在加密貨幣市場中，虛假交易活動是常見的詐欺活動之一，虛假交易的存在使得加密貨幣市場交易資訊不被信任，嚴重影響市場流動性特徵，使投資人誤判交易成本。過去的文獻研究主要聚焦在交易所的詐欺行為，然而虛假交易可能存在於特定加密貨幣中，因此本研究參考Cong, Li, Tang, Yang (2021)的研究方法，旨在找出可能含有虛假交易行為的加密貨幣，進而探討存在虛假交易的加密貨幣是否存在族群的特徵差異，並提供給投資人一個判別虛假交易貨幣的依據，以避免投資人受到非法行為的影響而蒙受投資損失。本研究之研究期間自2018年1月至2023年1月，篩選後合計共500個樣本，發現樣本內共有291個虛擬交易貨幣，研究結果發現虛假交易貨幣的市場交易對、網站排名等基本特徵較非虛假交易貨幣大，市值、流動性估計量等市場特徵的族群差異則相對不明顯。

In the cryptocurrency market, wash trading activities are among the common fraudulent practices. The existence of wash trading undermines the trustworthiness of transaction information in the cryptocurrency market, significantly impacting market liquidity characteristics and causing investors to misjudge transaction costs. Previous research primarily focused on fraudulent behaviors in exchanges. However, wash trading may exist within specific cryptocurrencies. Therefore, this study refers to the research methodology of Cong, Li, Tang, Yang (2021) with the aim of identifying cryptocurrencies that may have false trading activities. It further investigates whether cryptocurrencies with wash trading exhibit distinct characteristics among different populations. The study aims to provide investors with a basis for identifying cryptocurrencies with wash trading, thus avoiding investment losses due to illegal activities. The study period for this research spans from January 2018 to January 2023, with a total of 500 samples after screening. Among these samples, 291 currencies were found to have wash trading. The research findings indicate that cryptocurrencies with wash trading have larger market capitalization, higher website rankings, and other basic features compared to cryptocurrencies without wash trading. However, there is relatively little discernible population difference in market characteristics such as market capitalization and liquidity estimates.

目錄
論文審定書 i
摘要 ii
Abstract iii
目錄 iv
第一章、 緒論 1
1.1. 研究背景 1
1.2. 研究動機 4
1.3. 研究步驟 5
第二章、 文獻回顧 7
2.1. 衍生性商品對於加密貨幣市場的影響 7
2.2. 加密貨幣市場流動性 7
2.3. 加密貨幣市場虛假交易 8
2.4. 加密貨幣市場中的尾部分配 8
2.5. COVID-19期間加密貨幣的流動性和波動性 9
2.6. Benford's law在加密貨幣市場的應用 9
第三章、 研究資料與方法 10
3.1. 研究樣本篩選 10
3.2. 虛假交易貨幣判別方法 11
3.2.1 檢測成交值第一位有效數字的分佈 11
3.2.2 檢測成交值的尾部分佈 12
3.3. 流動性變數 13
3.4. 流動性變數敘述統計量 14
第四章、 判別虛假交易貨幣 16
4.1. 成交值第一位有效數字的分佈 16
4.1.1 Benford’s Law 16
4.1.2 檢測違反Benford’s Law行為 16
4.2. 成交值的尾部分佈 19
4.2.1 冪律分配 Power law distribution 19
4.2.2 檢測成交值分配有無肥尾特徵 19
第五章、 研究結果 22
5.1. 分群基本特徵分析 22
5.2. 分群市場特徵分析 25
5.3. 逐年判別虛假交易貨幣 27
5.4. 迴歸模型設計與變數說明 32
5.4.1 被解釋變數 32
5.4.2 解釋變數 32
5.4.3 控制變數 33
5.4.4 迴歸模型 33
5.5. 市場流動性迴歸模型結果 34
第六章、 研究結果 37
參考文獻 39

 
圖目錄
圖 1：第一有效位數與Benford’s Law模式 18
圖 2：有無虛假交易CMC排名分群圖 24
圖 3：有無虛假交易市場交易對分群圖 25
圖 4：每年虛假交易貨幣數量圖 27
圖 5：有無虛假交易分群市場特徵比較圖 28
圖 6：有無虛假交易分群流動性估計量比較圖 29

 
表目錄
表 1：每週拜訪率前十大加密貨幣交易所之交易量 2
表 2：加密貨幣流動性之敘述統計 15
表 3：Benford’s Law 卡方檢定 17
表 4：冪律分配擬和結果 21
表 5：有無虛假交易基本特徵敘述統計表 22
表 6：基本特徵Ｔ檢定 23
表 7：有無虛假交易族群市場特徵分析 26
表 8：市場特徵Ｔ檢定 26
表 9：逐年有無虛假交易族群流動性差異T檢定表 30
表 10：流動性估計量之最小平方迴歸分析 36

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