Purpose This paper addresses the conflicting views on whether traders become more risk-averse or more risk-seeking after experiencing trading shocks. It aims to uncover how the magnitude of prior gains or losses influences subsequent risk-taking behavior in retail trading. Design/methodology/approach Using over 349,000 daily retail trading records, the study classifies trading shocks into 18 levels and examines their lagged effects on traders' risk-taking behavior, measured by leverage. Findings Traders' responses to prior shocks exhibit clear asymmetry. After small shocks, whether gains or losses, traders become more risk-averse. In contrast, after large shocks, especially gains, they become increasingly risk-seeking. These effects scale with shock levels and fade over time. The switching point between risk aversion and risk seeking lies deeper in the loss domain. Practical implications By revealing nonlinear post-shock risk preferences, this study suggests design opportunities for trading platforms, such as nudging tools to prevent excessive risk-taking after large shocks. It also informs risk management systems that aim to reduce over-leverage during volatile periods. Originality/value This paper introduces a detailed framework for analyzing aftershock risk preferences, offering a behavioral explanation for previous mixed findings. It contributes to the literature by revealing a nonlinear, asymmetric pattern in how risk preferences respond to shocks.

Purpose This study aims to examine the effect of investor sentiment and institutional trading behavior on stock market returns and volatility in India, emphasizing asymmetric, causal and time-varying dynamics. Design/methodology/approach The study uses daily data from January 2010 to December 2024 and follows a stepwise empirical strategy. Ordinary least squares (OLS) models are employed to assess the impact of investor sentiment on returns and volatility, including asymmetries captured through positive and negative sentiment components. Pairwise Granger causality tests are used to identify directional linkages, while a term structure framework evaluates effects across different horizons. Robustness is ensured using an alternative equity index and exponential generalized autoregressive conditional heteroscedastic (EGARCH)-based volatility measures. Findings The results indicate that investor sentiment significantly affects returns and volatility, with negative sentiment exhibiting greater persistence than positive sentiment. Trading imbalances of both domestic and foreign institutional investors reduce volatility, highlighting their stabilizing roles. Granger causality tests indicate mutual feedback between sentiment and institutional activity, except for a one-way influence from domestic trading to sentiment. Term-structure analysis reveals that these effects weaken across horizons, though the influence of foreign trading remains comparatively more persistent. Practical implications The findings guide regulators in designing risk-sensitive policies and implementing timely interventions, while providing investors with evidence-based strategies for managing sentiment-driven risks. Originality/value This study provides evidence on the asymmetric and temporal effects of investor sentiment and institutional trading behavior in India's equity market, advancing behavioral finance research in emerging economies.

Purpose This study investigates how individuals who have fallen victim to investment scams perceive and interpret their financial decision-making, with a focus on the psychological and social mechanisms contributing to their vulnerability. It challenges the assumption that financial literacy alone mitigates fraud risk by examining the role of cognitive biases, emotional states and social influence. Design/methodology/approach Adopting a qualitative design, the study employed Interpretative Phenomenological Analysis (IPA) to explore the subjective experiences of twelve scam victims (N = 12) in the Philippines. Data were collected through in-depth semi-structured interviews and analyzed thematically, guided by core constructs of behavioral finance theory. Findings Cognitive biases – overconfidence, anchoring and confirmation bias – along with emotional responses such as hopefulness, excitement and regret, impaired risk judgment. Social mechanisms, including affinity bias and herd behavior, further reduced skepticism. Post-scam responses varied, with participants reporting either financial withdrawal or increased vigilance. Financial literacy was recognized but insufficient without behavioral awareness. Research limitations/implications Findings are context-specific and drawn from a small, purposively selected sample, limiting generalizability. Future research may compare victim experiences across cultures and scam types. Social implications The study supports policy reforms emphasizing behavioral training, critical thinking and social influence resistance to strengthen financial resilience in vulnerable communities. Originality/value This study integrates behavioral finance theory with phenomenological inquiry, providing empirical evidence of how heuristic reasoning, affective states and relational trust intersect in scam victimization. It advances fraud prevention research by prioritizing experiential insight over purely rationalist models.

Purpose This study investigates volatility and returns spillovers among US technology stocks, decentralized finance (DeFi) tokens and conventional cryptocurrencies, while also examining strategies for optimal portfolio allocation. Design/methodology/approach The study analyses daily financial market data from October 05, 2020 to February 09, 2024 by employing the Diebold and Yilmaz (2012) and dynamic conditional correlations generalized auto-regressive conditional heteroscedasticity (DCC-GARCH) models. Findings Empirical findings showed that the US technology stocks were highly interconnected both in returns and volatilities (same as the crypto assets), while technology stock-crypto asset market connections were quite low. Moreover, the technology stocks (crypto assets) were generally net volatility and return receivers (transmitters). Overall, market connectedness was high (65.6% for volatility and 77.2% for return). Portfolio optimization results showed that technology stock-crypto asset (all-DeFi, all-cryptocurrency, all-technology stock and DeFi-cryptocurrency) portfolios were attractive to risk-averse (risk-neutral and risk-seeking) investors. Originality/value This is the first study to comprehensively analyze volatility and return connectedness and provide insights into portfolio optimization across traditional technology, DeFi and cryptocurrency markets. The insights from this study will aid in risk management, optimal portfolio diversification and formulation of regulations and policies to promote market stability.

PurposeThis study investigates herd behavior in the Fan Tokens market, comparing it with the non-fungible tokens (NFTs) and traditional cryptocurrency markets.Design/methodology/approachThis study investigates herding behavior by examining the relationship between the cross-sectional dispersion of asset returns and overall market returns, utilizing five distinct model specifications. To enhance the robustness of the findings, the regressions are re-estimated using the GARCH model, ensuring more reliable parameter estimates and capturing the impact of volatility on herding behavior.FindingsThe analysis reveals strong evidence of herd behavior in the Fan Token market, particularly during bearish conditions, heightened volatility, and low trading volume. Positive news was found to amplify volatility more than negative news. In contrast, no statistically significant herd behavior was identified in the NFT and traditional cryptocurrency markets, where investors showed a more cautious response to market conditions.Practical implicationsUnderstanding the unique dynamics of Fan Tokens can help investors, regulators, and market participants make informed decisions and develop strategies to mitigate risks associated with herd behavior and volatility in this rapidly evolving market.Originality/valueThis study highlights the unique characteristics of Fan Tokens, emphasizing their strong ties to fan sentiment and sports outcomes, as well as the role of uninformed investors in shaping market dynamics. The findings contribute to the literature on digital asset markets and investor psychology, offering novel insights into this emerging asset class.

PurposeThis paper investigates the associations among the Big 5 personality traits (neuroticism, conscientiousness, agreeableness, openness to experience and extroversion), nine prominent investment biases and the moderating role of financial literacy.Design/methodology/approachWe used survey data from 475 individual investors in India based on various benchmarked scales in the literature and structural equation modeling to evaluate the desired relationship between the constructs.FindingsOur evidence shows that the extroversion personality trait is the most vulnerable to behavioral biases, and overconfidence bias affects individual Indian investors the most. Financial literacy is positively associated with two biases (risk aversion and representativeness bias) and moderates the relationship between two personality traits (extroversion and agreeableness) and risk aversion.Research limitations/implicationsOur study has limitations. First, it does not examine financial literacy in detail. Therefore, researchers should examine financial literacy within larger frameworks than those used in our study. Second, we confined our analysis to the Big 5 personality traits and nine behavioral biases. Our selection of biases to include in the study involved some subjectivity. Third, we limited our analysis to Indian investors. Researchers should replicate our study to see if its findings are generalizable in other countries with differing characteristics. Our findings call for a more careful examination of the circumstances behind which personality traits manifest in specific bias.Practical implicationsInvestment advisors can help their clients make rational investment decisions by guiding them to deal with their investment biases.Social implicationsImproving financial literacy could help investors avoid the pitfalls of behavioral biases and increase their performance in the stock market.Originality/valueThis study is the first to provide a comprehensive framework that examines the relationship between personality traits and investor biases and the moderating role of financially literate investors.

PurposeThis study examines the impact of online budget planning platforms (e.g. Goodbudget, Mint) on households’ financial satisfaction. Furthermore, the authors identify the channels and the cross-sectional heterogeneity of this impact based on households’ income, financial literacy and minority groups.Design/methodology/approachThis study utilizes data from the National Financial Capability Study (NFCS) for 2018 and 2021, which encompasses over 50,000 households. The authors apply logit and ordered logit regression techniques to examine the research questions and use propensity score matching and entropy balancing to address potential sample selection bias.FindingsThe authors find a substantial correlation between the adoption of financial budgeting tools and a notable improvement in households’ financial satisfaction, driven by the promotion of healthy financial behaviors and enhanced financial self-efficacy. The empirical findings underscore that the positive effects of online budget planners are more pronounced among low-income, financially illiterate and Black households.Originality/valueThis study is the first to examine the impact of online budget planners on household financial satisfaction. It contributes to the literature by offering valuable insights into how these tools influence financial satisfaction within households.

PurposeThis study investigates the paradox of lotteries in financial markets, challenging traditional utility models predicated on rational behavior amid uncertainty. It explores why investors are drawn to lotteries despite the potential trade-off between risk-adjusted returns and sporadically substantial gains.Design/methodology/approachEmploying a multifaceted approach, the study first scrutinizes diverse theories elucidating the perplexing behavior of lottery investors. Subsequently, it assesses the premium attached to lottery stock shares in the Brazilian financial market using distinct methodologies, thereby offering a comprehensive analysis of this phenomenon. Finally, the study estimates the risk premium associated with the lottery stocks applying an extended Fama–French multifactor model and searching for evidence of overlap with other risk-based anomalies.FindingsThis research unveils theories underpinning seemingly irrational investor behavior vis-à-vis lotteries, revealing the motivations propelling investors to willingly exchange risk-adjusted returns for the allure of substantial but infrequent gains. Empirical evidence delineates the extent of the premium paid for lottery stocks in the Brazilian market.Originality/valueThe study’s novelty lies in its amalgamation of theoretical exploration, empirical analysis and the application of the Fama–French factor model to gauge the risk premium associated with lottery-related behavior. Furthermore, its investigation of lottery stocks within the Brazilian market introduces a distinctive dimension, elucidating market dynamics and investor behaviors unique to the region.

PurposeThis research employs a behavioural approach to investigate the determinants of CEO disclosure tone inconsistency. By examining CEO characteristics and psychological attributes, the study aims to unravel the complexities underlying tone variations in Management Discussion and Analysis (MD&A) reports. Through this exploration, the research seeks to contribute to understanding ethical considerations in corporate communications and provide insights into the nuanced interplay between personal, job-related and psychological factors influencing CEO disclosure tone.Design/methodology/approachThe study utilises a dataset comprising 1,411 MD&A reports from 143 companies listed on the Tehran Stock Exchange between 2012 and 2021. Multiple regression analyses with year- and industry-fixed effects are employed to examine the relationships between CEO gender, tenure, duality, ability and psychological attributes such as narcissism, myopia, overconfidence and tone inconsistency. Data analysis involves MAXQDA software for analysing MD&A reports and Rahavard Novin software for document analysis, supplemented by audited financial statements.FindingsThe findings reveal significant relationships between CEO characteristics, psychological attributes and tone inconsistency. Female CEOs exhibit reduced tone inconsistency, contrasting with previous research trends. CEO tenure correlates negatively with tone inconsistency, whereas CEO ability shows a positive correlation, indicating a nuanced relationship with performance. However, CEO duality does not exhibit a significant association. Psychological attributes such as narcissism and myopia are positively associated with tone inconsistency, while no substantial connection is found with managerial overconfidence.Originality/valueThis research contributes to the inaugural exploration of CEO disclosure tone inconsistency through a behavioural lens, advancing measurement precision in the field. By delving into CEO characteristics and psychological attributes, the study offers unique insights into the roots of tone inconsistency. Applying comprehensive lexicon and phraseology enriches the methodological approach, fostering dialogue among diverse stakeholders and adding distinct perspectives to the discourse on ethical issues in business. Through its meticulous examination of behavioural underpinnings, this study becomes a catalyst for reflection, dialogue and progress in corporate communications and ethical considerations.

PurposeThis paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland.Design/methodology/approachThis paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland. Univariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering.FindingsUnivariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering. Results reveal pervasive clustering, strengthening with higher prices and turnover but weakening with larger trade volumes, firm size, and smaller tick sizes. These empirical findings support the theoretical expectations of price negotiation and resolution hypotheses.Practical implicationsThe observed clustering presents an opportunity for investors to potentially capitalize on this market anomaly and achieve supra-normal returns.Originality/valuePrice clustering, the phenomenon where certain price levels are traded more frequently, challenges the efficient market hypothesis and has been extensively studied in financial markets. However, the Scandinavian stock markets, particularly those in the Nasdaq Nordic Exchange, remain unexplored in this context.