scholarly journals Traders’ Networks of Interactions and Structural Properties of Financial Markets: An Agent-Based Approach

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Linda Ponta ◽  
Silvano Cincotti
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Market Maker ◽  
Clearing House ◽  
Stylized Facts ◽  
Risky Assets ◽  
Agent Based ◽  
Price Process ◽  
Different Types ◽  
Artificial Stock Market

An information-based multiasset artificial stock market characterized by different types of stocks and populated by heterogeneous agents is presented and studied so as to determine the influences of agents’ networks on the market’s structure. Agents are organized in networks that are responsible for the formation of the sentiments of the agents. In the market, agents trade risky assets in exchange for cash and share their sentiments by means of interactions that are determined by sparsely connected graphs. A central market maker (clearing house mechanism) determines the price process for each stock at the intersection of the demand and the supply curves. A set of market’s structure indicators based on the main single-assets and multiassets stylized facts have been defined, in order to study the effects of the agents’ networks. Results point out an intrinsic structural resilience of the stock market. In fact, the network is necessary in order to archive the ability to reproduce the main stylized facts, but also the market has some characteristics that are independent from the network and depend on the finiteness of traders’ wealth.

scholarly journals MARKET FLUCTUATIONS EXPLAINED BY DIVIDENDS AND INVESTOR NETWORKS

2017 ◽  
Vol 20 (08) ◽  
pp. 1750007 ◽  
Author(s):  
MATTHEW OLDHAM
Keyword(s):  
Stock Market ◽  
Complex Systems ◽  
Financial Markets ◽  
Network Topology ◽  
Network Science ◽  
Agent Based ◽  
Excess Volatility ◽  
Artificial Stock Market ◽  
Analytical Frameworks ◽  
Insight Into

The inability of investors and academics to consistently predict, and understand the behavior of financial markets has forced the search for alternative analytical frameworks. Analyzing financial markets as complex systems is a framework that has demonstrated great promises, with the use of agent-based models (ABMs) and the inclusion of network science playing an important role in increasing the relevance of the framework. Using an artificial stock market created via an ABM, this paper provides a significant insight into the mechanisms that drive the returns in financial markets, including periods of elevated prices and excess volatility. The paper demonstrates that the network topology that investors form and the dividend policy of firms significantly affect the behavior of the market. However, if investors have a bias to following their neighbors then the topology becomes redundant. By successfully addressing these issues this paper helps refine and shape a variety of additional research tasks for the use of ABMs in uncovering the dynamics of financial markets.

MICROSTRUCTURE DYNAMICS AND AGENT-BASED FINANCIAL MARKETS: CAN DINOSAURS RETURN?

2012 ◽  
Vol 15 (supp02) ◽  
pp. 1250060 ◽  
Author(s):  
MICHAEL KAMPOURIDIS ◽  
SHU-HENG CHEN ◽  
EDWARD TSANG
Keyword(s):  
Stock Market ◽  
Genetic Programming ◽  
Financial Markets ◽  
Trading Strategies ◽  
Self Organizing Maps ◽  
Market Models ◽  
Agent Based ◽  
Time Periods ◽  
Artificial Stock Market ◽  
Rule Inference

This paper formalizes observations made under agent-based artificial stock market models into a concrete hypothesis, which is called the Dinosaur Hypothesis. This hypothesis states that the behavior of financial markets constantly changes and that the trading strategies in a market need to continuously co-evolve with it in order to remain effective. After formalizing the hypothesis, we suggest a testing methodology and run tests under 10 international financial markets. Our tests are based on a framework that we recently developed, which used Genetic Programming as a rule inference engine, and Self-Organizing Maps as a clustering machine for the above rules. However, an important assumption of that study was that maps among different periods were directly comparable with each other. In order to allow this to happen, we had to keep the same clusters throughout the different time periods of our experiments. Nevertheless, this assumption could be considered as strict or even unrealistic. In this paper, we relax this assumption. This makes our model more realistic. In addition, this allows us to investigate in depth the dynamics of market behavior and test for the plausibility of the Dinosaur Hypothesis. The results show that indeed markets' behavior constantly changes. As a consequence, strategies need to continuously co-evolve with the market; if they do not, they become obsolete or dinosaurs.

scholarly journals An Agent-Based Approach to Artificial Stock Market Modeling

2020 ◽  
Vol 168 ◽  
pp. 161-169
Author(s):  
Samuel Vanfossan ◽  
Cihan H. Dagli ◽  
Benjamin Kwasa
Keyword(s):  
Stock Market ◽  
Agent Based ◽  
Artificial Stock Market

TRADER SPECIES WITH DIFFERENT DECISION STRATEGIES AND PRICE DYNAMICS IN FINANCIAL MARKETS: AN AGENT-BASED MODELING PERSPECTIVE

2010 ◽  
Vol 09 (02) ◽  
pp. 327-344 ◽  
Author(s):  
WEI ZHANG ◽  
GEN LI ◽  
XIONG XIONG ◽  
YONG JIE ZHANG
Keyword(s):  
Financial Markets ◽  
Asset Price ◽  
Agent Based Modeling ◽  
Price Dynamics ◽  
Trading Behavior ◽  
Agent Based ◽  
Price Process ◽  
Trading Decisions ◽  
The Individual ◽  
Analytical Approaches

Investors with different trading strategies can be viewed as different "species" in financial markets. Since the asset price is ultimately determined by the individual trading decisions, the combination and evolution of different trader species in financial market ecology will have great impact to the price dynamics. Considering the limitations and shortcomings of traditional analytical approaches in financial economics in dealing with this issue, an agent-based computational model is introduced in this paper. With the co-existence of 3-type trader species that make different decisions based on their own beliefs and constrains, it is found that although rational speculation destabilizes the price process with the presence of positive feedback strategy, as suggested in the literature, introducing extra noise trading behavior to the market will make the price process back to a more stationary situation, meaning that the market will be healthier if more diversified trader species co-exist in the markets.

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