가상화폐시장의 허딩현상 분석: 시간별 데이터를 이용하여
An Analysis of Herding in the Cryptocurrency Markets: Using Hourly Data
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본 연구는 국내 가상화폐거래소에서 거래되고 있는 가상화폐 중에서, 비트코인(BTC), 이더리움(ETH), 리플(XRP), 라이트코인(LTC), 지캐시(Zcash), 비트코인골드(BTG), 이더리움클래식(ETC), 모네로(XMR)의 일별 및 시간별 가격자료를 이용하여 허딩현상을 분석하였다. 허딩현상의 분석은 CSSD와 CSAD기법을 사용하였으며, 분석결과 하락 시장뿐만 아니라 상승 시장에서도 허딩현상이 존재함을 확인할 수 있었다. 또한, 가상화폐의 시가총액을 고려하여 비트코인을 포함하여 4개의 메이저 코인과 상대적으로 시가총액이 작은 마이너코인으로 분리하여 분석하였다. 분석결과를 살펴보면, 시장 상승기에 메이저코인에 대한 마이너코인의 허딩현상을 설명할 수 있었지만, 하락 시장에서는 메이저코인에 대한 마이너코인의 허딩현상을 설명할 수 없었다. 또한, 시가총액 비중이 가장 높은 비트코인에 대한 다른 코인들의 허딩현상을 전반적으로 명확하게 설명할 수 없었던 부분은 허딩현상이 가지는 기본적인 특성 중의 하나인 추종의 한계점을 의미한다.
Abstract
This study investigated the herding phenomenon in eight cryptocurrencies, namely Bitcoin(BTC), Ethereum(ETH), Ripple(XRP), Lightcoin(LTC), Zcash (ZEC), Bitcoin Gold(BTG), Ethereum Classic(ETC) and Monero (XMR). In this purpose, we calculated the CSSD and CSAD methods and analyzed the herding phenomenon both the bearish and bullish markets. From our empirical results, we found herding effect in both market conditions. In addition, considering the size of the cryptocurrency (major coins versus minor coins), minor coins shows the herding effect with the major coins in the bullish market, but in the bearish market. Moreover, Bitcoin does not clarify the explanation on the herding effect of other coins because the herding phenomenon is the inherent characteristic of the cryptocurrency markets.
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