Bitcoin Volatility and Currency Acceptance: A Time-Series Approach

Virtual currencies emerged in 2009 as alternatives to traditional methods of payment, offering faster transaction speeds and increased privacy. The prime example of these currencies is Bitcoin. Prior literature in the past five years has generally predicted that Bitcoin would fail to supplant an existing widely traded currency, but new trends appear to be emerging. I test Dowd and Greenaway’s (1993) currency acceptance model using recent data on Bitcoin, including Bitcoin volatility. This presentation will show whether Bitcoin's ability to act as a store of value and its level of price volatility affect the number of people that will accept it as a currency. Confidence in existing currencies may be weakening and thus analyzing the relationship between volatility and currency acceptance is significant in understanding the future behavior of currencies. I will employ a time-series vector autoregression to determine the effect of the supply of bitcoins, the volatility of the dollar, and the volatility of the Euro on both Bitcoin volatility and the number of vendors that accept Bitcoin.