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Some comments on Bitcoin market (in)efficiency.

V Dimitrova1, M Fernández-Martínez2, M A Sánchez-Granero3

  • 1Department of Economics and Business, Universidad de Almería, Almería, Spain.

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Summary
This summary is machine-generated.

This study analyzed Bitcoin-USD market efficiency using self-similarity exponents. Results show apparent memory is due to distribution, not persistent market memory, with periods of anti-persistent memory identified.

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Area of Science:

  • Quantitative Finance
  • Market Efficiency Analysis
  • Time Series Analysis

Background:

  • The efficiency of cryptocurrency markets, specifically Bitcoin-USD, remains a subject of ongoing research.
  • Understanding market dynamics requires robust analytical tools to assess memory and predictability.

Purpose of the Study:

  • To investigate the efficiency of the Bitcoin-USD market from mid-2010 to early 2019.
  • To dynamically analyze the evolution of the self-similarity exponent and identify market memory characteristics.

Main Methods:

  • Employed the Detrended Fluctuation Analysis (FD4) approach with a 512-day sliding window to analyze Bitcoin-USD daily returns.
  • Defined a memory indicator based on the difference between the self-similarity exponent of the original and shuffled series.
  • Conducted additional analyses using varying window sizes and FD algorithm parameters (q=1, 2), and compared with S&P500 series.

Main Results:

  • The self-similarity exponent for BTC-USD (and S&P500) consistently remained above 0.5.
  • This exponent value was attributed to the underlying data distribution, not significant persistent memory.
  • Identified periods exhibiting significant anti-persistent memory in the BTC-USD and S&P500 series.

Conclusions:

  • The Bitcoin-USD market exhibits characteristics that might suggest inefficiency, but these are driven by data distribution.
  • The observed self-similarity does not stem from persistent memory, challenging traditional efficiency interpretations.
  • Periods of anti-persistent memory were detected, indicating complex dynamics within the Bitcoin-USD market.