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                  <mods:namePart>Yalamova, Rossitsa</mods:namePart>
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                  <mods:namePart>Liu, Hanchao</mods:namePart>
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               <mods:abstract>The 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.</mods:abstract>
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                  <mods:topic>Capital market</mods:topic>
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               <mods:subject>
                  <mods:topic>Demography</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Lotka-Volterra equations</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Stock exchanges</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Supply and demand</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Dissertations, Academic</mods:topic>
               </mods:subject>
               <mods:titleInfo>
                  <mods:title>When one stock share is a biological individual: a stylized simulation of the population dynamics in an order-driven market</mods:title>
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               <mods:genre>Thesis</mods:genre>
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