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Starting in the 1980s, financial liberalization and technological developments have enabled individual investors to participate in financial markets and carry out easy transactions. With these developments, academics began to wonder how the individual investors decide to invest and what factors affect these decisions.

According to traditional finance theory, it is suggested that markets are efficient and investors show rational behaviors in their financial purchasing decisions. However, in many studies conducted in recent years, it was determined that investors included emotional elements as well as rational elements in their decision-making process and therefore exhibited irrational behaviors by believing rumors instead of real information. It is thought that many factors such as personal characteristics, psychological factors, demographic and socio-economic factors play a role in the behavior of investors in purchasing a financial product.

In this study, the importance of herd behavior, which is one of the psychological factors that play a very important role in financial markets, on financial product purchasing process is examined in the light of the behavioral finance theory. It is thought that information included in the study will be useful for researchers who want to study herd behavior and for those who are interested in the subject.

Our study focuses on analyzing the trading behaviour of the investors who invest in these currencies to review their trading patterns which may help us to understand the price formation of cryptocurrencies in this market.

We used Chang et al. (2000) measure to calculate herding that is based on cross-section absolute dispersion of stock returns (CSAD). We further analyse the nature of the same in different market regimes, that is up market, down market, high volatile market, low volatile market etc.

Applying different methodologies both static and time varying, we find that herding is pronounced when the market is either passing through stress or has become highly volatile. Anti-herding is found in a less volatile market or in a bullish market.

Our results are also helpful for the policy makers in designing stricter regulations to provide safe investment environment to the investors.

Our study in an extension of the literature in same direction and contribute in numerous ways. As the number of digital currencies is growing day by day and we have around 2,200 digital currencies trading across the world, we increased our sample size up to 100 most traded currencies. While majority of the studies cover the period 2015–2018, our study comprises the largest sample size starting from August 2013 to April 2019. We use the static model to find herding and simultaneously try to detect herding under different market regimes: up market and down market.

This chapter examines the existence of dynamic herding behavior by Tunisian investors in the Tunisia stock market during the revolution period of 2011–2013. The sample covers all Tunindex daily returns as a proxy for the Tunisia stock exchange index over the period 2007–2018. The author modifies the cross-sectional absolute deviation model to include all market conditions (bull and bear markets) and the geopolitical crisis effect corresponding to the Tunisian Jasmine revolution during 2011–2013, and show that herding is indeed not present in the Tunisia stock market including during its turmoil periods. These findings imply that the Tunisian emerging financial market became more vulnerable to adverse herding behavior after the revolution. There is also a clear implication for capitalist firms and angel investors in Tunisia that adverse herding behavior tends to exist on days of higher uncertainty and information asymmetry.

Introduction – Markowitz (1952) argues that individuals act rationally in their financial decisions. In contrast, Kahneman and Tversky (1979) claim that the psychological characteristics of people significantly affect financial decisions. In making these decisions, factors such as age, gender, and educational status may have an impact.

Purpose – The purpose of this study is to determine whether financial literacy has an impact on individuals’ cognitive biases related to financial investments.

Methodology – A sample of 444 individuals were surveyed.

Findings – In the results of study (1) it was determined that financial literacy leads to differences in cognitive biases; and (2) cognitive biases of individuals who do not receive finance education are different from individuals who receive finance education and professionals in the business world. The findings indicate that the increase in the level of financial literacy of individuals will reduce the cognitive biases and heuristics, and therefore will have a positive effect on the investor behavior in financial markets.

During the Greenspan‐Bernanke era, the responses of Federal Reserve officials to financial crises resulted in an extraordinary involvement of the US central bank in the non‐banking financial sector. The purpose of this paper is to examine the informal and evolving conceptual framework that allows Federal Reserve officials to pursue a strategy of “constrained discretion” in responding to financial disturbances.

Behavioural economics relies on designed psychological and economic experiments to predict behavioural biases at the group level. As an analogue applicable to understanding biases in the intuitive judgments of individual policymakers, a naïve behavioural economics approach relies on intuitive or naive psychology and the interpretation of historical events as natural experiments to explain why intuitive judgments of Federal Reserve officials will contain biases.

Under the Greenspan‐Bernanke conceptual framework, Federal Reserve officials exercise “constrained discretion” in responding to disturbances arising from macro structural changes in the financial sector. The two key concepts are the Greenspan‐Bernanke doctrine on how the Federal Reserve officials respond to financial asset price bubbles and their collapses, and Bernanke's financial accelerator. Several examples are cited in which policy errors made by Alan Greenspan were attributable to identifiable biases in his intuitive judgment. In addition, Bernanke's response to the financial crisis of 2007‐2009 was based on his interpretation of the Great Depression as a natural experiment. But that interpretation was heavily biased by the influence of Milton Friedman on Bernanke's intuitive judgment. While Federal Reserve officials will need to exercise discretionary judgment in responding to financial crises, the potential for errors due to biases in that judgment can be reduced through regulatory reforms that lessen the potential for financial crises to occur.

While quantitative analyses of the effects of the Federal Reserve's actions on non‐bank financial institutions and the financial markets are ongoing, little attention has been given to the psychological aspects of the intuitive judgment that influences the discretionary decisions of the policymakers.

Purpose – Are members of socially dominant groups aware of the privileges they enjoy? We address this question by applying the notion of hypocognition to social privilege. Hypocognition is defined as lacking a rich cognitive or linguistic representation (i.e., a schema) of a concept in question. By social privilege, we refer to advantages that members of dominant social groups enjoy because of their group membership. We argue that such group members are hypocognitive of the privilege they enjoy. They have little cognitive representation of it. As a consequence, their social advantage is invisible to them.

Approach – We provide a narrative review of recent empirical work demonstrating and explaining this lack of expertise and knowledge in socially dominant groups (e.g., White People, men) about discrimination and disadvantage encountered by other groups (e.g., Black People, Asian Americans, women), relative what members of those other groups know.

Findings – This lack of expertise or knowledge is revealed by classic cognitive psychological measures. Relative to members of other groups, social dominant group members generate fewer examples of discrimination that other groups confront, remember fewer instances after being presented a list of them, and are slower to respond when classifying whether these examples are discriminatory.

Social Implications – These classic measures of cognitive expertise about social privilege predict social attitude differences between social groups, specifically whether people perceive the existence of social privilege as well as believe discrimination still exists in contemporary society. Hypocognition of social privilege also carries implications for informal interventions (e.g., acting “colorblind”) that are popularly discussed.

The purpose of this paper is to investigate the impact of factor-based trading strategies on pricing and volume.

The authors employ a regression discontinuity approach to identify abnormalities in volume or pricing around expected portfolio changes. In addition, the authors characterize more granular effects on pricing and volume as a result of portfolio re-classification through Fama and Macbeth (1973) regressions.

The authors find that firms which are predicted to transfer among the factor portfolios of Fama and French (1993) exhibit strong and statistically significant short-term variation in stock price and volume. Short-term returns around the cutoff values comprising SMB and HML tend to be temporarily high if the firm is predicted to move into a long component of a factor-mimicking portfolio, and temporarily low if moving into a short component. Similar results are apparent when examining movement in and out of the 25 size and book-to-market sorted test asset portfolios.

The use of portfolio strategies formulated on the basis of sorting procedures, while once upon a time a niche market in the portfolio management industry, is now ubiquitous. The results of this study raise interesting methodological questions about the pricing implications arising from these common methodologies.

This study makes a number of contributions. First, it contributes to the idea that the publication or dissemination of trading strategies or – more generally – common portfolio sorting methods, leads to effects on pricing and volume through commonly motivated trading pressure. In other words, recipe-like discoveries of advantageous trading strategies lead to a synthetic creation of demand. Second, by noting that a lot of factor-focused trading activity begins around July and August of each year, the study relates to existing literature which documents seasonal variation in stock returns and volume. The findings raise questions about what guides institutional investors’ portfolio allocation decisions and whether these are optimal in aggregate.