近年來，虛擬貨幣盛行，比特幣為虛擬貨幣之母，比特幣價格不斷攀升，在2017年年底，比特幣價格來到歷史高點，當時正是比特幣期貨上市，隨後比特幣價格下跌，比特幣波動幅度大。本篇論文主要探討比特幣期貨的避險比率，以天真避險(Naïve hedge)、普通最小平方法(Ordinary Least Squares)和雙變量BEKK GJR GARCH (Bivariate BEKK GJR GARCH)模型，採用這三種方法進行比特幣期貨避險，分析何種方法避險效果較好。此外，探討比特幣與比特幣期貨之間的關係，運用GARCH (1,1)與Harnett和 Soni (1991)書上提出的統計方法，分析比特幣的波動度是否受到比特幣期貨上市而改變。本篇論文結果顯示，雙變量BEKK GJR GARCH模型的避險效果較好及比特幣的波動度會受到比特幣期貨上市的影響。

The goal of this study is to analyze the hedge ratio about Bitcoin Futures (BTC) and use three different hedge strategies to compare which method is the best. We use Naïve hedge, Ordinary Least Squares (OLS), and Bivariate BEKK GJR GARCH model to estimate the hedge ratio. The other aim is to investigate the relationship between Bitcoin and Bitcoin Futures (BTC). We use GARCH (1,1) and the statistical methods proposed by Harnett and Soni (1991) to test whether the volatility of Bitcoin would change before and after Bitcoin Futures (BTC) launched. Data of CME CF Bitcoin Reference Rate (BRR), CME Group Bitcoin Futures (BTC) from Thomson Reuters Eikon (Eikon) database, and the price and return of Bitcoin on the Bitstamp, Coinbase, itBit, and Kraken exchanges from Bloomberg database are used in this study. The results show that the hedge ratios by using the Bivariate BEKK GJR GARCH model in this paper is a good choice. In addition, the volatility of Bitcoin is influenced by the launch of Bitcoin Futures.

摘要...........................................i
ABSTRACT......................................ii
誌謝辭.......................................iii
CONTENTS......................................iv
1. Introduction................................1
2. Data........................................3
3. Methodology.................................4
3.1 Hedge ratios...............................4
3.2 GARCH (1,1) and Two sample t test..........6
4. Empirical Results...........................7
5. Conclusions.................................9
References....................................10
List of Tables and Figures....................12

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