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The use of high-frequency data in cryptocurrency research: A meta-review of literature with bibliometric analysis

SSRN Electronic Journal
2023
  • 1
    Citations
  • 1,276
    Usage
  • 6
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    1
    • Citation Indexes
      1
  • Usage
    1,276
    • Abstract Views
      949
    • Downloads
      327
  • Captures
    6
  • Ratings
    • Download Rank
      187,183

Article Description

As the crypto-asset ecosystem matures, the use of high-frequency data becomes increasingly common in decentralized finance literature. Using bibliometric analysis, we characterize the existing cryptocurrency literature that employs high-frequency data. Based on 189 articles collected from the Scopus database from 2015 to 2022, we highlight the most influential authors, articles, and journals. This approach enables us to identify the emerging trends and research hotspots with the aid of co-citation and cartographic analyses and shows the knowledge expansion through authors’ collaboration in the cryptocurrency research with co-authorship analysis. We identify four major streams of research: (i) return prediction and measurement of volatility in cryptocurrencies; (ii) (in)efficiency of cryptocurrencies; (iii) price dynamics and bubbles in cryptocurrencies; and (iv) diversification, safe haven and hedging properties of Bitcoin. We conclude that the investment features and the economic outcomes of highly trading cryptocurrencies would be analysed predominantly on tick-by-tick bases in the future. This paper provides recommendations for future research.

Bibliographic Details

Muhammad Anas; Syed Jawad Hussain Shahzad; Larisa Yarovaya

Elsevier BV

Cryptocurrencies; high-frequency data; intra-day data; bibliometric analysis; network analysis; meta-literature review

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