The work presented in this dissertation can be grouped around three major themes.
The first theme relates to risk, the second theme relates to asset pricing, whereas the
third theme relates to serial correlation of asset returns. The three chapters of this
dissertation investigate these themes
Chapter Two analyses the behavior over time of market risk, aggregate idiosyncratic
risk and correlations in portfolio of Taiwan listing stocks and studied pattern of
aggregate correlation between the 3 most important Taiwan stock index and Taiwan
value-weighted index. We find (1) Idiosyncratic risk is trended upwards; (2) The
conditional stock returns correlation process is asymmetric. The implication of our
finding is (1) It takes more stocks to achieve a given level of diversification; (2)
Diversification strategies perform poorly in bear markets.
Chapter Three investigates the role of the asset co-skewness and conditioning
information in asset pricing. First, I estimate long-run predictive regressions of asset
returns to test whether aggregate idiosyncratic risk is a price factor of industrial
returns. Then I use data on Taiwan 19 industry portfolios to fit various assets pricing
models. I find (1) the cross-sectional ctional correlation between 2 i
£] (the gamma coefficient
from the 3M-CAPM equation) and 3 i
ϕ (the interaction coefficient from the CCAPM
equation) is positive and fairly large. (2) The firm-level volatility is a good proxy for
cay as conditioning information variable. (3) The gamma coefficient can pick up the
extent of beta co-vary with the market wide excess-return over the business cycle.
(4)among 19 industrial returns, the 2 industrial returns can be explained by
3M-CAPM; the 7 industrial returns can be explained by CCAPM; the 5 industrial
returns can be explained by 3M-CAPM+CCAPM, Others can¡¦t be explained by either
of three models.
Chapter Four examines the impact of positive feedback trading behavior of the
investors on the short-term dynamics of return for four Taiwan index futures contracts
by utilizing the framework of the model developed by Sentana & Wadhwani(1992).
Use of the Asymmetric Nonlinear Smooth Transition GARCH Model demonstrates that positive feedback trading of investors is the main determinant of short-term
dynamics of return for Taiwan index futures contracts. Moreover, it shows that
positive trading is more intense during market declines than it is during market
advances due to extensive use of spot-loss trading for investors. Finally it is shown
that the sophisticated professional investors intend to take positive feedback trades
wave so that they lead to increase positive feedback trading in Taiwan index futures
since the government opened the enterprises for managed futures.
Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0710107-173311 |
Date | 10 July 2007 |
Creators | Chuang, Hung-Ming |
Contributors | Zheng Yuan Chen, David Shyu, Yu Juan Huang, Lo,Henry Y., Y. Chris Liao |
Publisher | NSYSU |
Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
Language | Cholon |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0710107-173311 |
Rights | off_campus_withheld, Copyright information available at source archive |
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