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.
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.
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.
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.
The purpose of the research paper is to investigate the relationship between personality traits and investment decisions in the crypto market, including cryptocurrencies and NFTs. The study aims to explore the effect of dark personalities and the big five personalities on investment decisions in the crypto market.
The research was conducted through two online questionnaire studies. In Study 1, data were collected from the general public, while in Study 2, data were collected from crypto investors. The researchers analyzed the effect of dark personalities and the big five personalities on investment decisions in the crypto market.
The present research found that Machiavellianism, narcissism, psychopath, sadism and extraversion have positive effects on having crypto investments. In addition, focusing on actual crypto investors, the present paper showed that personalities including Machiavellianism, narcissism, psychopath, consciousness and extraversion have statistically significant effect on investment decisions such as making investments in Bitcoin.
The study is original in exploring the relationship between personality traits and investment decisions in the newly emerging crypto market, including cryptocurrencies and NFTs. The research provides insights into how different personality traits affect investment decisions in the crypto market, which can be valuable for investors in making informed decisions.
This study examines the relationship between investors' familiarity bias, including the home bias and endowment bias, and their financial situations, expectations and personal characteristics.
Using the 2019 Survey of Consumer Finances, the authors utilize an ordinary least squares regression to identify the presence of endowment bias and home bias in individual investors' direct stock holdings and use a Heckman selection model to examine determinants of the extent of endowment bias and home bias.
This study finds that investors with higher income and more education, men, non-white investors and people with greater risk tolerance are actually at a greater risk of endowment bias. This study also identifies a profile of investors that are more likely to have a home bias: with less financial sophistication, lower net worth, older, female, more risk-averse, with a positive expectation about the domestic economy and a relatively shorter investment horizon.
This paper is among the first to use US investors' directly reported stock holdings to examine the individual characteristics that are correlated with greater familiarity bias, providing financial professionals with information about how to allocate their limited time in providing education to a variety of clients.
The purpose of this paper is to examine how individual risk preference influences the borrowing of payday loans – a prevalent type of cash loan in the USA with exorbitantly high-interest rates. Additionally, this paper tests how risk preference determines other alternative financial services (AFS), including pawn shops, rent-to-own purchases, title loans, etc.
The author applies Probit and Tobit regressions to test the relationship between individual risk preference and payday borrowing, based on the state-by-state survey data from National Financial Capability Study (NFCS) sponsored by Financial Industry Regulatory Authority (FINRA) Investor Education Foundation.
Individuals with higher risk tolerance are more likely to borrow payday loans and other AFS, after controlling for financial situation, financial literacy, overconfidence and demographic features.
This paper is the first to study risk preference as an explanation to the high cost and widely used payday loan services in the United States of America. This study provides evidence that these cash loans are determined by inherent human characteristics. The finding provides new insight for the policymakers and regulators in the consumer debt market.
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：