Signature of maturity in cryptocurrency volatility

ArXiv ID: 2409.03676 “View on arXiv”

Authors: Unknown

Abstract

We study the fluctuations, particularly the inequality of fluctuations, in cryptocurrency prices over the last ten years. We calculate the inequality in the price fluctuations through different measures, such as the Gini and Kolkata indices, and also the $Q$ factor (given by the ratio between the highest value and the average value) of these fluctuations. We compare the results with the equivalent quantities in some of the more prominent national currencies and see that while the fluctuations (or inequalities in such fluctuations) for cryptocurrencies were initially significantly higher than national currencies, over time the fluctuation levels of cryptocurrencies tend towards the levels characteristic of national currencies. We also compare similar quantities for a few prominent stock prices.

Keywords: Cryptocurrency Fluctuations, Inequality Metrics, Gini Index, Time Series Analysis, Market Volatility

Complexity vs Empirical Score

• Math Complexity: 2.5/10
• Empirical Rigor: 7.0/10
• Quadrant: Street Traders
• Why: The mathematics is limited to basic statistical measures like the Gini index, Kolkata index, and a simple Q factor, without advanced derivations or complex modeling. However, the paper is highly data-driven, presenting decade-long daily price data for cryptocurrencies, national currencies, and stocks, with detailed empirical comparisons and sector-specific tables.

  flowchart TD
    A["Research Goal: Assess Cryptocurrency Volatility Maturity"] --> B["Key Methodology:<br>Calculate Inequality Metrics (Gini, Kolkata, Q-factor)"]
    B --> C["Data Inputs:<br>10-Year Crypto Price Data vs. National Currencies & Stocks"]
    C --> D["Computational Process:<br>Time-Series Analysis of Volatility & Inequality"]
    D --> E["Key Findings:<br>Crypto Fluctuations Decline Over Time"]
    E --> F["Outcome:<br>Crypto Volatility Converges to Levels of National Currencies"]