When one stock share is a biological individual: a stylized simulation of the population dynamics in an order-driven market

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dc.contributor.authorLiu, Hanchao
dc.contributor.authorUniversity of Lethbridge. Dhillon School of Business
dc.contributor.supervisorYalamova, Rossitsa
dc.date.accessioned2019-09-04T14:27:52Z
dc.date.available2019-09-04T14:27:52Z
dc.date.issued2019-08-12
dc.degree.levelMastersen_US
dc.description.abstractThe demand-supply relationship plays an important role in an order-driven stock market. In this thesis, we propose a stylized model by defining demand (supply) over a stock at a certain time as how many shares are on the bid (ask) side, which includes all buy (sell) limit orders and buy (sell) market orders. We treat two types of shares as two different species with an interaction effect and construct generalized Lotka-Volterra equations based on some properties or assumptions of an order-driven market. Also, we apply the model to simulate how the population of the two types of shares evolves over time under the condition that there is no signal information influencing the decisions of investors. The model suggests that the population of bid and ask shares moves either to a fixed point in the phase space or exhibits periodical dynamics. Also, our model explains, though not perfectly, why it is that stock prices sometimes behave chaotically.en_US
dc.identifier.urihttps://hdl.handle.net/10133/5545
dc.language.isoen_CAen_US
dc.proquest.subjectManagement [0454]en_US
dc.proquest.subjectEconomics [0501]
dc.proquest.subjectEconomic theory [0511]
dc.proquestyesYesen_US
dc.publisherLethbridge, Alta. : University of Lethbridge, Dhillon School of Business
dc.publisher.facultyDhillon School of Businessen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Dhillon School of Business)
dc.subjectCapital market
dc.subjectDemography
dc.subjectLotka-Volterra equations
dc.subjectStock exchanges
dc.subjectSupply and demand
dc.subjectDissertations, Academic
dc.titleWhen one stock share is a biological individual: a stylized simulation of the population dynamics in an order-driven marketen_US
dc.typeThesis
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