The aim of this research is to analyze the relationship between the MAX effect and the sentiment associated with the news in the cryptocurrency market.
The study uses natural language processing to build the sentiment indicator derived from news headlines about cryptocurrencies. Further, a survey-based sentiment indicator is also utilized. The study undertakes analysis at both the portfolio level (Decile analysis) and at the cross-sectional level (using the Fama-Macbeth Regression).
The results demonstrate a positive MAX effect in the cryptocurrency market. When the investor sentiment interacts with the MAX effect, the positive MAX effect continues to exist. However, the strength of the MAX coefficient decreases, suggesting that the sentiment factor drove the standalone MAX effect to a large extent. Further, small-sized and low-priced cryptocurrencies tend to showcase lottery anomaly higher than their counterparts. The availability heuristic is higher in small-cap cryptocurrencies. Due to loss aversion bias, the negative sentiment does not lead to a negative MAX effect.
It will be useful for the growing investor base in the cryptocurrency market in devising investment strategies.
The study presents empirical evidence on the impact of behavioral variables on the MAX effect. The study examines the interplay of cryptocurrency investor sentiment and the MAX effect using three novel sentiment proxies.
