Journal of Behavioral and Experimental Finance最新文献

We investigate the price clustering effect in cryptocurrency limit order books, where traders tend to place orders in round numbers. Analyzing 10-minute snapshots of five USD-denominated cryptocurrencies over 35 weeks (January–August 2020), we find that the frequency of specific cent components (e.g., 00, 50) increases significantly at higher price levels. Subsample analyses reveal that this effect strengthens with larger previous cumulative dollar depth and larger price distance from the best price. Furthermore, near-best-price and far-from-best-price dollar quotes exhibit a weak negative and strong positive price impact, respectively, confirming the informativeness of the clustering effect. These findings remain robust when considering superstitious two digits, cluster undercutting, last digits, excluding stale quotes, and additional price levels.

Should cryptocurrencies be viewed as a gambling tool or a risky investment instrument? While their unpredictable returns resemble gambling, recent studies show their prices having a time-varying correlation with traditional risky assets like the S&P 500. Many institutional investors have, thus, included cryptocurrencies in their portfolios for diversification. This paper examines the behavior of cryptocurrency market participants and investigates whether they behave like gamblers or investors. Literature shows that gamblers often engage in loss-chasing behavior, escalating risk-taking after losses that may go on indefinitely. In contrast, investors typically exhibit risk aversion after losses, though some might increase risk-taking after “paper losses,” a phenomenon called the “realization effect.” Our study found high-risk individuals exhibit gambling-like behavior, chasing both realized and paper losses. In contrast, we found limited evidence that low-risk individuals engage in risk aversion and realization effect, similar to investors. These insights are crucial for policymakers, as loss-chasing can lead to the siutation where people taking on more risk than they can afford, potentially resulting in bankruptcy.

This paper analyzes the relationship between investor herding and attention in the decentralized cryptocurrency market with its continuous, around the clock trading and large share of retail investors. Herding behavior is stronger when market returns are positive but is negatively related to both the level and cross-sectional dispersion of investor attention. Moreover, there are pronounced intraday variations: Herding exhibits similar patterns as attention and blockchain activity and is strongest during the overlap of hours when traders in major economic centers are likely awake.

This study uses a time-varying parameter vector autoregression (TVP-VAR) approach to examine the transmission of tail risk among G7 stock markets from January 2000 to September 2022, focusing on major financial episodes like the dot-com collapse, the 2008 Global Financial Crisis, and the European debt crisis, as well as the COVID-19 pandemic and its variants. Our analysis shows fluctuating tail risk connectedness across G7 markets during the pandemic, influenced by lockdowns, supply chain issues, interventions, and investor sentiment. Notably, the UK and Italy were major tail risk transmitters, whereas Japan predominantly absorbed risk, highlighting its distinct vulnerability. The findings stress the need for a comprehensive understanding of tail risk dynamics to inform decisions by investors, governments, and regulators, ensuring financial system resilience during heightened economic stress.

We examine the role of borrowers' job titles in the online peer-to-peer (P2P) lending market. Using the U.S. Occupational Information Network database, we define skilled borrowers as the borrowers with their job titles in Job Zone 5, a group of occupations requiring individuals with the most extensive skill, knowledge, education and related experience. Analyzing data from Lending Club, one of the largest P2P platforms in the US, we find evidence that skilled borrowers are perceived as trustworthy and receive lower loan interest rate and default less frequently than do their non-skilled peers. Consistent with the signaling framework, our empirical results suggest that borrowers with certain job titles send effective signals and trustworthy job titles affect lending decisions and performance. This study sheds new light on the importance of borrowers' job titles in P2P lending.

Research in the social sciences has shown that interactions with biological daughters are potent catalysts for instilling and nourishing parents' social values, preferences, and behaviors. Drawn on the female socialization hypothesis, we investigate the impact of ultimate controlling owners’ offspring gender on corporate dividend policy. Based on data from Chinese family-owned listed companies, our empirical results document a “daughter effect” in cash dividends. That is, ultimate controlling owners shaped by daughters are more altruistic and less likely to exploit the interests of minority shareholders, which leads to more dividend activities. The results remain robust when considering endogeneity. Moreover, the “daughter effect” is more pronounced when the ultimate controlling owner is male, has a higher education background, and has been influenced by the daughter for a longer time. This paper contributes to the growing literature on female socialization and the determinants of dividend payments.

Research in behavioral and experimental finance becomes more multifaceted and the analysis of data from speech interactions more important. This raises the need for technical support for researchers using qualitative data generated from speech interactions. aTrain serves this need and is an open-source, offline transcription tool with a graphical interface for audio data in multiple languages. It requires no programming skills, runs on most computers, operates without internet, and ensures data is not uploaded to external servers. aTrain combines OpenAI’s Whisper transcription models with speaker recognition and provides output that integrates with MAXQDA and ATLAS.ti. Available on the Microsoft Store for easy installation, its source code is also accessible on GitHub. aTrain, designed for speed on local computers, transcribes audio files at 2-3 times the audio duration on mobile CPUs using the highest-accuracy Whisper transcription models. With an entry-level graphics card, this speed improves to 30% of the audio duration.

Corporate social responsibility (CSR) plays an important role in developing countries achieving sustainable goals. Using the textual analysis of Chinese earnings communication conferences, we investigate whether the managers' time horizons influence CSR performance. We find that the level of managerial myopia is negatively related to CSR scores. This deleterious impact manifests asymmetrically under diverse expectations. Furthermore, guided by the CSR pyramid theory, our findings suggest that managerial myopia undermines both financial and legal responsibilities, subsequently exerting an influence on the commitment to social responsibility. Compensation incentives can effectively mitigate the deleterious impacts associated with myopia. Nevertheless, heightened external pressures originating from capital and product markets may impose constraints on managers' time horizons, thereby amplifying the adverse repercussions of myopia.

This paper empirically investigates the financial performance of asset allocation strategies under “sustainable” risk preferences and conventional risk preferences. We assume that traditional investors and ESG investors behave differently in their investment decisions. The optimal portfolio choice is developed including dynamic higher order conditional co-moments and time-varying risk aversion. From an out-of-sample empirical experiment, we observe that this optimization technique provides much more stable optimal weights for the sustainable portfolio than for the traditional one. Based on both classical and downside-risk performance measures, active management in both portfolios outperforms the global market index. In this context, the non-inclusion of skewness and kurtosis leads to an underestimation of actual risk exposure. Finally, we provide empirical evidence that the sustainable portfolio largely outperformances the traditional investment.

This study examines 350 Level III ADR IPOs from 35 countries between 1990 and 2020 to explore the link between societal secrecy and IPO underpricing. Focusing on ADR IPOs, we hypothesize that firms from higher secrecy countries, compared to firms from low secrecy countries, benefit more from public offerings in a low secrecy country. U.S. investors might value these firms relatively more due to the reduction in information asymmetry and higher expected diversification benefits. The results support our hypothesis, showing that ADR IPO underpricing is lower for ADRs from high secrecy countries. These findings hold true across various measures and controls, ensuring robustness.