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Andrew W. Lo. Leika, Mindaugas Sloan School of Management. Sloan School of Management 2013-09-24T19:40:32Z 2013-09-24T19:40:32Z 2013 2013 http://hdl.handle.net/1721.1/81065 857792626 Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management, 2013. Cataloged from PDF version of thesis. Includes bibliographical references (p. 57-59). 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. by Mindaugas Leika. M.B.A. 117 p. eng Massachusetts Institute of Technology 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. http://dspace.mit.edu/handle/1721.1/7582 Sloan School of Management. System dynamics, market microstructure and asset pricing Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="48e9241d-708e-47f7-9488-d80a55b0ab75"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>System dynamics, market microstructure and asset pricing</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2013</PublicationDate> <Authors> <Author> <DisplayName>Leika, Mindaugas</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Sloan School of Management.</Keyword> <Abstract>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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>