saumya Ranjan Dash¹, Jitendra Mahakud¹•Institutions (1)

Indian Institute of Technology Kharagpur¹

23 Aug 2013-Margin: The Journal of Applied Economic Research

TL;DR: In this paper, the authors evaluate the pricing implications of market-wide investor sentiment risk for cross-sectional return variations of Indian listed companies across industry verticals across industry segments and industries.

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Abstract: 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 g...

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11 citations

Cites background or methods or result from "Investor sentiment, risk factors an..."

...The second approach is the implicit sentiment proxy (ISP) derived from selected market statistics (Baker and Wurgler, 2006, 2007; Brown and Cliff, 2004, 2005; Dash and Mahakud, 2012)....
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...The positive or negative impact of such proxies on our aggregate sentiment measure is consistent with the theoretical arguments given in the related literature (Brown and Cliff, 2004, 2005; Baker and Wurgler, 2006, 2007; Kumar and Lee, 2006; Finter et al., 2011; Baker et al., 2011; Dash and Mahakud, 2012)....
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...In common, using alternative sentiment proxies, the existing literature supports a negative relationship between individual investor sentiment and stock returns across different markets (Brown and Cliff, 2004, 2005; Baker and Wurgler, 2006, 2007; Baker et al., 2011; Changsheng and Yongfeng, 2012; Dash and Mahakud, 2012; Fisher and Statman, 2000; Finter et al., 2011; Kumar and Lee, 2006; Schmeling, 2009; Schmeling, 2009)....
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...Empirical consistency for the explanation of cross-section of stock returns behaviour of these risk factors in several markets is the basic motivation for the inclusion of such factors in our analysis (Dash and Mahakud, 2012; Her et al., 2004; Keene and Peterson, 2007; Lam and Tam, 2011; Pastor and Stambaugh, 2003; Sehgal and Jain, 2011)....
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Journal Article•DOI•

Does Shariah index hedge against sentiment risk? Evidence from Indian stock market using time–frequency domain approach

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Saumya Ranjan Dash¹, Debasish Maitra¹•Institutions (1)

Indian Institute of Management Indore¹

01 Sep 2018-Journal of Behavioral and Experimental Finance

TL;DR: In this paper, the authors examined the relationship of Shariah index returns with sentiments, risk and macroeconomic factors in the Indian stock market and found significant relationship between macro variables and Sharia index returns.

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11 citations

Journal Article•DOI•

Do Asset Pricing Models Explain Size, Value, Momentum and Liquidity Effects? The Case of an Emerging Stock Market

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Saumya Ranjan Dash¹, Jitendra Mahakud²•Institutions (2)

Institute of Management Technology, Ghaziabad¹, Indian Institute of Technology Kharagpur²

17 Dec 2014-Journal of Emerging Market Finance

TL;DR: In this paper, the authors examined whether the alternative asset pricing models and more specifically the liquidity-augmented multifactor models can explain the effect of size, value, momentum and liquidity on cross-section of stock returns in India during September 1995 to March 2011.

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Abstract: This article examines whether the alternative asset pricing models and more specifically the liquidity-augmented multifactor models can explain the effect of size, value, momentum and liquidity on cross section of stock returns in India during September 1995 to March 2011. We employ time series and panel data methodology to carry out the analysis. Our findings suggest that the value and liquidity effects are often explained, but the explanatory power of size and short-run past return or momentum effect remain consistent irrespective of alternative asset pricing models risk adjustment process. The liquidity-augmented multifactor models are found to have better explanatory power than to the other alternative multifactor models. The relative performance of liquidity-augmented multifactor modes for capturing the role of firm characteristics on stock returns varies across the individual firms’ liquidity sensitivity and the aggregate market liquidity conditions.JEL Classification: G11, G12, G14, G15

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11 citations

Cites background from "Investor sentiment, risk factors an..."

...…equity, momentum and liquidity in both developed and emerging stock markets for the determination of cross section of expected stock returns (Dash and Mahakud 2012; Fama and French 1996, 2012; Griffin 2002; Her et al. 2004; Keene and Peterson 2007; Lam and Tam 2011; Lischewski and Voronkova…...
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...Moreover, the available literature recognises the empirical validation of systematic risk factors with respect to market, size, book-to-market equity, momentum and liquidity in both developed and emerging stock markets for the determination of cross section of expected stock returns (Dash and Mahakud 2012; Fama and French 1996, 2012; Griffin 2002; Her et al. 2004; Keene and Peterson 2007; Lam and Tam 2011; Lischewski and Voronkova 2012; Sehgal and Jain 2011)....
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References

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Book Chapter•DOI•

Prospect theory: an analysis of decision under risk

[...]

Daniel Kahneman¹, Amos Tversky•Institutions (1)

University of British Columbia¹

01 Mar 1979-Econometrica

TL;DR: In this paper, the authors present a critique of expected utility theory as a descriptive model of decision making under risk, and develop an alternative model, called prospect theory, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights.

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Abstract: This paper presents a critique of expected utility theory as a descriptive model of decision making under risk, and develops an alternative model, called prospect theory. Choices among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory. In particular, people underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty. This tendency, called the certainty effect, contributes to risk aversion in choices involving sure gains and to risk seeking in choices involving sure losses. In addition, people generally discard components that are shared by all prospects under consideration. This tendency, called the isolation effect, leads to inconsistent preferences when the same choice is presented in different forms. An alternative theory of choice is developed, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights. The value function is normally concave for gains, commonly convex for losses, and is generally steeper for losses than for gains. Decision weights are generally lower than the corresponding probabilities, except in the range of low prob- abilities. Overweighting of low probabilities may contribute to the attractiveness of both insurance and gambling. EXPECTED UTILITY THEORY has dominated the analysis of decision making under risk. It has been generally accepted as a normative model of rational choice (24), and widely applied as a descriptive model of economic behavior, e.g. (15, 4). Thus, it is assumed that all reasonable people would wish to obey the axioms of the theory (47, 36), and that most people actually do, most of the time. The present paper describes several classes of choice problems in which preferences systematically violate the axioms of expected utility theory. In the light of these observations we argue that utility theory, as it is commonly interpreted and applied, is not an adequate descriptive model and we propose an alternative account of choice under risk. 2. CRITIQUE

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35,067 citations

"Investor sentiment, risk factors an..." refers background in this paper

...(Kahneman and Tversky, 1979), and limited arbitrage in determining stock prices (Brown and Cliff, 2005; Shleifer and Vishny, 1997)....
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Journal Article•DOI•

Prospect theory: analysis of decision under risk

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Daniel Kahneman, Amos Tversky

01 Jan 1979-Econometrica

27,773 citations

Journal Article•DOI•

Common risk factors in the returns on stocks and bonds

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Eugene F. Fama¹, Kenneth R. French¹•Institutions (1)

University of Chicago¹

01 Feb 1993-Journal of Financial Economics

TL;DR: In this article, the authors identify five common risk factors in the returns on stocks and bonds, including three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity.

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24,874 citations

"Investor sentiment, risk factors an..." refers background in this paper

...In recent years, following the theoretical argument of multifactor model specification (Merton, 1973; Ross, 1976) and motivated with the characteristic based risk pricing, the three factor (Fama and French, 1993), and four factor model (Carhart, 1997) have been widely debated and acclaimed in asset pricing literature to explain the cross section of average stock returns....
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A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix

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Whitney K. Newey, Kenneth D. West

01 May 1987-Econometrica

TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.

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Abstract: This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.

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18,117 citations

Journal Article•DOI•

Capital asset prices: a theory of market equilibrium under conditions of risk*

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William F. Sharpe

01 Sep 1964-Journal of Finance

TL;DR: In this paper, the authors present a body of positive microeconomic theory dealing with conditions of risk, which can be used to predict the behavior of capital marcets under certain conditions.

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Abstract: One of the problems which has plagued thouse attempting to predict the behavior of capital marcets is the absence of a body of positive of microeconomic theory dealing with conditions of risk/ Althuogh many usefull insights can be obtaine from the traditional model of investment under conditions of certainty, the pervasive influense of risk in finansial transactions has forced those working in this area to adobt models of price behavior which are little more than assertions. A typical classroom explanation of the determinationof capital asset prices, for example, usually begins with a carefull and relatively rigorous description of the process through which individuals preferences and phisical relationship to determine an equilibrium pure interest rate. This is generally followed by the assertion that somehow a market risk-premium is also determined, with the prices of asset adjusting accordingly to account for differences of their risk.

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17,922 citations