2026-09-21T04:58:25Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/458842022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Tomaso Poggio, Andrew W. Lo and J. Doyne Farmer.
Kim, Adlar Jeewook
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2009-06-30T16:32:11Z
2009-06-30T16:32:11Z
2008
2008
http://hdl.handle.net/1721.1/45884
320433350
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
Includes bibliographical references (leaves 151-157).
The thesis seeks a better understanding of liquidity generation process of financial markets and attempts to find a quantitative measure of market liquidity. Various statistical modeling techniques are introduced to model order flow generation, which is a liquidity generation process of the market. The order flow model successively replicates various statistical properties of price returns including fat-tailed distribution of returns, no autocorrelation of returns and strong positive autocorrelation of transaction signs. While attempting to explain how the order flow model satisfies Efficient Market Hypothesis (EMH), I discovered a method of calibrating market liquidity from order flow data.
by Adlar Jeewook Kim.
Ph.D.
157 leaves
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
An order flow model and a liquidity measure of financial markets
Thesis
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