Review of Behavioral Finance最新文献

Purpose

The purpose of this study is to examine the influence of conscientiousness on entrepreneurship over and above the impact of other factors that are associated with entrepreneurship in the literature.

Design/methodology/approach

The design uses household responses from the Panel Study of Income Dynamics (PSID) biennial survey that follows the same heads of households over time to measure their conscientiousness, businesses owned and other demographic and financial characteristics. Ordinary least squares (OLS), Probit and Poisson regression techniques are applied at the head of household and state level to examine the relationship.

Findings

The results show heads of households’ conscientiousness positively relating to the average number of businesses owned, beyond other Big Five traits and the impact of other characteristics. A one-standard deviation increase in conscientiousness is significantly associated with a 0.012 increase in the number of businesses owned. This association is robust to alternative regression specifications and variable measurements.

Originality/value

The results are original to the finance literature, complementing studies by linking intrinsic head of household-level traits to entrepreneurship while controlling for external financial and demographic factors. The study also attempts to externally validate previous findings using aggregate-level outcomes. The data and setting used to measure personality traits as well as entrepreneurial outcomes are original to the entrepreneurship literature, validating previous findings.

Purpose

The purpose of our study is to study the impact of chief executive officer (CEO) optimism and narcissism on the company's capital structure.

Design/methodology/approach

(1) The authors opt for regression, machine learning and text analysis to explore the impact of narcissism and optimism on the capital structure. (2) We analyze CEO interviews and employ three methods to evaluate narcissism: the dictionary proposed by Anglin, which enabled us to assess the following components: authority, superiority, vanity and exhibitionism; count of first-person singular and plural pronouns and count of CEO photos displayed. Following this approach, we were able to make a more thorough assessment of corporate narcissism. (3) Latent Dirichlet allocation (LDA) technique helped to find the differences in the corporate rhetoric of narcissistic and non-narcissistic CEOs and to find differences between the topics of interviews and letters provided by narcissistic and non-narcissistic CEOs.

Findings

Our research demonstrates that narcissism has a slight and nonlinear impact on capital structure. However, our findings suggest that there is an impact of pessimism and uncertainty under pandemic conditions when managers predicted doom and completely changed their strategies. We applied various approaches to estimate the gender distribution of CEOs and found that the median values of optimism and narcissism do not depend on sex. Using LDA, we examined the content and key topics of CEO interviews, defined as positive and negative. There are some differences in the topics: narcissistic CEOs are more likely to speak about long-term goals, projects and problems; they often talk about their brand and business processes.

Originality/value

First, we examine the COVID-19 pandemic period and evaluate how CEO optimism and pessimism affect their financial decisions under specific external conditions. The pandemic forced companies to shift the way they worked: either to switch to the remote work model or to interrupt operations; to lose or, on the contrary, attract clients. In addition, during this period, corporate management can have a different outlook on their company’s financial performance and goals. The LDA technique helped to find the differences in the corporate rhetoric of narcissistic and non-narcissistic CEOs. Second, we use three methods to evaluate narcissism. Third, the research is based on a set of advanced methods: machine learning techniques (random forest to reveal a nonlinear impact of CEO optimism and narcissism on capital structure).

Purpose

The study aims to test prospect theory (PT) predictions in the cryptocurrency (CC) market. It proposes a new asset pricing model that explores the potential of prospect theory value (PTV) as a significant predictor of CC returns.

Design/methodology/approach

The study comprehensively analyses a large sample set of 1,629 CCs, representing more than 95% of the CC market. The study uses a portfolio analysis approach, employing univariate and bivariate sorting techniques with equal-weighted and value-weighted portfolios. The study also employs ordinary least squares (OLS) regression, panel data methods and quantile regression (QR) to estimate the models.

Findings

This study demonstrates an average inverse relationship between PTV and CC returns. However, this relationship exhibits asymmetry across different quantiles, indicating that investor reactions vary based on market conditions. Moreover, PTV provides more robust predictions for smaller CCs characterized by high volatility and illiquidity. Notably, the findings highlight the dominant role of the probability weighting (PW) component in PT for predicting CC behaviors, suggesting a preference for lottery-like characteristics among CC investors.

Originality/value

The study is one of the early studies on CC price dynamics from the PT perspective. The study is the first to apply a QR approach to analyze the cross-section of CCs using a PT-based asset pricing model. The results shed light on CC investors' decision-making processes and risk perception, offering valuable insights to regulators, policymakers and market participants. From a practical perspective, a trading strategy centered around the PTV effect can be implemented.

Purpose

Robo-advisory has become an increasingly popular asset management tool in recent decades. This paper studies the association between robo-advisor usage and perceived financial satisfaction.

Design/methodology/approach

Using data extracted from the National Financial Capability Study 2015 (NFCS2015), the present study carried out a logistic analysis that examines the association between robo-advisory and perceived financial satisfaction. This model also studies the interaction effect of age on this association.

Findings

The present study finds that robo-advisor usage is positively correlated with a person’s perceived financial satisfaction after controlling for covariates related to financial literacy and other demographic factors. Moreover, the present study reveals that age moderates the association between robo-advisory usage and financial satisfaction. The results are robust after regressing financial satisfaction on robo-advisory by different age groups.

Originality/value

This paper extends existing literature on robo-advisory by showing that robo-advisory usage relates to a higher level of financial satisfaction. This finding helps understand the rapidly increasing trend of robo-advisory in the financial industry. Moreover, the present study reveals a moderate effect of age on the association between robo-advisory usage and perceived financial satisfaction.

Purpose

This work uses survey data from the Portuguese Securities Market Commission (Comissão de Mercado de Valores Mobiliários – CMVM) to examine financial literacy and literacy bias. The main objective of this study is to shed light on this issue by identifying the individual characteristics that are associated with financial literacy, namely overconfidence and underconfidence, which in turn might help explain individuals' financial decisions. The study distinguishes two groups, i.e. students and nonstudents, and considers several characteristics that are usually employed in this stream of research.

Design/methodology/approach

The data are based on a survey conducted by a partnership between the CMVM and a consortium of Portuguese universities. This paper has a three-fold aim. First, it studies the main individual features associated with objective financial literacy. Second, it analyzes the relationship between those variables and the bias between self-perceived and objective literacy, distinguishing overconfidence and underconfidence. Third, and most originally, this framework was also used to examine the differences between students and nonstudents. Those aims are pursued using cross-sectional ordinary least squares (OLS) regressions, except for the study of the literacy bias, for which the authors use an ordered probit.

Findings

Literacy is higher in individuals of the male gender who are older, have higher incomes, live in metropolitan areas, are highly educated, have a field of study related to finance and have high self-perceived literacy. Younger people are more overconfident. Unconditionally, women are less overconfident than men, but conditionally, they overestimate their knowledge. People holding securities and with a field of study related to finance are more overconfident. The gender effect is mainly driven by students, and the impact of a field of study and of holding securities on overconfidence decreases and increases, respectively, for students. The results highlight the importance of financial education.

Research limitations/implications

Due to the way that the questionnaire was made available, there is no guarantee that the sample is representative of the Portuguese general population, or, for that matter, representative of the typical Portuguese retail investors or households. Also, there is no guarantee that the same individual did not answer the questionnaire more than once, although this is highly improbable. The link to the online questionnaire was only transmitted within e-mail databases owned by the CMVM and Portuguese universities, so the authors cannot guarantee its unbiasedness.

Practical implications

The authors' results may help the National Plan for Financial Education (the acronym in Portuguese is PNFF) fine-tune the required actions towar

Purpose

In the context of investment decisions, the intricate interplay between exogenous shocks and their influence on investor confidence significantly shapes their behaviors and, consequently, their outcomes. Investment decisions are influenced by uncertainties, exogenous shocks as well as the sentiments and confidence of investors, factors typically overlooked by decision-makers. This study will meticulously examine these multifaceted influences and discern their intricate hierarchical nuances in the sentiments of industrial entrepreneurs during the COVID-19 pandemic.

Design/methodology/approach

Employing the robust framework of the generalized linear latent and mixed models (GLLAMM), this research will thoroughly investigate individual and group idiosyncrasies present in diverse data compilations. Additionally, it will delve deeply into the exogeneity of disturbances across different sectors and regions.

Findings

Relevant insights gleaned from this research elucidate the adverse influence of exogenous forces, including pandemics and financial crises, on the confidence of industrial entrepreneurs. Furthermore, a significant discovery emerges in the regional analysis, revealing a notable homogeneity in the propagation patterns of industrial entrepreneurs' perceptions within the sectoral and regional context. This finding suggests a mitigation of regional effects in situations of global exogenous shocks.

Originality/value

Within the realm of academic inquiry, this study offers an innovative perspective in unveiling the intricate interaction between external shocks and their significant impacts on the sentiment of industrial entrepreneurs. Furthermore, the utilization of the robust GLLAMM captures the hierarchical dimension of this relationship, enhancing the precision of analyses. This approach provides a significant impetus for data-informed strategic directions.