{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/45884"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/45884","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"An order flow model and a liquidity measure of financial markets","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Kim, Adlar Jeewook"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Tomaso Poggio, Andrew W. Lo and J. Doyne Farmer."],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-22T22:21:18Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"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. 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