Financial herding models' behavior hinges on information transmission velocity and agent population.
Markov chains are used in models to understand how financial markets work. By studying how information spreads among different types of investors, researchers found that the size of the investor group affects how well the model predicts market behavior. The way information moves and the structure of the investor network both play a role in how accurate the model is.