VOLATILITY MODELING, TRADING VOLUME AND INVESTORS SENTIMENTS: EMPIRICAL EVIDENCE FROM CRYPTO MARKET

Abstract

The primary objective of this study is to investigate cryptocurrency market volatility and how trading volume reflects the influence of investors sentiments on return and risk dynamics.  For this purpose, the study has used daily data from January 1, 2023, to March 31, 2025, for major 10 cryptocurrencies i.e BTC and other major Altcoins. Asymmetric GARCH (1,1) is used to investigate the volatility behavior, persistency and clustering patterns over time. Confidence, Optimism, Pessimism and Rational Expectation has been modeled in Mean and Variance Equation of GARCH (1,1) model simultaneously. The results conclude that fear, greed, and sentiment-driven speculation often dominate crypto price movements. Potential misspecification has also been shown. Over optimistic sentiments increases volatility and cause to decrease returns. The pessimistic attitude reflects the contrarian behavior. However, it is concluded that trade volume significantly affects the return behavior and the volatility is due to sentiments and past shocks. Further findings suggest directions to assist portfolio managers and institutional investors in developing more effective portfolio diversification and risk mitigation strategies.