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In this study, we investigate what drives the MAX effect in the South Korean stock market. We find that the MAX effect is significant only for overpriced stocks categorized by the composite mispricing index. Our results suggest that investors' demand for the lottery and the arbitrage risk effect of MAX may overlap and negate each other. Furthermore, MAX itself has independent information apart from idiosyncratic volatility (IVOL), which assures that the high positive correlation between IVOL and MAX does not directly cause our empirical findings. Finally, by analyzing the direct trading behavior of investors, our results suggest that investors' buying pressure for lottery-like stocks is concentrated among overpriced stocks.

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.

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.

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.

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.

We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.

Behavioral economics poses a challenge for the welfare evaluation of choices, particularly those that involve risk. It demands that we recognize that the descriptive account of behavior toward those choices might not be the ones we were all taught, and still teach, and that subjective risk perceptions might not accord with expert assessments of probabilities. In addition to these challenges, we are faced with the need to jettison naive notions of revealed preferences, according to which every choice by a subject expresses her objective function, as behavioral evidence forces us to confront pervasive inconsistencies and noise in a typical individual’s choice data. A principled account of errant choice must be built into models used for identification and estimation. These challenges demand close attention to the methodological claims often used to justify policy interventions. They also require, we argue, closer attention by economists to relevant contributions from cognitive science. We propose that a quantitative application of the “intentional stance” of Dennett provides a coherent, attractive and general approach to behavioral welfare economics.

Risk preferences play a critical role in almost every facet of economic activity. Experimental economists have sought to infer the risk preferences of subjects from choice behavior over lotteries. To help mitigate the influence of observable, and unobservable, heterogeneity in their samples, risk preferences have been estimated at the level of the individual subject. Recent work has detailed the lack of statistical power in descriptively classifying individual subjects as conforming to Expected Utility Theory (EUT) or Rank Dependent Utility (RDU). I discuss the normative consequences of this lack of power and provide some suggestions to improve the accuracy of normative inferences about individual-level choice behavior.

This study aims to examine the relationship between investor gambling preferences and stock returns, using data for all firms listed in Shanghai A-share market during 2016 and 2021.

This study employs price and trading volume data to capture the behavioral characteristics and gambling preferences of investors. Using the Fama-French three-factor and five-factor models to estimate benchmark returns, this study investigates whether investing in gambling stocks can yield positive excess returns.

The study reveals that stocks identified as gambling stocks generate high returns in the month they are identified as such but subsequently experience a significant drop in excess returns compared to non-gambling stocks over the following one to six months. These results are found to be consistent across different methods used to classify gambling stocks and across various industry sectors.

This research provides insights into the risk-return tradeoff of different stock types and the factors that fuel irrational investment behavior. This research underscores the importance of considering the behavioral elements of investment, particularly in emerging markets where individual investors have a significant impact.

This study advises investors to avoid adopting a gambler or speculative mindset and instead make well-informed and calculated investment decisions that are in line with investors financial objectives and risk appetite. This approach can help create a more stable and sustainable financial market.

This study provides new evidence on the relationship between gambling preferences and future stock returns in financial markets and sheds new light on the important role of irrational factors in investment decisions.

Storytelling through virtual reality (VR) combines the strengths of cutting-edge technology with traditional informational campaigns. As a tool for climate change mitigation, VR has been shown to educate individuals and stimulate both emotional and cognitive responses that promote pro-environmental behavior. This paper aims to investigate whether these benefits extend to the field of green investing through an experiment conducted with a sample of small business entrepreneurs.

The experimental design involved making choices between bonds varying in maturity dates, annual interest and environmental classification (regular versus green). To identify potential impacts of the immersive experience on investment decisions, these choices were made both before and after exposure to VR videos illustrating the devastating effects of climate change. A multiple price list was employed to elicit subjects' risk preferences, enabling the joint estimation of the treatment effect and the risk and time preference parameters.

The findings indicate that, when risk and time preference parameters are controlled for, a VR experience can nudge toward green investment choices. This effect is more profound among those who already exhibit a greater propensity to opt for green investments.

Previous research shows that negative emotions, such as guilt, affect pro-environmental intentions, as well as actions, while message vividness through immersive experiences is effective in nudging greener behavior. Since analogous results in the framework of financial investments are not currently available, this paper seeks to test whether VR videos depicting the adverse effects of climate change can generate negative emotions associated with experiencing these effects and make them salient in subsequent investment decisions made by small business entrepreneurs.

The authors aim to understand the driving forces behind the idiosyncratic volatility puzzle in the Korean stock market. The authors study the Korean stock market because previous works report a strong idiosyncratic volatility puzzle in Korea, and the market for the exchange-traded funds (ETFs) including low volatility ETFs has experienced drastic growth in Korea.

Using common stocks listed either on KOSPI or KOSDAQ over the period 1997–2016, the authors estimate idiosyncratic volatility using the Fama–French three-factor model. In addition, based on prior literature, the authors use turnover as a proxy for overvaluation. The authors then study the role of turnover in understanding the idiosyncratic volatility puzzle in Korea.

The authors find that turnover is highly associated with idiosyncratic volatility. Turnover is extremely large among firms with high idiosyncratic volatility and the puzzle disappears after we control for turnover, meaning that turnover subsumes the explanatory power of idiosyncratic volatility for equity returns. The authors also find underperformance of stocks with high turnover and high idiosyncratic volatility exclusively during earnings announcement periods. Overall, our finding implies that the puzzle arises since high idiosyncratic volatility stocks due to high turnover are overvalued and experience correction afterwards.

Literature has suggested explanations based on lottery preferences of investors and market frictions behind the idiosyncratic volatility puzzle. What makes our study distinct from previous work is that we find the role of turnover in understanding the idiosyncratic volatility puzzle using turnover measure as a proxy for overvaluation in the Korean stock market.

An estimated 1.2 million students gamble, equating to approximately two in every three students. In the UK, university students have reached the legal age to gamble; many have received significant sums of financial support and will be responsible for managing their own finances. Some UK universities have acknowledged that students engage in gambling activity and the need to provide gambling-related support. However, more research is needed to better understand student gambling activities and how universities can optimise provision of support. The purpose of this study was to enhance this understanding.

A total of 210 university students completed an online survey to provide details of their gambling behaviour and views on the types of support that they felt would best support students.

Both gambling and non-gambling students reported a preference for specialised gambling-related support within student services without the requirement for gambling-focused workshops (p < 0.01). Follow-up analysis revealed a significantly greater proportion of females did not gamble (p < 0.01), that males spent more money when gambling (p < 0.01) and were higher risk gamblers than females (p < 0.01).

These results provide evidence for gambling support to feature overtly as part of university support and well-being services.

Previous literature shows that market sentiment and the steepness of index option's implied volatility slope have a negative relation. This paper investigates the relation between firm-specific sentiment and individual option's implied volatility slope both theoretically and empirically.

The authors develop a simple model with option traders' sentiment heterogeneity to show that sentiment and the steepness of individual option's implied volatility slope have a positive relation.

When firm-specific sentiment is higher (more bullish), individual option's implied volatility slope becomes steeper. The positive relation is stronger when option traders' beliefs on risk are more dispersed. Empirical results support the theoretical model predictions.

Although both firm-specific sentiment and individual options implied volatility slope predict future stock returns, there is no research exploring the relation between them. In particular, none of previous studies associates implied volatility slope's stock return predictability to investor behavior such as sentiment. The authors’ findings provide a behavior-based explanation on why steep implied volatility slope negatively predicts cross-sectional stock returns.