Search results

The purpose of this study is to investigate the impact of disputed tax litigation risk on firm performance and stock return behavior using a sample of Indian listed firms.

The authors use disputed tax liability, reported as a contingent liability by the listed firms, as a proxy for the disputed tax litigation risk. To examine the impact of disputed tax litigation risk on firm performance (measured by accounting and market-based measures), the empirical approach used in this study focusses on the panel estimation technique. A portfolio-based approach using alternative asset pricing models examines the cross-sectional return variation because of the influence of disputed tax litigation risk.

The results of this study show a negative relationship between firm performance measures and disputed tax litigation risk. Cross-sectional test results reveal that higher disputed tax litigation risk is associated with higher expected returns.

This study focusses on disputed tax reported under the heading of contingent liability as a proxy for litigation risk. The study will help investors and portfolio managers to consider disputed tax litigation risk as an important parameter in the evaluation of firm performance. This study will also help regulators to get feedback on tax related policies and improve the dispute resolution process.

This study adds to the existing literature on the relationship between litigation risk and firm performance. In the context of emerging market, this study is the first-of-its-kind study, which focusses on disputed tax as a litigation risk proxy and examines its possible impact on firm performance and stock return behavior.

The purpose of this paper is to use investor sentiment (IS) as a conditioning information variable for the cross-sectional return predictability tests of alternative asset pricing models (APMs).

Cross-sectional tests of alternative APMs in the linear beta representation and stochastic discount factor specifications, Fama and Macbeth and generalized method of moments techniques have been used.

Results reveal that IS as a conditioning information variable contains significant information for making the discount factors time varying. Model comparison test statistics suggests that among the alternative APMs, the conditional five-factor model (FFM) performs better.

Empirical analysis does not extend to the inclusion of the business-cycle conditioning information variables for the test of APMs.

The potential benefit of the conditional FFM can be leveraged upon for cost of capital determination, and mutual fund manager’s portfolio performance evaluation when the portfolio is heavily weighted with sentiment-sensitive hard to value and difficult to arbitrage stocks. During volatile and boom periods in stock markets the IS scaled conditional APMs may be useful for the fundamental value determination of sentiment-sensitive stocks.

This study extends available literature in the context of both developed and emerging equity markets by exploring the cross-sectional tests of conditional APMs using IS as the conditioning information variable. To the author’s knowledge, this is perhaps the first study that examines IS as conditioning information for the cross-sectional tests of alternative APMs.

This paper aims to investigate the moderating role of government policy interventions amid the early spread of novel coronavirus (COVID-19) (January–May 2020) on the investor sentiment and stock returns relationship.

This paper uses panel data from a sample of 53 countries to examine the impact of investor sentiment, measured by the financial and economic attitudes revealed by the search (FEARS) index (Da et al., 2015) on the stock return.

The moderating role of government policy response indices with the FEARS index on the global stock returns is further explored. This paper finds that government policy responses have a moderating role in the sentiment and stock returns relationship. The effect holds true even when countries are split based on five classifications, i.e. cultural distance, health standard, government effectiveness, social well-being and financial development. The results are robust to an alternative measure of pandemic search intensity, quantile regression and two measures of stock market activity, i.e. conditional volatility and exchange traded fund returns.

The sample period of this study encompasses the early spread phase (January–May 2020) of the novel COVID-19 spread.

This paper provides some early evidence on whether the government policy interventions are helpful to mitigate the impact of investor sentiment on the stock market. The paper also helps to shed better insights on the role of different country characteristics for the sentiment and stock return relationship.

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.

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.

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 short-term momentum effects still persist even in the case of alternative unconditional and conditional APMs.

The empirical analysis does not extend for different market scenarios like high and low volatile market or good and bad macroeconomic environment. Because of the constraint of data availability, the authors could not include certain important anomalies like net operating assets, change in gross profit margin, external equity and debt financing and idiosyncratic risk.

Although the active investment approach in stock market shares a common ground of semi-strong form of market efficiency hypothesis which also supports the presence of asset pricing anomalies, less empirical evidence has been explored in this regard to support or repute such belief of practitioners. Our empirical findings make an attempt in this regard to suggest certain anomaly-based trading strategy that can be followed for active portfolio management.

From an emerging market perspective, this paper provides out-of-sample empirical evidence toward the use of conditional Fama and French three-factor and Carhart four-factor APMs for the complete explanation of market anomalies. This approach retains its importance with respect to the comprehensiveness of analysis considering alternative APMs for capturing unique effects of market anomalies.

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.

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.

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.

Constrained upon the data availability, certain market anomalies and conditioning variables cannot be included in the analysis.

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.

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.

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.

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.

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 naïve to argue for the universal pricing implication of sentiment risk in a multifactor model framework.

The test assets portfolios are not segregated as per any industry criteria.

Investment managers can use a contrarian investment strategy, for the stocks that are hard to value and riskier to arbitrage to gain excess return when the market follows a downward trend.

This makes the first attempt towards the investigation of the impact of the sentiment risk on cross sectional return variation from an emerging market perspective on such a diversified and large test asset portfolios. The paper has extended the available literature by investigating the impact of sentiment risk after controlling the liquidity risk factor in a multifactor specification. This measure of market wide irrational sentiment index is more comprehensive.