The Research Department of Economics and Management of Tadbir Nikan Business, Marketing, and Finance Open 3092-6238 In Press 2027 07 01 Investor Sentiment and Cryptocurrency Market Volatility: Evidence from High-Frequency Digital Asset Data Investor Sentiment and Cryptocurrency Market Volatility: Evidence from High-Frequency Digital Asset Data 1 18 EN Journal Article 2026 03 26 <p>This study aimed to examine the relationship between investor sentiment and cryptocurrency market volatility by integrating survey-based sentiment data from active cryptocurrency investors in Tehran with high-frequency digital asset market data. This quantitative explanatory-correlational study was conducted among 384 active cryptocurrency investors residing in Tehran who were selected through purposive sampling based on trading experience and direct involvement in digital asset investment. Investor sentiment was measured using a structured questionnaire assessing optimism, fear of loss, risk appetite, herding tendency, overreaction to market news, and speculative enthusiasm. High-frequency market data were collected at five-minute intervals for Bitcoin, Ethereum, Binance Coin, Solana, and Ripple over a 90-day observation period. Market variables included log returns, absolute returns, trading volume, bid-ask spread, and realized volatility. Data were analyzed using descriptive statistics, Pearson correlation, GARCH(1,1) volatility modeling, fixed-effects panel regression, and hierarchical regression analysis. Investor sentiment was positively and significantly correlated with realized volatility (r = 0.46, p &lt; 0.01), absolute log return (r = 0.38, p &lt; 0.01), trading volume (r = 0.31, p &lt; 0.01), and bid-ask spread (r = 0.22, p &lt; 0.01). The GARCH(1,1) model showed significant ARCH (β = 0.184, p &lt; 0.001) and GARCH effects (β = 0.741, p &lt; 0.001), confirming volatility clustering and persistence. Investor sentiment significantly increased conditional volatility (β = 0.057, p &lt; 0.001). Fixed-effects regression showed that speculative enthusiasm, overreaction to market news, fear of loss, herding tendency, and optimism significantly predicted realized volatility. Hierarchical regression indicated that investor sentiment added 11% explanatory power beyond market indicators. The findings demonstrate that investor sentiment is a significant behavioral determinant of cryptocurrency market volatility. Sentiment-driven optimism, fear, herding, and news overreaction intensify short-term instability in digital asset markets beyond the effects of conventional market variables.</p> https://bmfopen.com/index.php/bmfopen/article/download/508/362