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This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

The purpose of this paper is to empirically test the relationship between investors’ rationality and behavioural biases like self-attribution, overconfidence.

The study applies structural equation modelling to understand whether individual investors, besides being rational, are subjected to self-attribution bias and overconfidence bias.

The study shows the empirical evidence in the support of behavioural biases like self-attribution and overconfidence existing besides investors’ rationality. Moreover, there is a statistically significant positive covariance found between self-attribution and overconfidence, implying that an increase/decrease in self-attribution results in the increase/decrease in overconfidence and vice versa. It is also observed that the personal characteristics of an investor such as gender, age, occupation, annual income and their trading experience have an impact on behavioural biases.

The study focused on rational decision making, self-attribution and overconfidence biases using primary data. Further studies can be encouraged to test the existence of behavioural biases based on both market level and individual account data simultaneously.

Insights from the study suggest that the investors should perform a post-analysis of each investment, so that they become aware of past behavioural mistakes and stop continuing the same. This might help investors to minimise the negative impact of self-attribution and overconfidence on their expected utility.

To the best of the authors’ knowledge, this is the first study to examine the relationship among investors’ rationality, self-attribution and overconfidence in the Indian context using a comprehensive survey.

The main objective of this paper is to analyze the dynamic volatility spillovers between the investor's behavioral biases, the macroeconomic instability factors and the value at risk of the US Fintech stock market before and during the COVID-19 pandemic.

The authors used the methodologies proposed by Diebold and Yilmaz (2012) and the wavelet approach.

The wavelet coherence results show that during the COVID-19 period, there was a strong co-movement among value at risk and each selected variables in the medium-run and the long-run scales. Diebold and Yilmaz's (2012) method proved that the total connectedness index raised significantly during the COVID-19 period. Moreover, the overconfidence bias and the financial stress index are the net transmitters, while the value at risk and herding behavior variables are the net receivers.

This study offers some important implications for investors and policymakers to explain the impact of the COVID-19 pandemic on the risk of Fintech industry.

The study findings might be useful for investors to better understand the time–frequency connectedness and the volatility spillover effects in the context of COVID-19 pandemic. Future research may deal with investors' ability of constructing portfolios with another alternative index like cryptocurrencies which seems to be a safer investment.

To the best of the authors' knowledge, this is the first study that relies on the continuous wavelet decomposition technique and spillover volatility to examine the connectedness between investor behavioral biases, uncertainty factors, and Value at Risk of US Fintech stock markets, while taking into account the recent COVID-19 pandemic.

The current study aims to investigate the impacts of two behavioral biases, namely, loss aversion and overconfidence on the performance of US companies. First, the impact of loss aversion on the economic performance of companies was assessed. Second, the impact of overconfidence on market performance was discussed.

This study used around 6,777 quarterly observations on the population of US-insured industrial and services companies over the 2006-2016 period. Ordinary least squares (OLS) regression in two panel data models were used to test the hypotheses formulated for the study.

It was documented that the loss-aversion bias negatively affects the economic performance of companies and this is achieved for both sectors. In contrast, the findings suggest that overconfidence positively affects market performance of industrial firms but negatively affects market performance in service firms. Further robust evidence was found that overconfidence bias seems to be dominant, and hence, investors may tend to be more overconfident rather than more loss-averse.

This research can be extended by focusing on the following question: What is the impact of the contradictory (positive and negative) effects of an investor's loss aversion and overconfidence on the US company performance in case of realization of a stock market crisis or stock market crash?

Research in the area of behavioral finance has demonstrated that investors exhibit irrational behavior while making investment decisions. Investor behavior usually deviates from logic and reason, and consequently, investors exhibit various behavioral biases which impact their investment decisions. The purpose of this paper is to rank the behavioral biases influencing the investment decision making of individual equity investors from the state of Punjab, India. This research would provide valuable insight into the different behavioral biases to investors and other participants of the capital market and help them in improving investment decisions.

The research is conducted on the individual equity investors of Punjab, India. Fuzzy analytic hierarchy process was applied to rank the factors influencing the decision making of individual equity investors of Punjab. The primary factors considered for the study are overconfidence bias, representative bias, anchoring bias, availability bias, regret aversion bias, loss aversion bias, mental accounting bias and herding bias.

The three most influential criteria were herding bias, loss aversion bias and overconfidence bias. The five most influential sub-criteria were “I readily sell shares that have increased in value (C61),” “News about the company (Newspapers, TV and magazines) affects my investment decision (C84),” “I invest each element of my investment portfolio separately (C71)” and “I usually hold loosing stock for long time, expecting trend reversal (C52).”

Although sample survey conducted in the present study was based on a limited sample selected from a particular area that truly represented the total population, it is considered as the limitation of this study.

The outcome of this research provides investors with a better understanding of behavioral biases that influence their decision making. This study provides them a guideline on different behavioral biases that they should consider while making investment decisions.

The research model is based on the available literature on behavioral finance and the research results and findings would add value to the existing knowledge base.

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

The objective of this paper is to explore how anchoring affects the dynamics of investor decision-making with regard to mutual funds and how this bias differs amongst gender and level of financial knowledge.

An experimental research design was adopted to uncover the relationship between the variables under study; this involved the use of a questionnaire with an embedded experiment. Data obtained from the study were analysed using Pearson's chi-square test and two-way analysis of variance.

The findings show that, overall, investors were prone to be significantly influenced by the anchoring bias. The study finds a strong, albeit not significant, association between participants' susceptibility to anchor and both gender and the level of financial knowledge of participants. Females were observed to be more likely to anchor than their male counterparts. Also, a higher level of financial knowledge did not help to reduce the possibility of anchoring; it rather increased it.

The findings of the study cannot be interpreted as suggesting causality as the study only tests for association between variables and not causality. Additionally, external validity cannot be fully established as a result of the quasi-experiment approach used.

The study adds to the body of knowledge on the influences of behavioural biases in the sub-region to make investors aware of their biases in order to minimise the influence of these biases on their investment decisions.

This study differs from earlier studies in that it analyses the presence of anchoring as influenced by a completely different set of variables (expertise and gender) and also does it within the context of an African country where there remains a paucity of research on behavioural finance.

The main purpose of this study is to investigate the investment choices' relationship with cognitive abilities, risk aversion, risky investment intentions, subjective financial literacy and objective financial literacy.

To examine the relationship, two investment choices were given to 256 subjects from Pakistan. Questionnaire had total 20 questions for measuring five variables. To review this nexus, discriminant analysis was used as to explore the depth of the nexus that is the ability of the variables to predict the investment choices.

This study establishes the findings that Investment choices are guided by risk aversion, risky investment intentions, financial literacy (subjective and objective) and cognitive abilities. The risk aversion has negative relation to investment choices and other variables depict positive relationship to with investment choices.

This study provides a new and useful understanding into the existing literature on investment choices. The results are significant as the cognitive abilities show a positive contribution to the investment choices. This is point of significance as the portfolio managers and advisors would get help in regards of advising investments as they are aware what factors impact the investment choices.

This study is novel in its nature to evaluate investment choices using the cognitive ability alongside risk attitudes and financial literacy.

This paper aims to review, systematize and integrate existing research on alternative investments. This study conducts performance analysis comprising production timeline, country-wise contributions, analysis of sources, affiliations, the geography of authors and citations of studies on alternative investments.

This study adopts a thematic and bibliometric analysis methodology on 570 papers identified from mainstream literature on alternative investments. This study provides an analysis of science mapping, including co-citation analysis, bibliometric coupling, word analysis and trending topics on alternative investments. In addition, the study presents thematic analysis by classifying existing studies into nine themes.

Alternative investments provide diversification benefits and play a critical role in portfolio construction, and the research on alternative investments has gained momentum in recent times. This study finds that hedge funds, private equity, artwork, collectibles, commodities, fine wine and venture capital have remained prominent themes in the field. Investments in cryptocurrencies are an emerging area in the research on alternative investments.

This study limits itself to the papers published in the area of finance and economics listed on the Scopus database.

This study provides quantitative bibliometric analysis and thematic analysis of the extant literature on alternative investments and identifies the areas that could be developed to advance research on alternative investments.