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Statistical Models of Market Reactions to Influential Trades

In this study, we consider high frequency transaction data of NYSE, and apply statistical methods to characterize each trade into two classes, influential and ordinary liquidity trades. First, a median based approach is used to establish a high R-square price-volume model for high frequency data. Next, transactions are classified into four states based on the trade price, trade volume, quotes, and quoted depth. Volume weighted transition probability of the four states are investigated and shown to be distinct for informed trades and ordinary liquidity trades. Furthermore, four market reaction factors are introduced and studied. Logistic regression models of the influential trades are established based on the four factors and odds ratios are used to select the cutoff points.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0716107-104950
Date16 July 2007
CreatorsGuo, Yi-Ting
ContributorsMong-Na Lo, Mei-Hui Guo, Chi-Jeng Wang
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716107-104950
Rightswithheld, Copyright information available at source archive

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