隔夜是指股市收盤後至隔日開盤前的非交易時段，日內則是開盤後至收盤前的交易時段。隔夜相對日內，有較低的成交量、流動性與波動性，且由於訊息多在日內公佈，因此隔夜相對來說存在較少資訊。過去多有文獻指出，股市存在明顯的隔夜效應。隔夜效應為隔夜報酬與日內報酬的反轉關係，亦即正(負)的隔夜報酬會伴隨負(正)的日內報酬。本研究認為虛擬貨幣雖為24小時連續交易，但因投資人間的資訊不對稱，也可能存在「隔夜效應」。根據成交量與成交筆數，以及美國投資人的生理睡眠時間，大膽假設出虛擬貨幣市場的開收盤時間，將「隔夜」定為22:31-5:59，「日內」定為6:00-22:30。

為進一步分析虛擬貨幣市場投資人交易行為，本研究依據每日總交易量(BTC)將投資人分為大、中、小戶，以各時段成交量佔所屬類型投資人類別全天總成交量來看交易時間偏好，並以各時段買賣成交量差，衡量投資人看法。研究結果發現，虛擬貨幣市場較股市，較傾向於「隔夜」與「日內」間發生動能現象。同時，虛擬貨幣市場24小時皆為大戶驅動，雖存在交易時段偏好，然而小戶影響力不足以造成市場反轉，因此本研究認為虛擬貨幣市場不存在「隔夜效應」。

進一步思考，隔夜效應本質上就是隔夜與日內報酬的動能、反轉現象。比較虛擬貨幣市場動能與反轉的影響因素，相同之處在於，兩者皆不受投機性影響。相異之處有五點，首先，動能現象多發生於「隔夜」報酬上漲與極端漲跌時。反轉現象多發生於「隔夜」報酬下跌與非極端漲跌時。其次，動能現象與投資人關注度呈顯著負相關，反轉現象則與投資人關注度無顯著關係。其三，動能現象與從眾行為無顯著關係，反轉現象則與從眾行為呈顯著負相關。其四，動能現象與波動度無顯著關係，反轉現象則與波動度呈顯著負相關。其五，動能現象與大戶交易比例呈顯著負相關，反轉現象則與大戶交易比例無顯著關係。顯示投資人關注度增加，波動度增加，大戶交易比例下降時，市場投機交易增加，HAM模型假設，投機交易者在市場波動度大時，較傾向動能交易，因此減弱反轉現象。

本研究為首次使用比特幣地址交易資料，將地址依據每日總交易量(BTC)分為大中小戶，並分析其交易行為如何影響虛擬貨幣市場「隔夜效應」。同時亦補充虛擬貨幣市場動能與反轉的影響因素。

Overnight refers to the non-trading period after stock market closes to the opening of the next day, and intraday refers to the trading period from the opening to the closing of the market. Relative to intraday, there is lower trading volume, liquidity and volatility, and since most information is announced in the day, there is relatively less information during overnight. Past literature pointed out that the stock market had an obvious overnight return effect. Overnight return effect describes the negative relation between overnight returns and intraday returns, that is, positive (negative) overnight returns will be accompanied by negative (positive) intraday returns. Although cryptocurrency market is continuously traded for 24 hours, there may also be an "overnight return effect" due to information asymmetry among investors. Based on the trading volume and the number of transactions, as well as the physiological sleep time of American investors, we assume the opening and closing time of the cryptocurrency market, set "overnight" as 22:31-5:59, and "intraday" as 6:00 -22:30.

In order to analyze the trading behavior of investors in the cryptocurrency market, we divides investors into large, medium and small investors based on the total daily trading volume (BTC).The results of the study found that cryptocurrency market is more likely to be momentum between "overnight" and "intraday" than stock market. Moreover, price of cryptocurrency market is driven by large investors all day. Although there are trading time preference difference between investors, the influence of small investors is still not enough to cause a market reversal. Therefore, we believe that there is no "overnight return effect" in the cryptocurrency market.

Furthermore, "overnight return effect" is essentially the momentum and contrarian of "overnight" and "intraday" returns. Comparing the determinants of the momentum effect and contrarian effect in cryptocurrency market, they both are not affected by speculative trading. There are five differences. First of all, momentum effect often occurs during positive "overnight" and extreme rises and falls. Contrarian effect occurs mostly during negative "overnight" returns and non-extreme rises and falls. Secondly, momentum effect has a significant negative correlation with investor attention, while contrarian effect has no significant relationship with investor attention. Third, there is no significant relationship between momentum effect and the herding behavior, and contrarian effect is significantly negatively related to the herding behavior. Fourth, momentum effect has no significant relationship with volatility, while contrarian effect has a significant negative relationship with volatility. Fifth, momentum effect is significantly negatively correlated with the proportion of large-scale transactions, while contrarian effect has no significant relationship with the proportion of large-scale transactions. It shows that when investor attention increases, volatility increases, and the proportion of large-scale transactions decreases, market speculative trading increase. According to the HAM model, speculative traders tend to trade with momentum when the market is volatile, thus weakening contrarian effect.

This study is the first time to use bitcoin address transaction data to divide addresses into large, medium and small accounts based on the total daily transaction volume (BTC), and analyzes how their transaction behavior affects the "overnight return effect" of the cryptocurrency market. Moreover, we also find out the determinants of the momentum effect and contrarian effect in the cryptocurrency market.

論文審定書 i
誌謝 ii
摘要 iii
Abstract iv
目錄 vi
圖次 viii
表次 x
第一章、前言 1
1.1 研究背景與動機 1
1.2 研究目的 10
1.3 貢獻與研究結果 10
第二章、文獻回顧 11
2.1 隔夜效應之相關文獻 11
2.2 虛擬貨幣市場的本質 12
2.3虛擬貨幣市場投資人行為 13
2.4 影響虛擬貨幣市場價格之因素 16
2.5 文獻回顧總結與本文發展 18
第三章、研究假說 20
第四章、研究方法 22
4.1 資料來源 22
4.2 虛擬貨幣市場隔夜定義 22
4.3 虛擬貨幣市場大中小戶定義 24
4.4 被解釋變數 25
4.4.1 隔夜效應之衡量 25
4.4.2 動能與反轉之衡量 25
4.5影響虛擬貨幣市場隔夜效應的因素 26
4.5.1行為面變數26
4.5.2微結構面變數 27
4.5.3 投資人結構變數 28
4.5.4 投資人看法歧異性之衡量 28
4.6 實證模型 29
第五章、敘述統計 34
5.1 股市及虛擬貨幣市場報酬 34
5.2股市敘述統計 41
5.2.1股市隔夜效應敘述統計 41
5.2.2股市各面向因素敘述統計 41
5.3虛擬貨幣市場敘述統計 46
5.3.1虛擬貨幣市場24小時型態 46
5.3.2虛擬貨幣市場投資人行為 51
5.3.3虛擬貨幣市場「隔夜效應」敘述統計 61
5.3.4虛擬貨幣市場各面向變數敘述統計 62
第六章、實證結果 69
6.1虛擬貨幣是否存在隔夜效應 69
6.2影響股市隔夜效應強度之因素 72
6.3影響虛擬貨幣市場「隔夜效應」強度之因素 74
6.3.1多元迴歸模型 74
6.4預測隔天虛擬貨幣市場「隔夜效應」強度之因素 77
6.4.1多元迴歸模型 78
6.4.2機器學習模型(預測) 79
6.5影響虛擬貨幣市場「隔夜」與「日內」動能之因素 80
6.5.1羅吉斯回歸模型 80
6.6預測虛擬貨幣市場「隔夜」與「日內」動能之因素 83
6.6.1羅吉斯迴歸模型 83
6.6.2機器學習模型(預測) 85
第七章、結論 86
7.1研究結果總結 86
7.2研究限制與後續研究方向 89
參考文獻 90

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