The volatility model of the ASEAN Stock Indexes

  • Received October 25, 2018;
    Accepted February 13, 2019;
    Published March 18, 2019
  • Author(s)
    Faurani Santi Singagerda
    ORCID Researcher ID ,
    Linda Septarina
    ORCID ,
    Anuar Sanusi
    ORCID
  • DOI
    http://dx.doi.org/10.21511/imfi.16(1).2019.18
  • Article Info
    Volume 16 2019, Issue #1, pp. 226-238
  • TO CITE АНОТАЦІЯ
  • Cited by
    3 articles
  • 1090 Views
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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

This research study examines the characteristics of the Association of Southeast Asian Nations (ASEAN) volatility of stock indexes. The following models are used in this research: Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH), Fractionally Integrated Generalized Autoregressive Conditional Heteroscedasticity (FIGARCH), Glosten Jaganathan Runkle Generalized Autoregressive Conditional Heteroscedasticity (GJR-GARCH), and Multifractal Model of Asset Return (MMAR). The research also used the data from the ASEAN country members’ (the Philippines, Indonesia, Malaysia, Singapore, and Thailand) stock indexes for the period from January 2002 until 31 January 2016 to determine the suitable model.
Meanwhile, the results of the MMAR parameter showed that the returns of the countries have a characteristic called long-term memory. The authors found that the scaling exponents are associated with the characteristics of the specific markets including the ASEAN member countries and can be used to differentiate markets in their stage of development.

Finally, the simulated data are compared with the original data by scaling function where most of the stock markets of the selected ASEAN countries have long-term memory with the scaling behavior of information asymmetry. Some of the countries such as the Philippines and Indonesia have their own alternative models using GARCH and EGARCH due to the possibility of leverage. Generally, MMAR is the best model for use in ASEAN market, because this model considered Hurst exponent as a parameter of long-term memory that indicates persistent behavior.

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    • Figure 1. The return index of (a) the Philippines, (b) Indonesia, (c) Malaysia, (d) Singapore, and (e) Thailand (January 1, 2002 – January 31, 2016)
    • Figure 2. The scaling function of the nonlinear return sequence that shows an existing series of returns is multifractal
    • Figure 3. Partition function each country parallel with the horizontal axis on range two
    • Figure 4. The path of standard deviation shows the MMAR model has the smallest value compared to other models
    • Table 1. Gross Domestic Product of ASEAN member countries
    • Table 2. The model return series estimation results
    • Table 3. Mono-fractal H for origin series
    • Table 4. Return series estimation results using GARCH model
    • Table 5. Return series estimation results using EGARCH model
    • Table 6. Order q of returning series
    • Table 7. Return series estimation results using multifractal model
    • Table 8. Standard deviation from difference between original and simulated
    • Table 9. Scaling function
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