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This study investigates whether or not the short-selling behavioral bias of investors exists in the Korean stock market. We analyze how the weather bias related to climate factors affects short-selling traders, commonly known as informed traders. To do this we estimated the dynamic panel model using daily data and examined the relationship between market variables such as stock returns, short sale volume, non-short sale volume, total trading volume, and weather variables consisting of cloud cover and sunshine hours. This study shows that not only returns but also short selling volumes are all affected by weather factors. In the case of stock returns, both cloud cover and sunshine hours have a statistically significant impact on returns, and its sign is estimated to be inversely proportional to both factors. That is, we find that returns decrease on cloud days, but increase on sunny days. In terms of the trading behavior of the market participants, it is interesting to note that the trading volume decreases when the weather is blunted, But did not show any statistical significances. On the other hand, both the original and the seasonally adjusted weather factors of cloud cover have a statistically significant positive effect on the short-sale volume. This means that as the weather worsens, short-selling traders submit more orders, indicating the presence of behavioral bias.

Research draws the distinction between noise traders and informed traders. Research also documents market biases in equity returns due to cloud cover, a non‐informational (noise) event, showing that returns decrease on cloudy days. The purpose of this paper is to investigate the trading behaviour of short‐sellers, who are considered informed traders, conditioning on the level of cloudiness, and find an increase in short selling with the level of cloudiness. Additionally, the paper finds decreases in short selling the three days prior to a cloudy day (or series of cloudy days).

The authors replicate the weather anomaly in stock returns reported in the literature for the sample period, and then study the trading behaviour of short sellers conditioned on cloud cover. Additionally the authors treat cloud cover as an event and study short selling volume in the pre‐event window.

The paper finds an increase in short selling with the level of cloudiness. Additionally, the paper finds decreases in short selling, relative to the event day(s), in the three days prior to a cloudy day (or series of cloudy days).

The authors believe that they are the first to document that weather impacts short seller's trading behaviour. The authors argue that the results point towards a behavioural bias.

This research aims to explore and explain the determinants of irrational financial decision making, especially the day‐of‐the week anomaly, by using psychological approach.

As it is a conceptual paper, this research explores the psychological biases literature and links it to the day‐of‐the week anomaly. Using Ellis' ABC (Activating Event, Belief, and Consequences) Model, the authors survey and classify the stimulant as the occasion that stimulates the psychological biases of investors, and these psychological biases will bring a consequence in behaviour which is irrationality in weekend effect.

Adopting Ellis' ABC model, the paper constructs a theoretical framework that link the psychological biases and day‐of‐the week anomaly. The theoretical model is also given as a proposed model for future empirical research.

This paper contributes to research by giving the theoretical model and its framework. The latter, future research can examine the proposed psychological biases as the determinant of day‐of‐the week anomaly empirically.

This paper conceptually builds a framework and derives a proposed equation model linking the psychological biases (weather, moon, attention bias, heuristic bias, regret, and cognitive bias) to the day‐of‐the week anomaly.

The purpose of this paper is to study and describe several biases in investment decision-making through the review of research articles in the area of behavioral finance. It also includes some of the analytical and foundational work and how this has progressed over the years to make behavioral finance an established and specific area of study. The study includes behavioral patterns of individual investors, institutional investors and financial advisors.

The research papers are analyzed on the basis of searching the keywords related to behavioral finance on various published journals, conference proceedings, working papers and some other published books. These papers are collected over a period of year’s right from the time when the most introductory paper was published (1979) that contributed this area a basic foundation till the most recent papers (2016). These articles are segregated into biases wise, year-wise, country-wise and author wise. All research tools that have been used by authors related to primary and secondary data have also been included into our table.

A new era of understanding of human emotions, behavior and sentiments has been started which was earlier dominated by the study of financial markets. Moreover, this area is not only attracting the, attention of academicians but also of the various corporates, financial intermediaries and entrepreneurs thus adding to its importance. The study is more inclined toward the study of individual and institutional investors and financial advisors’ investors but the behavior of intermediaries through which some of them invest should be focused upon, narrowing down population into various variables, targeting the expanding economies to reap some unexplained theories. This study has identified 17 different types of biases and also summarized in the form of tables.

The study is based on some of the most recent findings to have a quick overview of the latest work carried out in this area. So far very few extensive review papers have been published to highlight the research work in the area of behavioral finance. This study will be helpful for new researches in this field and to identify the areas where possible work can be done.

Practical implication of the research is that companies, policymakers and issuers of securities can watch out of investors’ interest before issuing securities into the market.

Under the Social Implication, investors can recognize several behavioral biases, take sound investment decisions and can also minimize their risk.

The essence of this paper is the identification of 17 types of biases and the literature related to them. The study is based on both, the literature on investment decisions and the biases in investment decision-making. Such study is less prevalent in the developing country like India. This paper does not only focus on the basic principles of behavioral finance but also explain some emerging concepts and theories of behavioral finance. Thus, the paper generates interest in the readers to find the solutions to minimize the effect of biases in decision-making.

In the wake of climate change and its associated impact on firms' performance, this paper attempts to provide a piece of empirical evidence in support of the effect of weather conditions on the stock market performance.

Monthly time-series dataset and the fully modified ordinary least square (FMOLS) semi-parametric econometric technique are used to establish the effect of weather variables on stock market return.

This study finds that temperature and wind speed have a negative and statistically significant relationship with stock market performance. Likewise, humidity exhibits a negative relationship with stock market performance, albeit insignificant. The relevant stock market and macroeconomic control variables are statistically significant in addition to exhibiting their expected signs. The findings lend support to advocates of behavioural factors inclusion in asset pricing and decision-making.

For policy purposes, the authors recommend that traders, investors and stock exchange managers must take into consideration different weather conditions as they influence investors' behaviour, investment decisions, and consequently, the stock market performance.

To the best of the authors’ knowledge, this study provides the first empirical evidence of the nexus between disaggregated weather measures and stock market performance in Ghana. This study uses monthly data (which are very rare in the literature, especially for developing country studies) to provide empirical evidence that weather influences stock market performance.

This paper describes how financial professionals' behavioral biases influence their financial forecast and decision-making process. Most of the earlier studies are focused on well-developed financial markets, and little is researched about financial professionals, such as institutional investors, portfolio managers, investment advisors, financial analysts, etc., in emerging markets.

An expert-validated questionnaire measure four prominent behavioral biases and Indian financial professionals' rational decision-making process. The final sample consists of 274 valid responses using the purposive sampling technique. IBM SPSS and AMOS structural equation modeling (SEM) software are used to build measurement and structural models, multivariate analysis including regression, factor analysis, etc.

The results provide empirical insights into the relationship between behavioral biases and the decision-making process. The results suggest that the structural path model closely fits the sample data. The presence of behavioral biases indicates that financial professionals' forecasting and decision-making is not always rational but bounded rational or irrational due to these factors. Furthermore, these biases (except overconfidence bias) have a markedly significant and positive relationship with irrational decision-making.

It is critical to eradicate these psychological errors, but awareness and attentiveness toward behavioral biases may help financial professionals to make informed decisions. Investors can improve their portfolio decisions and investments by recognizing their judgment errors and focusing on specific investment strategies to mitigate the impact of these biases. It is necessary to incorporate behavioral insights while developing training techniques for financial professionals. Rules of thumb, visual tools, financial coaching and implementing social-cultural elements in training programs enable financial professionals to develop simple, engaging, appealing and customized approaches for their clients.

This novel study is the first of this kind of research that examines the relationship between financial professionals' behavioral biases and rational decision-making process. This study significantly and remarkably provides insights into irrationality in financial professionals' decision-making.

The purpose of this second of two companion papers is to further review the insights provided by experimental studies examining financial decisions and market behavior.

Focus is directed on those studies examining explicitly, or with direct implications for, the most robustly identified phenomena or stylized facts observed in behavioral finance. The themes for this second paper are biases, moods and emotions.

Experiments complement the findings from empirical studies in behavioral finance by avoiding some of the limitations or assumptions implicit in such studies.

The author synthesizes the valuable contribution made by experimental studies in extending the knowledge of how biases, moods and emotions influence the financial behavior of individuals, highlighting the role of experimental studies in policy design and intervention.

The purpose of this paper is to investigate the mediating effect of online reviewers' affect (ORA) on the relationship between weather and online review ratings (ORR).

The consumers' online review data were collected from the third-party restaurant website, and the weather data were obtained from the weather part of Chinese e-government website. SnowNLP was utilized to analyze sentiment and further extract ORA. Furthermore, the mediating effects of ORA on temperature and ORR, rain and ORR were explored separately using PROCESS 3 Macro Model 4, and the interaction effect of temperature and rain was tested through PROCESS 3 Macro Model 7.

The findings of this work demonstrate that ORA mediates the relationship between temperature and ORR and the relationship between rain and ORR. Besides directly leading to higher ORR, a higher temperature can bring about higher ORR by elevating ORA. On the other hand, little rain and heavy rain have a direct negative influence on ORR, and they can also lead people into a bad mood state, thus leading to lower ORR. Furthermore, temperature moderates the effect of rain on ORA. When the temperature is higher, the differences of ORA are larger between different types of rain than that of lower temperature.

This study appears to be the first to investigate the relationship among weather, ORA and ORR using online data. The results could help managers understand when consumers are more likely to provide negative eWOM under corresponding weather conditions and adopt appropriate strategies to improve ORR.

This paper forwards a conceptual model identifying some of the key sources of judgment error in individual environmental sensemaking. Recommendations are offered to mitigate some of these biasing dysfunctions and thereby improve the effectiveness of environmentally related business policy.

Theories of cognitive and behavioral sciences are reviewed and applied to create a conceptual model describing some of the key influences on individual sensemaking in regard to environmental risk and opportunity.

It is found that the model presented in this paper contributes to the literature of corporate social responsibility in explaining some of the heuristic phenomena that can lead to denial of a firm's negative environmental impact, or conversely, recognition of emerging opportunities arising from increasing societal concern for environmental integrity. Many environmental scientists believe denial is omnipresent in modern business and governmental organizations. In addition, because the model is grounded in well‐established theories of problematic heuristic bias, it helps identify “leverage points” where well‐designed interventions can be deployed to promote learning and improved decision making. The model helps the decision maker better understand and potentially influence ethical judgment because ethical decision making is conceived within the frame of bounded ethicality versus a less potent theory of intervention based upon espoused moral prescriptions.

Some important influences on environmental sensemaking are not emphasized in the model to include dimensions of individual personality, early childhood experiences, gender, religious background, etc. Rather, the emphasis here is placed upon relatively ubiquitous cognitive heuristics and other cognitive phenomena likely to influence many organizational decision makers.

This analysis and resulting conceptual model should help change agents, students, policy makers and business practitioners avoid predictable biases and sensemaking distortions and, in so doing, improve the firm's social responsibility profile and recognition of emerging business opportunities growing out of sustainability imperatives.

This paper participates in the debate on market efficiency and correct approach for asset pricing through a comprehensive review of literature in favor, as well as against the long held belief of market efficiency. The purpose of this paper is to understand emerging trends in behavioral finance and establish its future potential as a mainstream alternative theory of asset pricing.

The review and discussion of literature is mainly divided into three different sections that are –theories supporting efficient market hypothesis (EMH); studies providing evidences from the stock market on the failure of EMH and studies on behavioral finance, discussing separately investors’ behavioral biases keeping in mind their effect on stock prices; and providing empirical evidences on the effect of investor sentiment on stock prices.

The review of literature from both the point of views has helped in understanding the market efficiency issue and changing dynamics of asset pricing approach. This is achieved by highlighting the gaps in the concept of market efficiency and also suggesting how these gaps can be bridged with a superior approach such as behavioral finance. Through further discussion of emerging trends in behavioral finance, the paper also points out gaps and how these can be abridged, for behavioral finance to be accepted as a mainstream alternative approach to EMH.

This is an extensive and one of a kind study that discusses market efficiency through discussion of EMH and behavioral finance side by side. With the help of such a study, researchers can precisely understand the need and can focus on the future course of action to make behavioral finance a mainstream approach to asset pricing.