Persistence in the cryptocurrency market

By Guiglielmo Maria Caporale, L. Gil‐Alana, Alex Plastun. Research In International Business and Finance, 2017

277 citations recorded by the source corpus.

This paper examines persistence in the cryptocurrency market. Two different longmemory methods (R/S analysis and fractional integration) are used to analyse it in the case of the four main cryptocurrencies (BitCoin, LiteCoin, Ripple, Dash) over the sample period 2013-2017. The findings indicate that this market exhibits persistence (there is a positive correlation between its past and future values), and that its degree changes over time. Such predictability represents evidence of market inefficiency: trend trading strategies can be used to generate abnormal profits in the cryptocurrency market.

Subfields: Economics and Econometrics, Finance, Information Systems

View Paper: https://www.semanticscholar.org/paper/3dae2f3c7ca5e9c60aa41df4e6dfba35f9586d83

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Shaen Corbet
2. Brian M. Lucey
3. L. Yarovaya
4. Andrew Urquhart
5. Pengfei Wang
6. Dehua Shen
7. Paraskevi Katsiampa
8. Tetsuya Takaishi

In Finance

1. Pengfei Wang
2. Dehua Shen
3. Shaen Corbet
4. Brian M. Lucey
5. Andrew Urquhart
6. L. Yarovaya
7. A. H. Dyhrberg

In Information Systems

1. Shaen Corbet
2. Brian M. Lucey
3. Pengfei Wang
4. Andrew Urquhart
5. Dehua Shen
6. L. Yarovaya
7. Paraskevi Katsiampa
8. Emmanouil Platanakis

Citations in the corpus

• Cryptocurrencies as a financial asset: A systematic analysis (2019, background): “Corbet et al. [2018a] analyse in time and frequency domains, the relationships between the three most popular cryptocurrencies and a variety of other financial assets to find evidence of the relative isolations of these assets from the financial and economic assets.”
• Cryptocurrency trading: a comprehensive survey (2020, unknown): “[43] examined persistence in cryptocurrency market by Rescaled range (R/S) analysis and fractional integration.”
• A systematic review of the bubble dynamics of cryptocurrency prices (2020, unknown): “…a number of pricing ineffi-ciencies (Urquhart [2016], Sensoy [2019], Mensi et al. [2019], Corbet et al. [2019]; Ma and Tanizaki [2019]), persistence (Caporale et al. [2018]; Corbet and Katsiampa [2018]), to be correlated or in isolation from other traded assets (Gil-Alana et al. [2020]; Sifat et…”
• An empirical investigation of volatility dynamics in the cryptocurrency market (2019, unknown): “, 2017; Katsiampa, 2017), vulnerability to speculative bubbles (Cheah and Fry, 2015), persistence (Caporale et al., 2018), heavy tail behaviour (Osterrieder and Lorenz, 2017; Osterrieder et al.”
• Does twitter predict Bitcoin? (2019, result): “This finding has been further supported by Nadarajah and Chu (2017), Tiwari et al (2018), Kjuntia and Pattanayak (2018) and Caporale et al (2018) amongst others.”