Testing Cryptocurrency Return Stability Against Currencies and Equity Indexes

Summary

This study examines whether Bitcoin, Ethereum, and Ripple had stable daily dollar returns relative to the euro, Japanese yen, the S&P 500, and the MSCI World Index over the sample period from 2016 to 2020. It first removes cycles shorter than one month, then assesses relationships in the filtered daily returns using three approaches: Pearson correlations, dynamic time warping to allow for lagged relationships, and a cumulative prediction-error test based on bounds implied by the Black-Scholes model.

The authors report that correlations became stronger in later sample years, while return similarities allowing for leads and lags appeared throughout the period. Their cumulative error test did not exceed its stated bounds, which they interpret as failing to reject the efficient market hypothesis. These findings concern filtered returns and the selected assets and years; they do not establish that cryptocurrencies are stable as units of account in general or that the relationships persist outside the sample. The excerpt gives no detailed estimates or robustness checks.

Key ideas

• The analysis compares filtered daily returns for three cryptocurrencies with major currencies and equity indexes.
• Pearson correlations increased in later sample years, according to the study.
• Dynamic time warping is used to detect return similarities that may involve leads or lags.
• A cumulative prediction-error test stays within Black-Scholes-based bounds, so the study does not reject the efficient market hypothesis.

Tags

# Price Stability of Cryptocurrencies as a Medium of Exchange


# Price Stability of Cryptocurrencies as a Medium of Exchange









We present positive evidence of price stability of cryptocurrencies as a medium of exchange. For the sample years from 2016 to 2020, the prices of major cryptocurrencies are found to be stable, relative to major financial assets. Specifically, after filtering out the less-than-one-month cycles, we investigate the daily returns in US dollars of the major cryptocurrencies (i.e., Bitcoin, Ethereum, and Ripple) as well as their comparators (i.e., major legal tenders, the Euro and Japanese yen, and the major stock indexes, S&P 500 and MSCI World Index). We examine the stability of the filtered daily returns using three different measures. First, the Pearson correlations increased in later years in our sample. Second, based on the dynamic time-warping method that allows lags and leads in relations, the similarities in the daily returns of cryptocurrencies with their comparators have been present even since 2016. Third, we check whether the cumulative sum of errors to predict cryptocurrency prices, assuming stable relations with comparators' daily returns, does not exceeds the bounds implied by the Black-Scholes model. This test, in other words, does not reject the efficient market hypothesis.

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