SOCIAL MEDIA SENTIMENT AND ITS EFFECTS ON CRYPTOCURRENCY PRICE VOLATILITY

Purpose- Following its introduction in 2008, cryptocurrencies have attracted great deal of attention from the investors. Cryptocurrency market have grown rapidly in terms of transaction volumes and number of investors involved with the launch of different kinds of alternative coins (altcoins). Cryptocurrency markets show some differences from the stock market with less institutional investor involvement. With the high proportion of retail investors in the market, we assume sentiment would be one of the leading forces that can accelerate cryptocurrency price movements in both directions that leads to higher volatilities. In this study, we try to shed a light on social media sentiment and its effect on cryptocurrency price volatility for 9 different cryptocurrencies, namely Bitcoin, Ethereum, Ripple, Binance Coin, Dogecoin, Solana, Cardano, Litecoin, Avax. Methodology- The study uses Google search volume index and number of tweets weekly collected from Twitter between the dates January 2020 to March 2023 as investor attention measures to attract social media sentiment in addition to economic policy uncertainty index (EPU), CBOE S&P 500 implied volatility index (VIX) and macro and micro indexes constituted by using the Google search volume indexes for micro and macro fears and taking the weekly sum of those indexes. We investigated investor attention measures and mentioned indexes’ impact on cryptocurrency volatility by using seemingly unrelated regression. Findings- The analysis reveals that google search volume index has a significant positive impact on volatility of cryptocurrencies in addition to economic policy uncertainty index and micro pessimism measures. Number of tweets data has no significant impact on volatility in contrast to Google search volume index. Conclusion- Based upon the analysis, it may be concluded that google search volume index has better captured investor attention and might give an insight regarding cryptocurrency volatilities where number of tweets collected from Twitter has no significant impact on volatilities. Keywords: Cryptocurrency, investor attention, social media sentiment, Google Search Volume Index, Uncertainty Index JEL Codes: G10, G14,L86