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Student Number 954208021
Author Fu-Hsiu Wu(§dÃL¨q)
Author's Email Address No Public.
Statistics This thesis had been viewed 1491 times. Download 631 times.
Department Finance
Year 2007
Semester 2
Degree Master
Type of Document Master's Thesis
Language English
Title Empirical Determinants of Momentum Life Cycle
Date of Defense 2008-06-16
Page Count 38
Keyword
  • momentum life cycle (MLC)
  • persistence of price momentum
  • trading volume
  • Abstract This study examines whether trading volume is a useful determinant of momentum life cycle in the U.S. market. From the momentum life cycle hypothesis, price momentum of low-volume winners and high-volume losers is more likely to persist in near future. However, the evidence of this paper reveals that low-volume stocks actually show greater persistence in price momentum among winners, but the persistence of price momentum between high-volume losers and low-volume losers is not significantly different. It is obvious that the trading volume cannot provide information in locating a given stock in its momentum life cycle perfectly. However, we find that book-to-market ratio, firm size and institutional ownership are useful determinants of momentum life cycle. Particularly, the price momentum of winners with high book-to-market ratio, large size or high institutional ownership and that of losers with low book-to-market ratio, small size or low institutional ownership tend to persist in near future while price momentum of winners with low book-to-market ratio, small size or low institutional ownership losers and that of losers with high book-to-market ratio, large size or high institutional ownership tend to reverse in near future.
    Table of Content 1 Introduction 1
    2 Literature Review 2
    3 Sample and Methodology 5
    3.1 Sample . . . . . . . . . . . . . . . . . . . . . . 5
    3.2 Methodology . . . . . . . . . . . . . . . . . . . 5
    3.2.1 Duration Model . . . . . . . . . . . . . 7
    4 Empirical Results 10
    4.1 Descriptive Statistics . . . . . . . . . . . . . . . 10
    4.2 Results of Cross-Sectional Regression . . . . . . 13
    4.3 Subperiod Regression . . . . . . . . . . . . . . 16
    5 Conclusion 17
    References 19
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    Advisor
  • Pin-Huang Chou(©P»«°Ä)
  • Files
  • 954208021.pdf
  • approve in 2 years
    Date of Submission 2008-06-24

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