Bitcoin Sentiment Index, Performance and US Dollar Exchange Rate

Econometric Modeling: International Economics eJournal Pub Date : 2020-05-10 DOI:10.2139/ssrn.3597331

Ishfaque Ahmed Soomro, Suresh Kumar Oad Rajput, N. Ali

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Abstract

This study introduces a comprehensive Google search volume based Bitcoin sentiment index (BSI) by following the methodology of Da, Engelberg, and Gao (2014). BSI is investigated for its association with Bitcoin returns, trade volume, volatility, and United States dollar exchange rates (USD). Results of the simple OLS regression clarify that BSI has a positive impact on Bitcoin returns and trade volume while it has a negative impact on the volatility of Bitcoin returns. Furthermore, the Auto-regressive distributed lag (ARDL) model has been used to capture the relationship between BSI and Bitcoin price with USD. Empirical results of the ARDL model demonstrate that Bitcoin sentiments affect USD in the short-run but not long-run. However, Bitcoin's price can negatively affect USD in short as well as in the long-run. Error correction term represents a 38.50% adjustment towards the long-run equilibrium in one month if there is a deviation in the short-run. The results imply that investors in FOREX or public in general interested in Bitcoin trading should foresee sentiments of the public towards Bitcoin.

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比特币情绪指数、表现和美元汇率

本研究采用Da、Engelberg和Gao(2014)的方法，引入了一个基于谷歌搜索量的综合比特币情绪指数(BSI)。BSI因其与比特币回报、交易量、波动性和美元汇率(USD)的关联而受到调查。简单OLS回归结果表明，BSI对比特币收益和交易量有正向影响，而对比特币收益波动率有负向影响。此外，使用自回归分布滞后(ARDL)模型来捕捉BSI与比特币价格与美元之间的关系。ARDL模型的实证结果表明，比特币情绪在短期内影响美元，但不影响长期。然而，从短期和长期来看，比特币的价格都会对美元产生负面影响。如果短期存在偏差，则误差修正项表示在一个月内向长期均衡调整38.50%。结果表明，外汇投资者或对比特币交易感兴趣的公众应该预见公众对比特币的情绪。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Econometric Modeling: International Economics eJournal

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