Title page for etd-0703116-174342


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URN etd-0703116-174342
Author Bakti Siregar
Author's Email Address siregarbakti@gmail.com
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Department Applied Mathematics
Year 2015
Semester 2
Degree Master
Type of Document
Language English
Title Statistical Analysis of Indonesia Stock Market
Date of Defense 2016-07-11
Page Count 44
Keyword
  • GARCH
  • Clustering
  • Volatility
  • ARCH
  • AIC
  • Abstract Liberalization and economic integration become topics of discussion and research in
    recent years. Indonesia is one of the countries that actively participates in the achievement
    of liberalization and economic integration, especially in the ASEAN region. Indonesia stock
    market has a high degree of volatility which can be used to produce high investment returns,
    which is one of the reasons to attract foreign investors to enter Indonesia stockmarket.
    Volatility plays an important role for market participants to control and reduce their market
    risk of financial assets
    In this study we establish the volatility models for the stocks listed in the Indonesia stock
    market index LQ45. The models we considered include the Autoregressive Conditional Heteroskedasticity
    (ARCH) proposed by Engle (1982), Generalized Autoregrassive Conditional
    Heteroskedasticity (GARCH) by Bollerslev (1986), the Stochastic Volatility Model (SVM) by
    Jacquier, Polson and Rossi (1994), and Autoregressive Moving Average (ARMA) by Box, Jankins, and Reinsel (1994). We use the daily log returns to establish the models and select the best
    one via Akaike information criterion (AIC).Moreover, we use it to predict the future volatility.
    In the end, we also apply machine learning application such as the K-means method to figure
    out how itsmovement of the clusters volatility in Indonesia stocks.
    Advisory Committee
  • Mong-Na Lo Huang - chair
  • Shih-Feng Huang - co-chair
  • Mei-Hui Guo - advisor
  • Files
  • etd-0703116-174342.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2016-08-25

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