Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10140540 | Physica A: Statistical Mechanics and its Applications | 2019 | 34 Pages |
Abstract
We simulate the asset pricing in the framework of information networks when the number of agents is constant and tends to infinity. When the number of agents is a constant, we find that a higher risk aversion coefficient, a lower information uncertainty, or a higher standard variance of payoff volatility induces a lower asset price; a higher number of agents induces a higher aggregate demand. When the number of agents tends to infinity, we study and simulate the closed form expressions for asset price with risk aversion coefficient. We find that a higher network connectedness or a lower risk aversion coefficient induces a higher information driven volatility component and a lower Sharpe ratio; a higher network connectedness or a lower risk aversion coefficient induces a higher market efficiency. Liquidity driven volatility component, trading profit, price volatility are non-monotonic functions of network connectedness, or risk aversion coefficient.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Wentao Wang, Junhuan Zhang, Shangmei Zhao, Yanglin Zhang,