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The purpose of this paper is to investigate investor behavior under two broad categories, market-wide sentiment and herding.

Using a dynamic factor model, that extracts distinct latent factors representing fluctuations in asset returns due to changes in fundamentals as well as investors’ sentiments, the paper investigates the impact of investor behavior on asset pricing.

Consistent with the literature, the results suggest that the behavioral factors play a significant role in explaining variation in the asset prices. However, the degree of influence depends on the nature of the stocks or portfolios. The findings conform to the hypothesis that behavioral factors play a more important role in explaining the price movements of high and medium valued stocks than those of smaller valued stocks. Further, the behavioral factors also exhibit high auto-correlation, depicting the pervasive nature of such factors, and proving that information cascades and other behavioral mechanisms propagate over a period of time leading to bubbles and market crashes. Finally, since herding is often associated with market volatility, the authors test the hypothesis using two measures of volatility and the result shows positive significant associations between them as suggested in the literature.

The paper presents a dynamic factor model to study the impact of investor behavior on asset returns using a conventional three factors model with behavioral factors. A factor model is proposed to extract distinct latent factors representing fluctuations in asset returns due to changes in fundamentals as well as investors’ sentiments. The study investigates investor behavior under two broad categories, market-wide sentiment and herding. Consistent with the literature, the results suggest that the behavioral factors play a significant role in explaining variation in the asset prices. However, the degree of influence depends on the nature of the stocks or portfolios. The findings conform to the hypothesis that behavioral factors play a more important role in explaining the price movements of high and medium valued stocks than those of smaller valued stocks. Further, the behavioral factors also exhibit high auto-correlation, depicting the pervasive nature of such factors, and proving that information cascades and other behavioral mechanisms propagate over a period of time leading to bubbles and market crashes.

The objective of this paper is to investigate the role of information asymmetry in the equity selling mechanisms chosen by the firms from an important emerging market, India. Specifically, the authors look into the choice between the two most popular mechanisms of equity issues – rights issue and private placement of equity.

This study introduces three analyst specific variables as proxies of information asymmetry as the conventional proxies are fraught with several disadvantages. First, the paper tests the choice between rights issue and private placement using a binary logistic model. In the second approach the authors use rights issue and segregate the private placements into preferential allotments and qualified institutional placements and test the impact of information asymmetry using a multinomial logistic regression.

The outcome of this empirical exercise shows that only those firms facing lesser information problems choose rights issue of equity. Private placements are chosen by firms facing higher information problems to circumvent information costs. The results remain invariant even after segregating the qualified institutional placements from private equity placement as the firms with information disadvantage choose to place equity privately.

In contrast to the conventional studies that focus on the debt-equity framework, the authors argue that the impact of information asymmetry is applicable even at disaggregated levels of equity selling mechanism.

The purpose of this paper is to investigate the role of information asymmetry in the equity issue decision of two categories of Indian firms with distinct levels of information asymmetry – levered firms and unlevered firms.

This paper proposes a novel empirical approach to compare these two categories of firms. Levered firms exposed to the debt markets are under the scrutiny of lenders, reducing their information asymmetry problems. On the other hand, unlevered firms, which are smaller firms with fewer tangible assets and no credit history suffers more information problems. The authors use a propensity score matching method to identify firms that share similar firm-specific characteristics in these groups and compare equity issues to analyze the impact of information asymmetry.

The results show that information asymmetry plays a key role in the equity issue decision of Indian firms. Additionally, the authors find that the trends and characteristics of low-leverage (LL) firms in India are comparable to the LL from developed economies, which is consistent with the findings that they face more information problems.

Unlike the conventional approach of using proxy variables to capture information asymmetry, this study uses a novel framework where the authors compare the equity issue decision of similar firms in two categories with different degrees of information asymmetry.

The purpose of this study is to empirically examine the presence of herding behavior of Indian investors using daily sample data drawn from the Standard and Poor's (S&P) Bombay Stock Exchange-500 Index over the period 2007–2018.

The study employs the model proposed by Chang et al. (2000), taking stock return dispersion as a measure to capture herding. The empirical results demonstrate the absence of herding behavior in all market states, that is, normal, up and down market conditions for the overall period.

Contrastingly, the study found negative herding behavior, which underlines that individuals are taking the decision away from the market consensus. The subperiod analysis corroborates the negative herding behavior. The results remain invariant across large, mid and small-capitalization firms except in one year, that is, 2009 for small firms. While using liquidity and sentiment as variables to examine herding, the study finds some evidence of herding behavior for high market liquidity state and sentiment. The findings of negative herding shed new light on herding behavior in the Indian stock market.

This pattern of behavior may indicate irrationality of investor behavior and the presence of noise traders who mistrust market-wide information. Behavioral factors such as overconfidence may explain this pattern of behavior.

The purpose of this paper is to examine the capital structure determinants and speed of adjustment (SOA) toward the target capital structure of firms.

The study has used the generalized method of moments (GMM) model and two-stage least squares (TSLS) to the panel data of 3,310 Indian firms, from January 2000 to March 2018, to determine the adjustment speed toward target capital structure. Further, the study employed a fully modified ordinary least square technique to shed light on the dynamic nature of the adjustment process.

The results of the GMM estimations indicate that Indian firms are adjusting their capital structure toward the target rate of 10.38 percent per year. Similarly, the findings of TSLS estimate specify a SOA of 15.49 percent per year. The low adjustment speed suggests the prevalence of higher adjustment costs of Indian firms.

Future research can be undertaken by including certain macroeconomic factors such as GDP, inflation and the interest rate, which also affect the SOA since firms are pretentious by market conditions while designing capital structure for firms.

In the current financial and regulatory set-up when there are frequent perturbations in the capital market, the study will be valuable for regulators, firms and academicians. The work would enable the concerned stakeholders to manage their scare resources and capital effectively by a better way to make informed decisions. It will facilitate managers of young companies to identify and regulate the factors that are more pertinent for them to make flexible financial decisions concerning the capital structure.

The study amplifies on previous studies and provides new insights on the speed of the adjustment process of Indian firms, helping to modify and refine their capital structures toward the optimum capital structure. This will not only enhance the financial flexibility in the capital structure of Indian corporates but also be of great value to the policymakers and other stakeholders.