| Abstract: | 特幣是一種使用區塊鏈技術為基礎的加密虛擬貨幣，因其蘊含與傳統貨幣不同的新穎概念，受到了全球金融市場和媒體的極大關注，比特幣不僅成為金融市場上支付、投資或避險的工具，更成為數位金融科技熱潮下資產數位化的重要實例。本研究的主要目的就是分析比特幣交易市場的複雜度，以便了解比特幣市場交易價格的動態變化中是否存在著富有意義的結構，並研究在世界經濟及比特幣歷史上重大事件的發生，是否會影響到比特幣市場的交易價格。本研究使用了2010年07月31日至2018年07月31日的比特幣價格資料做為樣本，並視比特幣市場交易價格的變動為一個非線性的時間序列。但因比特幣交易價格的資料為一個較短的時間序列，所以本研究中使用修正後的多尺度熵來分析比特幣交易市場中的複雜度，並將其與白雜訊及粉紅雜訊做比較。本研究另外也使用多尺度的潘凱圖來對比特幣交易價格之時間序列進行圖形的分析，以了解其中的自我相似性。而由在修正後的多尺度熵資料分析的結果中顯示，比特幣市場的複雜度非常的低，表示比特幣市場與白雜訊相似，是一個較為隨機的時間序列。再對照多尺度潘凱圖分析的結果，也顯示出比特幣市場價格的自我相似性相當的低，是類似於白雜訊的隨機時間序列，證明我們使用這兩個方法的結果是相互吻合的。在另一項研究結果中我們也發現，在歷史上發生的重大事件，會影響到比特幣市場的活絡程度。整體而言，本論文的研究顯示比特幣交易價格的變動走勢是一個複雜度低、隨機性較高、自我相似度低、未來可預測性也較低的時間序列，同時比特幣市場與交易價格也容易受到事件的影響而波動。
Bitcoin, a cryptocurrency based on the application of blockchain technology, has attracted great attention from the global financial market and media for its novel concept different from traditional currencies. Bitcoin has become not only an instrument for payment, investment or risk aversion in the financial market, but also an important case of asset digitization in the context of the boom of digital finance technology. The purpose of the study was mainly to analyze the complexity of Bitcoin trading market, to facilitate understanding whether there is meaningful structure in the dynamic changes of Bitcoin market trading price and studying whether the occurrence of significant events in the world economy and the history of Bitcoin will affect Bitcoin market trading price. In the study, Bitcoin price data during the period from 31 July 2010 to 31 July 2018 were used as samples, and changes in Bitcoin market trading price were regarded as a non-linear time series. Bitcoin trading price data were a short-term time series, therefore, modified multiscale entropy was used in the study to analyze the complexity of Bitcoin trading market and compare with white noise and pink noise. In addition, multiscale poincaré plots were used in the study to implement graphic analysis to the time series of Bitcoin trading price, so as to understand the self-similarity herein. However, the results of data analysis using modified multiscale entropy show that the complexity of Bitcoin market is very low, which indicates that Bitcoin market is similar to white noise and is a relatively random time series. Moreover, the results of analysis using multiscale poincaré plots also show that the self-similarity of Bitcoin market price is very low, and is a random time series similar to white noise. Therefore, it has been proven that the results obtained by us applying such two methods are consistent. It is also found in another study that, the significant events occurred in the history will have an impact on the liquidity of Bitcoin market. Overall, the study shows that changes and movements of Bitcoin trading price is a time series featuring a low complexity, a high randomness, a low self-similarity and also a low future predictability. In addition, both Bitcoin market and trading price are prone to be affected by events. |
