Sains Malaysiana 49(8)(2020): 2023-2034
http://dx.doi.org/10.17576/jsm-2020-4908-25
Ukuran
Kebersandaran bagi Pulangan
Lima-Minit Berbanding Pulangan Harian menggunakan Kopula
Statik dan Dinamik
(Dependence Measure of
Five-Minutes Returns Compared to Daily Returns using Static and Dynamic
Copulas)
NURUL
HANIS AMINUDDIN JAFRY1*, RUZANNA AB RAZAK2 &
NORISZURA ISMAIL1
1Jabatan Sains Matematik, Fakulti
Sains dan Teknologi, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan,
Malaysia
2Economics and Quantitative Methods
Unit, Faculty of Management, Multimedia University, 63100 Cyberjaya, Selangor Darul Ehsan,
Malaysia
Diserahkan:
22 Januari 2020/Diterima: 29 April 2020
ABSTRAK
Kajian tentang kebersandaran antara
pasaran saham adalah penting kerana kemampuannya memberi petunjuk dalam proses
membuat-keputusan bagi mengatur strategi pelaburan. Kebanyakan kajian lepas
mengukur kebersandaran antara pasaran saham menggunakan kopula statik. Walau
bagaimanapun, sejak beberapa tahun kebelakangan ini, kopula dinamik telah
digunakan sebagai kaedah alternatif bagi mengukur kebersandaran kerana
keupayaannya untuk memodelkan kebersandaran masa-berubah antara pasaran saham. Kebanyakan kajian berkaitan kopula lebih tertumpu kepada
korelasi data bivariat bagi pulangan harian atau mingguan atau bulanan untuk
menjelaskan pergerakan bersama antara pasaran kewangan dan sebagai petunjuk
kewangan bagi aspek pengurusan portfolio. Namun begitu, maklumat daripada data
berfrekuensi rendah tidak lagi mampu untuk menampung aktiviti perdagangan
berskala besar. Sebaliknya, data berfrekuensi tinggi mengandungi maklumat yang
lebih banyak mengenai pasaran saham di samping berupaya mencerminkan kemeruapan
pasaran saham dengan lebih tepat. Oleh itu, kajian ini bertujuan untuk membandingkan
kebersandaran antara pulangan lima-minit (atau data frekuensi tinggi) dengan
pulangan harian (atau data frekuensi rendah) bagi menentukan sama ada data-data
ini mempunyai struktur kebersandaran yang sama atau berbeza. Kedua-dua model
kopula statik dan dinamik diguna untuk memodelkan
kebersandaran masa-berubah dalam data bivariat. Sebagai
contoh berangka, data siri pulangan bivariat bagi pasaran Islam (FBMHS) dan
konvensional (KLCI) di Malaysia diguna untuk memodelkan kebersandaran data
harian dan kebersandaran data lima-minit. Keputusan kajian ini menunjukkan bahawa struktur
kebersandaran antara pulangan harian dan logaritma kemeruapan terealis 5-minit adalah berbeza dan kepelbagaian portfolio bagi pasangan
KLCI-FBMHS adalah tidak digalakkan. Akhir sekali, siri 5-minit dan model kopula
SJC dinamik masing-masing dipilih sebagai set data dan model kebersandaran
terbaik.
Kata kunci:
FBMHS; KLCI; kopula dinamik; pulangan harian; pulangan lima-minit
ABSTRACT
Studies
on dependence between stock markets are crucial because of their indications on
the process of decision-making in investment strategies. Many previous studies
measure the dependence between stock markets using static copula. However, in
recent years, dynamic copula has been used as an alternative for measuring
dependence due to its capability of capturing time-varying dependence between
stock markets. Many copula studies have been focusing on examining the
correlation of the bivariate data of daily, or weekly, or monthly returns to
explain the co-movement between financial markets and for possible financial
directions on portfolio management. However, information of low-frequency data
is unable to accommodate large-scale trading activities. On the other hand,
high frequency data contains more information about the stock market and has
the ability to reflect stock market volatility more accurately. Therefore, this
study aims to compare the dependence of the five-minutes returns (or
high-frequency data) with the daily returns (or low-frequency data) to
determine whether these data have similar or different dependence structures.
Both static and dynamic copula models are utilized to capture the existence of
time-varying dependence of the bivariate data. For numerical examples, the
bivariate returns series of the Islamic (FBMHS) and conventional (KLCI) stock markets
in Malaysia are utilized to model the dependence of the daily data and the
dependence of the five-minute data. Findings of this paper
shows that the structure of dependency between daily returns and 5-minute
logarithmic realized variance are different, and portfolio diversification
between KLCI-FBMHS pair is not advisable. Finally, the 5-minute series and dynamic SJC copula model
are chosen as the best data set and the best dependency model, respectively.
Keywords:
Daily returns; dynamic copula; FBMHS; five-minutes returns; KLCI
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*Pengarang
untuk surat-menyurat; email: nurulhanis.fst@gmail.com
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