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Time-varying long-term memory in Bitcoin market

Yonghong Jiang, He Nie and Weihua Ruan

Finance Research Letters, 2018, vol. 25, issue C, 280-284

Abstract: This study attempts to investigate the time-varying long-term memory in the Bitcoin market through a rolling window approach and by employing a new efficiency index (Sensoy and Hacihasanoglu, 2014). The daily dataset for the period from 2010 to 2017 is utilized, and some interesting findings emerge that: (i) all of the generalized Hurst exponents in the Bitcoin market are above 0.5; (ii) long-term memory exists in the Bitcoin market; (iii) high degree of inefficiency ratio; (iv) the Bitcoin market does not become more efficient over time; and (v) rolling window approach can help to obtain more reliable results. Some implications for investors and policymakers are concluded.

Keywords: Long-term memory; Bitcoin market; Generalized Hurst exponents; Rolling window (search for similar items in EconPapers)
JEL-codes: C65 G14 (search for similar items in EconPapers)
Date: 2018
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Handle: RePEc:eee:finlet:v:25:y:2018:i:c:p:280-284