Shannon Entropy: An Econophysical Approach to Cryptocurrency Portfolios

Area of Science:

• Econophysics
• Quantitative Finance
• Computational Economics

Background:

• Cryptocurrency markets have gained significant global investor interest due to their novelty, accessibility, and profit potential.
• Understanding the statistical properties of cryptocurrency returns is crucial for risk management and investment strategies.

Purpose of the Study:

• To analyze the return distributions of major cryptocurrencies using an econophysics approach.
• To investigate the effectiveness of diversification in mitigating risk within cryptocurrency portfolios.

Main Methods:

• Statistical analysis of cryptocurrency return data.
• Application of entropy measures to quantify uncertainty.
• Comparison of return distributions against Gaussian and heavy-tailed models.

Main Results:

• Many widely traded cryptocurrencies exhibit return distributions that deviate from the Gaussian model.
• These distributions are characterized by heavy tails, indicating a higher probability of extreme events.
• Entropy analysis confirms that portfolio diversification is a viable strategy for reducing return uncertainty.

Conclusions:

• The non-Gaussian, heavy-tailed nature of cryptocurrency returns necessitates advanced risk assessment techniques.
• Portfolio diversification remains a fundamental and effective strategy for managing investment risk in cryptocurrency markets.