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OBJECTIVES: This study aimed to identify subgroups of retail investors based on their engagement in trading and gambling activities, and to examine differences in involvement, demographics, substance use, impulsivity, cognitive biases, problem gambling, and disordered trading. STUDY DESIGN: Cross-sectional, population-based study using panel data. Quota sampling and post-stratification weights were applied using data from a prior population-based random digital dial telephone survey. METHODS: Data were collected from 1,429 Spanish adults (aged 18-64). Participants reported involvement in trading of 8 financial instruments (e.g., cryptocurrencies, stocks, ETFs) and 12 gambling (e.g., lotteries, sports betting) and gambling-like activities (e.g., loot boxes, skin betting). 28.6 % of respondents engaged in non-professional trading. RESULTS: Using weighted latent class analysis we identified three distinct subgroups of retail investors: crypto-traders (52.4 %), focused on cryptocurrency trading with minimal gambling; stock-traders (32 %), involved in stocks/ETFs and lotteries, and gambling-traders (15.6 %), heavily involved in high-risk trading and various gambling activities. Although gambling-traders were not the highest investors in terms of trading volume, this class exhibited the highest frequency of trading and gambling, impulsivity, gambling-related cognitive biases, rates of disordered trading, and illicit substance use. 24.9 % of gambling-traders scored for problem gambling (PGSI≥8), compared to 0.5 % of crypto-traders and 3.5 % of stock-traders. CONCLUSIONS: Not all retail investors seem to extend their gambling behaviors to financial markets; however, those with higher impulsive traits and gambling-related cognitive biases tend to combine trading with gambling. This combination is strongly associated with problem gambling and disordered trading.
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Coloma‐Carmona et al. (2025) studied this question.
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