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研究生(外文):Chang, Tun-Hsiang
論文名稱(外文):Long-term and Short-term Interaction among Cryptocurrencies, Stablecoins and Financial Markets
指導教授(外文):Lin, Chien-Hsiu
口試委員(外文):Liao, Szu-LangChen, Chih-NanTsai, Hung-Pin
外文關鍵詞:CryptocurrencyStablecoinARDLCointegration AnalysisError Correction Model
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從加密貨幣問世以來,透過去中心化與不受政府監管的特點博取廣大市場投資者的興趣,在這波浪潮下,關於加密貨幣的研究也如雨後春筍般產出。然而,近年來,儘管加密貨幣與傳統金融市場的低相關性或對沖風險能力逐漸獲得認可,但其極大的波動幅度也常使眾人卻步。為了改善這項缺點,與具備穩定價格的資產掛勾的穩定幣便應運而生,以加密貨幣資金避風港的角色於2014年開始發行。COVID-19爆發之後,隨著美國重啟量化寬鬆政策(Quantitative easing)與接連降息刺激經濟,大量資金流入市場推升加密貨幣價格,紛紛創下歷史新高。但就在2022年3月美國聯準會宣布恢復升息循環與縮表以打擊居高不下的通貨膨脹後,加密貨幣整體市值出現急遽下滑,也讓穩定幣再度浮上檯面。
本文有別於過往文獻,將加密貨幣與穩定幣一同放入比較,觀察兩者對於傳統金融市場、商品以及不同變數間的反應。研究方法則首先以單根檢定確認變數序列有無呈現定態(Stationary),再結合ARDL(Autoregressive Distributed Lag Model)模型與Pesaran and Shin (1999)與Pesaran et al. (2001)所提出的 Bound Testing檢定加密貨幣、穩定幣和解釋變數間是否存在長期共整合關係,同時利用誤差修正模型(Error Correction Model)來識別短期互動方向,最後分別探討COVID-19疫情前後彼此間關聯是否發生變化。
Since the emergence of cryptocurrency, its decentralized and unregulated features have attracted the interest of many investors, leading to a surge of research on the topic. Despite the low correlation or hedging ability of cryptocurrencies with traditional financial markets, their high volatility has often made investors cautious. To address this issue, stablecoins linked to assets with stable prices were introduced in 2014 to serve as a safe haven for cryptocurrency. After the outbreak of COVID-19, the injection of massive amounts of funds into the market by the US government's quantitative easing policy and consecutive rate cuts pushed up the prices of cryptocurrencies, setting new historical highs one after another. But in March 2022, the Federal Reserve announced the resumption of interest rate hikes and balance sheet reduction to combat persistent inflation. This caused a sharp decline in the overall market capitalization of cryptocurrencies, and brought stablecoins back into the spotlight.
Unlike previous literature, this paper compares both cryptocurrencies and stablecoins, examining their reactions to traditional financial markets, common trading assets, and different variables. The research method first confirms the stationarity of variable sequences using the unit root test, then combining the ARDL (Autoregressive Distributed Lag Model) model with the Bound Testing proposed by Pesaran and Shin (1999) and Pesaran et al. (2001) to investigate the existence of long-term cointegration relationships among cryptocurrencies, stablecoins, and explanatory variables. The Error Correction Model is used to identify short-term interactive directions, and the changes in their correlation before and after the COVID-19 pandemic are separately explored.
Empirical results show that cryptocurrencies have limited hedging benefits for investment portfolios in the long run, regardless of their interactions with interest rates, hedge assets such as gold, or the short-term interaction with the VIX index. On the other hand, stablecoins not only provide traders with a safe haven during adverse cryptocurrency market conditions, but also attract capital inflows during bear markets or market panic in the short term. Moreover, the link between stablecoins and interest rates underwent a change after the pandemic, making them more appealing to investors as a safe haven. However, as cryptocurrencies and stablecoins are still emerging fields, their market confidence is highly affected by negative news, and buyers need to remain vigilant.
摘要 ii
Abstract iii
目次 v
表次 vi
圖次 viii
第一章 緒論 1
第一節 研究背景 1
第二節 研究動機與目的 4
第三節 研究架構 5
第二章 文獻回顧 7
第三章 研究資料與方法 10
第一節 資料選擇 10
第二節 變數間預期方向 11
第三節 單根檢定 13
第四節 ARDL/Bound Testing 15
第四章 實證分析與結果 20
第一節 敘述統計 20
第二節 單根檢定結果 23
第三節 ARDL/Bound Testing實證結果 29
第四節 短期ARDL結果 41
第五章 結論 46
參考文獻 48
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