Examining the Relationship Between Market Efficiency and Behavioral Biases in Cryptocurrency Trading Activities
Posted: Sep 19, 2022
Abstract
The emergence of cryptocurrency markets has presented a unique laboratory for examining financial market theories under conditions of extreme volatility, limited regulation, and novel technological infrastructure. Traditional efficient market hypothesis, which posits that asset prices fully reflect all available information, has faced significant challenges when applied to cryptocurrency ecosystems. These digital asset markets exhibit characteristics that deviate substantially from conventional financial markets, including 24/7 trading, global accessibility, and the absence of traditional market makers. This research addresses the fundamental question of how behavioral biases interact with market efficiency in these emerging financial ecosystems. Cryptocurrency markets have demonstrated persistent anomalies that cannot be adequately explained by traditional financial theories. The extreme price volatility, frequent bubbles and crashes, and apparent inefficiencies present an intriguing puzzle for financial economists and behavioral scientists alike. Previous research has documented various behavioral phenomena in cryptocurrency trading, including herding behavior, disposition effects, and overreaction to news. However, the systematic relationship between these behavioral biases and market efficiency remains poorly understood. This study makes several original contributions to the literature. First, we develop a novel methodological framework that integrates multiple analytical approaches to quantify behavioral biases and market efficiency simultaneously. Second, we introduce the concept of behavioral efficiency coefficients that capture the dynamic interplay between cognitive biases and market functioning. Third, we examine how these relationships vary across different market conditions.
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