加密貨幣市場泡沫特徵與檢測方法研究

Abstract

新冠疫情的爆發促進了加密貨幣市場的顯著增長，市場呈現高度波動與頻繁劇烈的價格震盪，識別和分析加密貨幣市場中的泡沫現象儼然成為投資者、研究者與監管單位的關注焦點。本研究選取市值排名前三的加密貨幣：比特幣、以太幣與幣安幣作為研究對象，並應用Phillips, Wu 與 Yu (2011, PWY) 提出的 supremum augmented Dickey–Fuller (SADF) 檢定與 Phillips, Shi與Yu (2015a, PSY) 提出 generalized SADF (GSADF) 檢定方法進行泡沫檢測，並透過backward SADF (BSADF) 檢定標記出泡沫發生日期。研究結果顯示，這些加密貨幣在樣本期間內均被檢測出多次泡沫。儘管這些檢定能有效識別部分泡沫，但在面對加密貨幣價格複雜且變化劇烈的序列特徵時，PWY(2011) 與 PSY(2015a) 所提出的泡沫偵測模式的應用價值仍有所局限，這一缺失有待進一步改進。然而，這些模型仍然為投資者提供了具有價值的預警資訊。此外，本研究亦發現，加密貨幣價格易受市場情緒、新聞事件以及政策變動的影響。

The COVID-19 pandemic has significantly accelerated the growth of the cryptocurrency market, characterized by high volatility and frequent dramatic price fluctuations. Identifying and analyzing bubbles in this market has become a critical concern for investors, researchers, and regulatory authorities. This study focuses on the top three cryptocurrencies by market capitalization: Bitcoin (BTC), Ethereum (ETH), and Binance Coin (BNB). We employ the supremum augmented Dickey-Fuller (SADF) test proposed by Phillips, Wu, and Yu (2011, PWY), the generalized SADF (GSADF) test by Phillips, Shi, and Yu (2015a, PSY), and the backward SADF (BSADF) test to date the occurrence of bubbles. Our findings reveal multiple bubbles in these cryptocurrencies during the sample period. Although these tests effectively identify some bubbles, the complex and highly volatile nature of cryptocurrency price sequences limits their utility, indicating a need for further investigation. Despite these limitations, these models still provide valuable early warning signals for investors. Additionally, our study finds that cryptocurrency prices are influenced by market sentiment, news events, and policy changes, highlighting the multifaceted dynamics of this emerging market.