Information flows in the market: An evolutionary game approach

Area of Science:

• Economics
• Game Theory
• Market Dynamics

Background:

• Investor decisions are heavily influenced by market information.
• Markets can distinguish between true and false information.
• Understanding information propagation is crucial for market analysis.

Purpose of the Study:

• To propose and analyze an information flow game using an evolutionary game approach.
• To investigate how information value and investor behavior interact in financial markets.
• To determine the impact of a sharing rate on information propagation and market stability.

Main Methods:

• Developed an information flow game based on evolutionary game theory.
• Modeled information as having a quantifiable value.
• Analyzed investor strategies as either 'sharers' or 'silencers' with a defined sharing rate (α).

Main Results:

• Increased emergence of information sharers in rumor-heavy markets, particularly with higher sharing rates.
• Higher sharing rates decrease information value standard deviation in rumor markets, but increase it in true information markets.
• Asymmetric investor reactions observed, with greater sensitivity to losses than profits.
• Network randomness influences the optimal sharing rate for sharer emergence stability based on information veracity.

Conclusions:

• The sharing rate significantly impacts information propagation and market dynamics.
• Investor sensitivity to losses plays a key role in market reactions.
• Market structure and information veracity dictate the optimal sharing strategy for stability.