نوع مقاله : مقاله پژوهشی
نویسندگان
گروه مهندسی مالی،دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران.
کلیدواژهها
موضوعات
عنوان مقاله English
نویسندگان English
Purpose: This study examines the impact of salience theory on the cross-sectional return predictability of cryptocurrencies and evaluates it as a risk factor in asset pricing. The study seeks to analyze the role of investor behavioral biases in shaping return fluctuations in the cryptocurrency market.
Methodology: Using data from over 4,000 cryptocurrencies with a market capitalization above one million USD during the period from January 2014 to June 2025, a Salience theory was constructed based on the difference between salient weighted returns and average value-weighted returns. The empirical analysis was conducted through portfolio sorting, Fama-MacBeth regressions, and the Liu-Tsyvinski-Wu three-factor model.
Findings: The results show that cryptocurrencies with salient positive returns tend to underperform in subsequent periods, whereas those with salient negative returns tend to yield higher future returns. The effect of the ST index is statistically and economically significant and remains robust after controlling for other behavioral and fundamental factors. The index also explains well-known anomalies such as skewness preference, prospect theory, and downside beta.
Originality/Value: This study is the first to introduce the ST index as a novel and effective behavioral factor in the cryptocurrency market. The findings demonstrate its strong predictive power and its ability to explain cross-sectional pricing patterns, outperforming traditional models and other behavioral factors.
کلیدواژهها English
