Investor Psychology and Sentiment Analysis in Cryptocurrency Markets: A Behavioral Finance Approach
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Behavioral Finance, Investor Sentiment, Market Volatility
Abstract
The volatility of cryptocurrency markets has attracted growing attention from scholars seeking to understand how psychological and emotional factors shape investor behavior. Behavioral finance provides a theoretical foundation to explain deviations from rational decision-making, particularly in environments driven by speculation, social influence, and technological uncertainty. This study aims to examine the relationship between investor sentiment, psychological bias, and market dynamics within cryptocurrency trading using a behavioral finance approach. The research employs a mixed-method design, combining quantitative sentiment analysis of social media data (Twitter, Reddit, and Telegram) with econometric modeling of market indicators such as trading volume, volatility, and price momentum. The results indicate a strong correlation between positive sentiment and short-term price surges, while fear and loss aversion significantly contribute to panic selling and extreme volatility. Investor psychology, particularly herd behavior and overconfidence, is shown to amplify market cycles beyond fundamental valuations. The findings confirm that behavioral variables exert a measurable and systematic influence on cryptocurrency market movements. The study concludes that integrating psychological and sentiment metrics into financial modeling enhances predictive accuracy and provides critical insights for investors and policymakers seeking stability in digital asset markets.
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References
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