Saumya Ranjan Dash

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

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...

Conditional multifactor asset pricing model and market anomalies

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...

Investor Sentiment and Stock Return: Do Industries Matter?

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. JEL Classification: GI,G12,G14

Market anomalies, asset pricing models, and stock returns: evidence from the Indian stock market

Purpose – This paper aims to investigate whether the use of conditional and unconditional Fama and French (1993) three-factor and Carhart (1997) four-factor asset pricing models (APMs) captures the role of asset pricing anomalies in the context of emerging stock market like India. Design/methodology/approach – The first step time series regression approach has been used to drive the risk-adjusted returns of individual securities. For examining the predictability of firm characteristics or asset pricing anomalies on the risk-adjusted returns of individual securities, the panel data estimation technique has been used. Findings – Fama and French (1993) three-factor and Carhart (1997) four-factor model in their unconditional specifications capture the impact of book-to-market price and liquidity effects completely. When alternative APMs in their conditional specifications are tested, the importance of medium- and long-term momentum effects has been captured to a greater extent. The size, market leverage and s...

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

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

Investor Sentiment and Stock Price: Evidence from India

The impact of investor sentiment on stock market price has been a subject of long standing interest to both economists and practitioners. Following the theoretical argument of behavioral asset pricing, recent literature confirms the possible linkage between the aggregate investor sentiment and stock returns. In this paper we examine the causal relationship between investor sentiment index constructed from various market related implicit proxies, and aggregate stock market indices such as BSE sensex and NSE Nifty indices. The Johansen co-integration test is applied to measure the long-term relationship between the sentiment index and market indices and Error Correction Method has been used to check the short-term relationship between the two variables. Granger causality test is used to check the causal relationship between them. Our results suggest that, given the evidence of comovements of sentiment and market index there is significant long-run and short-run relationship between the two indices. Consistent with the existing literature which suggest that the sentiment effect is a short-run phenomena, our findings gives an indication that long term investment strategy can effectively mitigate the sentiment risk. The results for causality test suggest that there exist a unidirectional causal relationship between the sentiment index and market indices.

Does Sentiment Risk Persist as Priced Risk Factor? A Multifactor Approach for Stock Return

Much of the academic debate has gone in to exploring the better asset pricing model that can explain the quantification of the trade-off between risk and expected return for the cross section of stock return. Nevertheless this intimidating task becomes more pragmatic given the market structure of emerging markets, liquidity effects, market inefficiency, and more significantly the presence of inherent imperfect rationality or sentiment. The basic objective of this paper is to evaluate the pricing implication of unconditional five factor model to explain the cross sectional stock return behaviour in the context of Indian stock market. Our analysis also aims to examine the pricing nature of aggregate market wide sentiment risk in the presence of other risk factors. We employ 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. Our empirical results show that given the multidimensional nature of risk the choice of a five factor model is apparently persuasive for consideration in investment decisions. However, inconsistent with prior literature book-to-market equity fails to explain the average return in case of large stocks, and pricing evidence of momentum profits fades in case of winner stocks and momentum strategy retains its value only for the sell side transactions i.e., loser portfolios. With the presence of liquidity factor in the five factor model specification, the results suggest that liquidity is priced and explains a cross sectional variation in stock returns. Our results also suggest that it is naive to argue for the universal pricing implication of sentiment risk in a multifactor model framework, and market wide risk factors resume their importance as rational source of priced risk.