System dynamics, market microstructure and asset pricing

Traditional asset pricing approaches are not able to explain extreme volatility and tail events that characterized financial markets in the past decade. System Dynamics theory, which is still underutilized in financial modeling, could help researchers to model stock market dynamics, explain and simulate extreme events. This paper proposes an artificial stock market model, which can be used to simulate stock market behavior, incorporate various assumptions about interactions among market participants: fundamental, noise and technical traders. The model includes multiple feedback loops, namely, positive feedback, ratings, debt and leverage. Dynamic interactions among loops stabilize markets and limit bubble formation. Model simulation results show, that not only the numerical limit of leverage, but also regulatory definition of leverage matters. Market stability can be achieved faster with lower system-wide and narrow definition of leverage. To increase stability, Central banks and regulators might consider targeting leverage in a financial system.

Department dc:contributor.department

Sloan School of Management.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2013

Author dc:creator

• Leika, Mindaugas

Advisor dc:contributor.advisor

• Andrew W. Lo.

• Sloan School of Management.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/81065

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/81065