Review of Behavioral Finance最新文献

Purpose

This paper seeks to investigate whether women exhibit greater risk-aversion behavior than men in investments by estimating the influence of gender on portfolio volatility.

Design/methodology/approach

Data on the volatility observed in the portfolio in the last six months, last twelve months and since the individual became a client at one of the largest financial institutions in Brazil – and in Latin America – that operates in the capital markets are used. In addition to the gender explanatory variable, socioeconomic variables such as age, marital status, suitability, residence in capitals and declared assets are controlled, and multiple linear regression models are controlled.

Findings

The results show that gender is statistically significant in all models estimated to explain the volatility of investment portfolios, saying that women are more risk averse than men.

Originality/value

These findings are useful for the scientific literature that investigates behavioral finance by bringing empirical evidence for Brazil.

Purpose

Using a substantial sample of U.S.-listed firms’ Seasoned Equity Offerings (SEOs) spanning the period from 2012 to 2017, we examine the relationship between hierarchical complexity and the selection of SEO methods.

Design/methodology/approach

We employ multinomial logistic regression to examine the influence of hierarchical complexity on the choice among various SEO techniques. To strengthen the robustness of our results, we employ a two-stage-least-squares (2SLS) analysis and utilize propensity score matching to address potential endogeneity issues and mitigate self-selection bias, respectively.

Findings

The research indicates that companies characterized by high levels of hierarchical complexity tend to steer clear of accelerated offerings but exhibit a preference for rights offerings over firm commitment offerings. This tendency is plausibly attributed to the impact of hierarchical complexity, which diminishes information transparency and heightens information asymmetry. Furthermore, the study highlights a negative association between hierarchical complexity and firm value following SEOs.

Originality/value

While an expanding body of evidence establishes a connection between hierarchical complexity and various firm- or market-specific activities, to the best of our knowledge, there are no specific empirical studies that have investigated how hierarchical complexity impacts equity offering strategies. Building on the established correlation in previous research between hierarchical complexity, information transparency, and asymmetric information, and recognizing the critical role of information in the selection of SEO methods, our study reveals that hierarchical complexity may diminish information transparency, heighten information asymmetry, and hinder outside investors from fully grasping a firm’s actions and outcomes. Consequently, this influence extends to the methods of offerings chosen by listed companies.

Purpose

This study examines herding behaviour in commodity markets amid two major global upheavals: the Russo–Ukraine conflict and the COVID-19 pandemic.

Design/methodology/approach

By analysing 18 commodity futures worldwide, the study examines herding trends in metals, livestock, energy and grains sectors. The applied methodology combines static and dynamic approaches by incorporating cross-sectional absolute deviations (CSAD) and a time-varying parameter (TVP) regression model extended by Markov Chain Monte Carlo (MCMC) sampling to adequately reflect the complexity of herding behaviour in different market scenarios.

Findings

Our results show clear differences in herd behaviour during these crises. The Russia–Ukraine war led to relatively subdued herding behaviour in commodities, suggesting a limited impact of geopolitical turmoil on collective market behaviour. In stark contrast, the outbreak of the COVID-19 pandemic significantly amplified herding behaviour, particularly in the energy and livestock sectors.

Originality/value

This discrepancy emphasises the different impact of a health crisis versus a geopolitical conflict on market dynamics. This study makes an important contribution to the existing literature as it is one of the first studies to contrast herding behaviour in commodity markets during these two crises. Our results show that not all crises produce comparable market reactions, which underlines the importance of the crisis context when analysing financial market behaviour.

Purpose

The paper aims to investigate differences in non-professional and professional stock investors’ trust in and tendency to follow financial analysts’ buy and sell recommendations.

Design/methodology/approach

Online experiment conducted in Sweden in March 2022 comparing non-professional private investors (n = 80), professional investors (n = 33), and master students in finance (n = 28). Information was presented about four company stocks listed on the New York stock exchange. Two stocks were buy-recommended and two stocks sell-recommended by financial analysts. For one stock of each type, the recommendation was presented to participants. Dependent variables were predictions of the stock price after three months, ratings of confidence in the predictions and choices of holding, buying or selling the stock. Ratings were also made of the importance of presented stock-related information as well as trust in analysts’ skill and integrity.

Findings

More positive return predictions were made of buy-recommended than sell-recommended stocks. Non-professionals and to some degree finance students tended to trust financial analysts more than professional investors did and they were more influenced by the presentation of the buy recommendations. All groups made too optimistic return predictions, but the professionals were less confident in their predictions, more likely to sell the stocks and lost less on their investments.

Originality/value

A new finding is that non-professional stock investors are more likely than professional stock investors to trust financial analysts and follow their recommendations. It suggests that financial analysts’ recommendations influence non-professional investors to take unmotivated investment risks. Non-professionals in the stock market should hence be advised to exercise more caution in following analysts’ recommendations.

Purpose

This paper aims to explore the development of investment decision tools by understanding the rationality behind the disposition effect. We suspect that not all disposition decisions are irrational. The decisions should be evaluated based on the bounded rationality of the individuals’ target and tolerance level, which is not covered in previous literature. Adding the context of individual preference (target and tolerance) in their decision could improve the classic measurement of disposition effect.

Design/methodology/approach

The laboratory web experiment is prepared to collect the responses in holding and selling the stocks within 14 days. Two groups of Gen Z investors are observed. The control group makes a decision based on their judgment without any system recommendation. In contrast, the second group gets help inputting their target and tolerance. Furthermore, the framing effect is also applied as a reminder of their target and tolerance to induce more holding decisions on gain but selling on loss.

Findings

The framing effect is adequate to mitigate the disposition effect but only at the early day of observation. Bounded rationality explains the rationality of liquidating the gain because the participants have reached their goal. The framing effect is not moderated by days to affect the disposition effect; over time, the disposition effect tends to be higher. A new measurement of the disposition effect in the context of bounded rationality is better than the original disposition effect coefficient.

Practical implications

Gen Z investors need a system aid to help their investment decisions set their target and tolerance to mitigate the disposition effect. Investment firms can make a premium feature based on real-time market data for investors to manage their assets rationally in the long run. Bounded rationality theory offers more flexibility in understanding the gap between profit maximization and irrational decisions in behavioral finance. The government can use this finding to develop a suitable policy and ecosystem to help beginner investors understand investment risk and manage their assets based on subjective risk tolerance.

Originality/value

The classic Proportion Gain Realized (PGR) and Proportion Loss Realized (PLR) measurements cannot accommodate several contexts of users’ targets and tolerance in their choices, which we argue need to be re-evaluated with bounded rationality. Therefore, this article proposed new measurements that account for the users’ target and tolerance level to evaluate the rationality of their decision.

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Practical implications

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.

Originality/value

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.

Purpose

This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.

Design/methodology/approach

The authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.

Findings

The study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.

Practical implications

Despite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.

Originality/value

This study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.

Purpose

The price clustering behavior is becoming a core part of the market efficiency theory especially with the development of trading strategies and the occurrence of major and unprecedented shocks which have led to severe inquiry regarding asset price dynamics and their distribution. However, research on emerging stock market is scant. The study contributes to the literature on price clustering by investigating an active emerging stock market, the Muscat stock market one of the Arabian Gulf Markets.

Design/methodology/approach

This research adopts the artificial intelligence technique and other statistical estimation procedure in understanding the price clustering patterns in Muscat stock market and their main determinants.

Findings

The findings reveal that stock prices are marked by clustering behavior as commonly highlighted in the previous studies. However, we found strong evidence of price preferences to cluster on numbers closer to zero than to one. We also show that the nature of firm’s activity matters for price clustering behavior. In addition, firms with traded bonds in Oman market experienced a substantial less stock price clustering than other firms. Clustered stock prices are more likely to have higher prices and higher volatility of price. Finally, clustering raised when the market became highly uncertain during the Covid-19 crisis especially for the financial firms.

Originality/value

This study provides novel results on price clustering literature especially for an active emerging market and during the Covid-19 pandemic crisis.