Title page for etd-0716107-104950


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URN etd-0716107-104950
Author Yi-Ting Guo
Author's Email Address No Public.
Statistics This thesis had been viewed 5059 times. Download 1901 times.
Department Applied Mathematics
Year 2006
Semester 2
Degree Master
Type of Document
Language English
Title Statistical Models of Market Reactions to Influential Trades
Date of Defense 2007-06-20
Page Count 38
Keyword
  • Quoted depth
  • Influential trade
  • Price-volume model
  • Transition probability
  • High frequency data
  • Logistic regression model
  • Odds ratio
  • Abstract 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.
    Advisory Committee
  • Mong-Na Lo - chair
  • Chi-Jeng Wang - co-chair
  • Mei-Hui Guo - advisor
  • Files
  • etd-0716107-104950.pdf
  • indicate accessible in a year
    Date of Submission 2007-07-16

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