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Expecting the Unexpected: Entropy and Multifractal Systems in Finance
Giuseppe Orlando1,2,3, Marek Lampart4,5
1Department of Mathematics, University of Bari, Via Edoardo Orabona 4, 70125 Bari, Italy.
Entropy (Basel, Switzerland)
|November 24, 2023
Summary
Higher entropy in financial markets signals increased chaos and unexpected extreme events, particularly during bear markets. This study analyzes the New York Stock Exchange (NYSE) to understand multifractal dynamics and market conditions.
Area of Science:
- Quantitative Finance
- Complex Systems Analysis
- Market Dynamics
Background:
- Entropy quantifies information loss in systems, crucial for understanding complex dynamics.
- Multifractal systems require a singularity spectrum, not a single exponent, for full characterization.
- Investors view rising entropy as a signal of abnormal returns, necessitating preparedness for unexpected events.
Purpose of the Study:
- To analyze the multifractal characteristics of the New York Stock Exchange (NYSE) U.S. Index and its constituents.
- To utilize entropy as a method for identifying market conditions (bearish/bullish).
- To investigate the relationship between market downturns and entropy levels.
Main Methods:
- Analysis of the New York Stock Exchange (NYSE) U.S. Index and its components.
- Assessment of multifractal properties using entropy measures.
- Identification of market states (bearish/bullish) based on entropy fluctuations.
Main Results:
- Price declines correlate with increased entropy, challenging prior research suggesting reduced entropy during crises.
- Bear markets are characterized by higher entropy, indicating a greater likelihood of extreme, unpredictable events.
- The study observed power-law behavior and the absence of variance in the analyzed market data.
Conclusions:
- Market crises, specifically bear markets, exhibit higher entropy, signifying increased unpredictability.
- Entropy is an effective tool for recognizing fluctuating fractal markets and anticipating extreme events.
- Findings suggest that increased chaos, not determinism, characterizes market downturns.
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