Shannon entropy to quantify complexity in the financial market

Paper: arXiv 2307.08666

Abstract

In this paper we study the complexity in the information traffic that occurs in the peruvian financial market, using the Shannon entropy. Different series of prices of shares traded on the Lima stock exchange are used to reconstruct the unknown dynamics. We present numerical simulations on the reconstructed dynamics and we calculate the Shannon entropy to measure its complexity

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 3.0/10
• Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper employs advanced mathematical concepts like Takens’ embedding theorem and fractal geometry, indicating high mathematical complexity. However, it lacks detailed backtesting, statistical performance metrics, or implementation specifics beyond basic simulations, resulting in low empirical rigor.

Research Flowchart

  flowchart TD
  A["Research Goal<br>Quantify complexity in<br>Peruvian financial market"] --> B["Data Input<br>Equity prices from Lima Stock Exchange"]
  B --> C["Methodology<br>Reconstruct Price Dynamics"]
  C --> D["Computational Process<br>Calculate Shannon Entropy"]
  D --> E["Outcome<br>Numerical simulations<br>Complexity quantification"]