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Using a dictator game, we examine the other‐regarding behavior of allocators, who are given the responsibility of unilaterally making an allocation decision without consultation on behalf of a two‐person group between their group and another group. We then contrast the behavior of the same individuals in an analogous interindividual situation. We also explore other‐regarding perceptions of passive recipients, who are asked to give behavioral forecasts of how they would behave if assigned the allocator role and how they think their allocators would behave. Gender differences are found in both behavior and perceptions. Males are significantly more self‐interested and less other‐regarding when they are responsible for a group, while females behave similarly under both conditions. Female recipients' forecasts of their own behavior are significantly higher than both their expectations of allocators and the actual female behavior observed in the experiment. Both male and female recipients underestimate the other‐regarding behavior of allocators.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

The purpose of this study is to identify factors instrumental in developing entrepreneurial intentions among youth. Although, numerous studies have been conducted focusing on entrepreneurship intention, however, this study attempts to provide an integrated model by means of analyzing the impact of internal (personal) and external (environmental) factors in developing entrepreneurial intentions.

This cross-sectional study is based on primary and secondary data. A sample of 358 respondents belonging to the age group of 21–25 years from various universities and colleges in Kashmir participated in the study. Primary data collection was done using self-administered questionnaires. A purposive sampling approach was used to identify respondents for the current study. Structural equation modeling has been used for testing hypotheses besides other statistical methods and techniques.

The study identifies three important antecedents of entrepreneurship intentions, namely, personal competencies, contextual factors and entrepreneurial exposure and tests the relationships using path analysis. It further suggests that there exists a significant relationship between personal competencies, entrepreneurial exposure, contextual elements and entrepreneurial intention.

The paper presents an integrated and comprehensive model of entrepreneurial intentions discussing important antecedents instrumental in developing entrepreneurship intentions among youth considering both personal and environmental factors. It is, therefore, an important contribution toward entrepreneurship literature and of interest to different policymakers and institutions related to entrepreneurship.

This study examines the relationship between managerial overconfidence and corporate financing decisions by constructing proxies for managerial overconfidence based on the track records of earnings forecasts in Japanese listed firms. We find that managers have the stable tendency to forecast overly upward earnings compared to actual ones and that their upward bias decreases the probability of issuing equity in the public market by about 4.7 percent per one standard error, which economically has the strongest impact on financing decisions. This tendency is observed when we employ alternative measures for managerial overconfidence and other model specifications. However, in private placements, the choice to offer equity is not always avoided by managers. This implies that managers place private equity with the expectation of the certification effect

Unfortunately, the answers given are thoroughly embedded in the physics-inspired view of the financial economy as a stable and an equilibrium seeking system. In such a view, if some changes do occur in the financial markets, those changes present no discontinuities and the model has ample time to react by slowly adjusting risk forecasts as the volatility rises. As almost everybody in the world by now knows, currently accepted risk models have time and again shown their inability to deal with financial market reality. Frequent talk of ‘hundred year floods’ and ‘rise in correlations’ not only suggests frequent failures of a theory, but also the inability of the theory to learn from past mistakes by incorporating new data. The crash of 2008, completely unforeseen by all traditional risk systems, should serve as the final wake-up call to re-examine the foundations of the old paradigm and consider how sound they really are.

This paper synthesizes existing experimental research in the area of investor perceptions and offers directions for future research. Investor-related experimental research has grown substantially, especially in the last decade, as it has made valuable contributions in establishing causal links, examining underlying process measures, and examining areas with little available data. Within this review, I examine 121 papers and identify three broad categories that affect investor perceptions: information format, investor features, and disclosure credibility. Information format describes how investors are influenced by information salience, information labeling, reporting and accounting complexity, financial statement recognition, explanatory disclosures, and proposed disclosure changes. Investor features describes investors’ use of heuristics, investor preferences, and the effect of investor experience. Disclosure credibility is influenced by external and internal assurance, management credibility, disclosure characteristics, and management incentives. Using this framework, I summarize the existing research and identify areas that would benefit from additional research.

Because of the high volatility with unstable data patterns in the real world, the ability of forecasting price indices is notoriously embarrassing and represents a major challenge with traditional time series mechanisms; especially, most of the traditional approaches are weak to forecast future predictions in the high volatile and unbalanced frameworks under the global and local financial depressions. The purpose of this paper is to propose a new statistical approach for portfolio selection and stock market forecasting to assist investors as well as stock brokers to predict the future behaviors.

This study mainly takes an attempt to understand the trends, behavioral patterns and predict the future estimations under the new proposed frame for the Colombo Stock Exchange (CSE), Sri Lanka. The methodology of this study is carried out under the two main phases. In the first phase, constructed a new portfolio mechanism based on k-means clustering. In the second stage, proposed a nonlinear forecasting methodology based on grey mechanism for forecasting stock market indices under the high-volatile fluctuations. The autoregressive integrated moving average (ARIMA) predictions are used as comparison mode.

Initially, the k-mean clustering was applied to pick out the profitable sectors running under the CSE and results indicated that BFI is more significant than other 20 sectors. Second, the MAE, MAPE and MAD model comparison results clearly suggested that, the newly proposed nonlinear grey Bernoulli model (NGBM) is more appropriate than traditional ARIMA methods to forecast stock price indices under the non-stationary market conditions.

Because of the flexible nonlinear modeling capability, proposed novel concepts are more suitable for applying in various areas in the field of financial, economic, military, geological and agricultural systems for pattern recognition, classification, time series forecasting, etc.

For the large sample of data forecasting under the normality assumptions, the traditional time series methodologies are more suitable than grey methodologies. However, the NGBM is better both in model building and ex post testing stagers under the s-distributed data patterns with limited data forecastings.

Making decisions in finance have been regarded as one of the biggest challenges in the modern economy today; especially, analysing and forecasting unstable data patterns with limited sample observations under the numerous economic policies and reforms. The purpose of this paper is to propose suitable forecasting approach based on grey methods in short-term predictions.

High volatile fluctuations with instability patterns are the common phenomenon in the Colombo Stock Exchange (CSE), Sri Lanka. As a subset of the literature, very few studies have been focused to find the short-term forecastings in CSE. So, the current study mainly attempted to understand the trends and suitable forecasting model in order to predict the future behaviours in CSE during the period from October 2014 to March 2015. As a result of non-stationary behavioural patterns over the period of time, the grey operational models namely GM(1,1), GM(2,1), grey Verhulst and non-linear grey Bernoulli model were used as a comparison purpose.

The results disclosed that, grey prediction models generate smaller forecasting errors than traditional time series approach for limited data forecastings.

Finally, the authors strongly believed that, it could be better to use the improved grey hybrid methodology algorithms in real world model approaches.

However, for the large sample of data forecasting under the normality assumptions, the traditional time series methodologies are more suitable than grey methodologies; especially GM(1,1) give some dramatically unsuccessful results than auto regressive intergrated moving average in model pre-post stage.

The purpose of this paper is to review the insights provided by behavioral finance studies conducted in the last decade (2006-2015) examining behavioral variables in financial decision making.

The literature review assesses 623 qualitative and quantitative studies published in various international refereed journals and identifies possible scope of future work.

The paper identifies stock market anomalies which contradict rational agents of modern portfolio theory at an aggregate level and behavioral mediators, influencing the financial decision making at an investor level. The paper also attempts to classify different dimensions of risk as professed by the investor.

The authors synthesize the contribution made by behavioral finance studies in extending the knowledge of financial market and investor behavior.