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The purpose of this paper is to capture the presence and impact of optimism in the Indian equity market.

The data set comprises the daily values of the Nifty 50 index, index options and Treasury-bill index for a period of five years (2006-2011). The focus of this paper is two pronged. It first investigates the presence of optimism (pessimism) using the pricing kernel technique suggested by Barone-Adesi et al. (2012). Second, it tries to analyze the relationship of this bias with stock market indicators like risk premium, market return and volatility using time series regression.

The findings indicate that the Indian equity market has been predominantly pessimistic from the period 2006 to 2011. The interaction of this bias with market indicators also unveils some interesting insights. The study shows that high past volatility can lead to pessimism in the Indian equity market and vice versa. It further explores that when the investors are rational, their risk and return relationship is positive while it tends to be negative when they are irrational. The impact of investors’ irrationalities on asset valuation has also been accounted by Brown and Cliff (2005).

The findings of the paper have significant implications for fund managers and asset management companies. It is recommended that they should try to identify behavioral biases in their clients before designing their portfolios.

This study is one of the very few attempts to capture the presence and impact optimism (pessimism) in the Indian equity market.

The purpose of this paper is to examine the presence the behavioral biases in Indian investors specifically, overconfidence, excessive optimism (pessimism), herd behavior and the disposition effect. It further investigates the role of demographics and investor sophistication in influencing the biases. Finally, it reveals which bias is most prevalent in the Indian context.

For this purpose, a survey has been conducted on the investors of the Delhi/NCR area. The data have been collected with the help of a structured questionnaire that is analyzed with the help of relevant statistical tools.

The survey evidence shows that behavioral biases are dependent on investors’ demographics and their trading sophistication with highest influencing factors being age, profession and trading frequency. Each bias corresponds to a specific set of investor characteristics and overconfidence comes out to be the most important bias in the Indian context.

The potential limitations of the present survey can be ascribed to socially desirable responses and their difference with actual market behavior. Further, due to time and resource constraint, the data set is limited to investors of only Delhi/NCR.

This study is most relevant for financial advisors, as it facilitates them in gaining a better understanding of their clients’ psychology. It can aid them in developing behaviorally modified portfolio, which best suits their clients’ predisposition.

The paper gives a unique insight on the investors’ profile corresponding to each bias under consideration. It not only updates the evidence on behavioral biases but also highlights which bias is the most influential in the Indian context.

The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is general market-wide sentiments, while the second is biased approaches toward specific assets.

To achieve the goal, the authors conducted a multi-step analysis of stock returns and constructed complex sentiment indices that reflect the optimism or pessimism of stock market participants. The authors used panel regression with fixed effects and a sample of the US stock market to improve the explanatory power of the three-factor models.

The analysis showed that both market-level and stock-level sentiments have significant contributions, although they are not equal. The impact of stock-level sentiments is more profound than market-level sentiments, suggesting that neglecting the stock-level sentiment proxies in asset valuation models may lead to severe deficiencies.

In contrast to previous studies, the authors propose that investor sentiments should be measured using a multi-level factor approach rather than a single-factor approach. The authors identified two distinct levels of investor sentiment: general market-wide sentiments and individual stock-specific sentiments.

This study aims to critically review recent contributions to the methodology of financial economics and discuss how they relate to one another and directions for further research.

A critical review of recent literature on new methodologies for financial economics.

Recent books have made important contributions to the study of financial economics. They suggest new approaches that include an emphasis on radical uncertainty, adaptive markets, agent-based modeling and narrative economics, as well as extensions of behavioral finance to include concepts such as diagnostic expectations. Many of these contributions can be seen more as complements than substitutes and provide fruitful directions for further research. Efficient markets can be seen as holding under particular circumstances. A major them of most of these contributions is that the study of financial crises and other aspects of financial economics requires the use of multiple theories and approaches. No one approach will be sufficient.

There are great opportunities for further research in financial economics making use of these new approaches.

These recent contributions can be quite useful for improved analysis by researchers, private participants in the financial sector and macroeconomic and regulatory officials.

Provides an introduction to these new approaches and highlights fruitful areas for their extensions and applications.

Introduction: According to the effective market hypothesis, investors act rationally when making an investment decision. The hypothesis assumes that investors invest in a way that maximizes their returns, taking into account the new information received. If the information released on the market is interpreted in the same way by all investors, no investor would be able to earn above the market. This hypothesis is valid in case of efficient markets. In the event that investors show irrational behavior to the information released on the market, the markets move away from efficiency. Overreaction behavior is one of the non-rational behaviors of investors. Overreaction behavior involves investors overreacting by misinterpreting the new information released to the market. According to De Bondt and Thaler’s (1985), overreaction hypothesis in the event that investors overreact to the news coming to the market, after a period the false evaluation, the price of the security is corrected with the reversal movement, without the need of any positive or negative information. Aim: The purpose of this study is to examine investors’ overreaction behavior in mergers and acquisitions. For this purpose, overreaction behavior was analyzed for companies whose stocks are traded on the Borsa Istanbul, which were involved in mergers or acquisitions. Method: In the study, companies that made mergers and acquisitions for the period 2007–2017 were determined, and abnormal returns and cumulative abnormal returns were calculated by using monthly closing price data of these companies. Moreover, whether investors overreact to the merger and acquisition decision is examined separately for one-, three- and five-year periods. Findings: As a result of the research, it has been observed that there is a reverse return for one-, three-, and five-year periods. However, it has been determined that the overreaction hypothesis is valid for only one year.

The main purpose of this study is to investigate the effect of investor sentiment on accounting conservatism in listed companies in the Tehran Stock Exchange (TSE).

In this paper, two models of Ball and Shivakumar (2006) and Basu (1997) have been used for measuring conditional conservatism in accounting. To measure investor sentiment, the author uses the Baker and Wurgler (2006, 2007) index. The research sample consists of 1,820 observations and 182 firms listed on TSE over a ten-year period between 2011 and 2020. This study uses panel data and multivariate regression analysis to test it hypotheses.

Consistent with this hypothesis that accounting conservatism will increase with investor sentiment, the results showed that Iranian firms recognize economic losses and bad news in a more timely manner during high sentiment periods than during low sentiment periods. This implies that Iranian managers recognize economic losses and bad news in earnings in a more timely manner during periods of high investor sentiment.

This finding provides significant evidence for investors and financial reporting standard-setters in Iran because by removing accounting conservatism from the conceptual framework, managers are not able to present conservative financial reports, and this can intensify the negative impact of investors sentiment in the Iranian capital market. Managers of Iranian companies can reduce information asymmetry and increase capital market efficiency by accelerating the disclosure of bad news. Thus, managers can strategically recognize losses and prevent investors from making emotional decisions that reduce their wealth.

To the best of the authors’ knowledge, this is the first study to empirically examine the impact of investor sentiment on accounting conservatism in a developing market called Iran. This study contributes to the corporate disclosure literature. Also, the result of this study contributes to standard-setters of accounting standards to improve the mandatory disclosure literature on more conservative accounting earnings.

This paper aims to analyze the effects of investors’ sentiment, return and risk series on one to another of selected exchange rates. The empirical analysis consists of a time-varying inter-dependence between the observed variables, with the focus on spillovers between the variables.

Monthly data on the index Sentix, exchange rates EUR–USD, EUR–CHF and EUR–JPY are analyzed from February 2003 to December 2019. The applied methodology consists of vector autoregression models (VAR) with Diebold and Yilmaz (2009, 2011) spillover indices.

The results of the empirical research indicate that using static analysis could result in misleading conclusions, with dynamic analysis indicating that the financial of 2007-2008 and specific negative events increase the spillovers of shock between the observed variables for all three exchange rates. The sources of shocks in the model change over time because of variables changing their positions being net emitters and net receivers of shocks.

The shortfalls of this study include using the monthly data frequency, as this was available for the authors, namely, investors are interested to obtain new information on a weekly and daily basis, not only monthly. However, at the time of writing this research, we could obtain only monthly data.

As the obtained results are in line with previous literature and were found to be robust, there exists the potential to use such analysis in the future when forecasting risk and return series for portfolio management purposes. Thus, a basic comparison was made regarding the investment strategies, which were based on the results from the estimation. It was shown that using information about shock spillovers could result in strategies that can obtain better portfolio value over time compared to basic benchmark strategies.

First, this paper allows for the spillovers of shocks in variables within the VAR models in all directions. Second, a dynamic analysis is included in the study. Third, the mentioned spillover indices are included in the study as well.

This study creates a measure of investor sentiment directly from retail trader activity to identify misvaluation and to examine the link between sentiment and subsequent returns.

Using investor reports from a large discount brokerage that include measures of activity such as net buying, net new accounts and net new assets, this study creates a measure of retail trader sentiment using principal components. This study examines the relation between sentiment and returns through conditional mean and regression analyses.

Retail sentiment activity coincides with aggregate Google Trends search data and firms with the greatest sensitivity to retail sentiment tend to be small, young and volatile. Periods of high retail sentiment precede poor subsequent market returns. Cross-sectional results detail the strongest impact on subsequent returns within difficult to value or difficult to arbitrage firms.

This study links a rich measure of retail trader activity to subsequent market and cross-sectional returns. These results deepen our understanding of noise trader risk and aggregate investor sentiment.

FOR the purposes of this paper the prefixes hyper and super, which, etymologically, have the same essential signification, are given different meanings: to the first a sense of distance, and to the second a sense of altitude.

Sees the objective of teaching financial management to be to help managers and potential managers to make sensible investment and financing decisions. Acknowledges that financial theory teaches that investment and financing decisions should be based on cash flow and risk. Provides information on payback period; return on capital employed, earnings per share effect, working capital, profit planning, standard costing, financial statement planning and ratio analysis. Seeks to combine the practical rules of thumb of the traditionalists with the ideas of the financial theorists to form a balanced approach to practical financial management for MBA students, financial managers and undergraduates.