1 research outputs found
Structurally dynamic spin market networks
The agent-based model of stock price dynamics on a directed evolving complex
network is suggested and studied by direct simulation. The stationary regime is
maintained as a result of the balance between the extremal dynamics, adaptivity
of strategic variables and reconnection rules. The inherent structure of node
agent "brain" is modeled by a recursive neural network with local and global
inputs and feedback connections. For specific parametric combination the
complex network displays small-world phenomenon combined with scale-free
behavior. The identification of a local leader (network hub, agent whose
strategies are frequently adapted by its neighbors) is carried out by repeated
random walk process through network. The simulations show empirically relevant
dynamics of price returns and volatility clustering. The additional emerging
aspects of stylized market statistics are Zipfian distributions of fitness.Comment: 13 pages, 5 figures, accepted in IJMPC, references added, minor
changes in model, new results and modified figure