以太幣價格與總體經濟變數之實證分析

Abstract

高波動性的加密貨幣市場吸引許多人的注意，2021年 NFT 與元宇宙的熱潮更是大幅推升加密貨幣的價格。現今加密貨幣已是大眾關注的焦點。 自比特幣暴漲的2017年以來，學界也開始對加密貨幣產生興趣。惟過去相關研究大多以比特幣為主題，討論以太幣價格與總體經濟變數如何互動的文獻甚少，並多未考慮 Defi 總鎖倉量對以太幣價格的影響。以太幣是以太坊的原生代幣，而以太坊與比特幣最大的差異之一在於以太坊可以在區塊上執行應用程式，Defi 總鎖倉量則顯示這些應用程式的熱門程度，因此 Defi 總鎖倉量對以太幣價格的影響必須考慮。 本文使用向量誤差修正模型分析以太幣價格與總體經濟變數之關係。模型中變數包含以太幣價格、比特幣價格、Defi 總鎖倉量、布蘭特原油期貨價格、黃金期貨價格、美元指數、日圓兌美元匯率、人民幣兌美元匯率、標準普爾500指數與 VIX 恐慌指數。實證發現變數之間存在長期均衡關係。同時也透過 Granger causality 檢視總體經濟變數是否能夠預測以太幣價格，以及利用衝擊反應函數分析各個解釋變數衝擊對以太幣價格的影響。

The cryptocurrency market, characterized by its high volatility, has attracted considerable attention. In 2021, the surge in Non-Fungible Tokens (NFTs) and the emergence of the metaverse significantly impacted cryptocurrency prices, elevating their prominence. Cryptocurrencies have become a focal point of interest, not only among the general public but also within academic circles. Since the substantial price increase of Bitcoin in 2017, scholarly interest in cryptocurrencies has grown. However, previous research has predominantly focused on Bitcoin, neglecting the examination of how Ethereum prices interact with macroeconomic variables. Additionally, the impact of the Total Value Locked (TVL) in decentralized finance (DeFi) on Ethereum prices has been largely overlooked. Ethereum, as the native token of the Ethereum blockchain, differentiates itself from Bitcoin by enabling the execution of decentralized applications (DApps). Therefore, it is crucial to consider the influence of TVL in DeFi on Ethereum prices. This study employs a Vector Error Correction Model (VECM) to analyze the relationship between Ethereum prices and macroeconomic variables. The model includes Ethereum and Bitcoin prices, TVL in DeFi, Brent crude oil futures prices, gold futures prices, the US dollar index, the Japanese yen to US dollar exchange rate, the Chinese yuan to US dollar exchange rate, the S&P 500 index, and the VIX (Volatility Index). The empirical findings reveal the existence of long-term equilibrium relationships among these variables. Granger causality tests are applied to examine the predictive power of macroeconomic variables for Ethereum prices. Moreover, impulse response functions are utilized to assess the impact of shocks from each explanatory variable on Ethereum prices.