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Dwi Atmono AW
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Mathematics

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ANALISIS KOMPONEN UTAMA DENGAN MENGGUNAKAN MATRIK VARIAN KOVARIAN YANG ROBUST Sujatmiko, Irwan; Linuwih, Susanti; AW, Dwi Atmono
MATEMATIKA Vol 2, No 8 (2005): JURNAL MATEMATIKA
Publisher : MATEMATIKA

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Abstract

The present of outlier data causes the estimator of variance-covariance be overestimated. As a consequent, in the principle component analysis, the variability of the data in the main component becomes biger than as expected. To cope this condition, one can use robust estimator, i.e. MVE and MCD. Using simulation of Monte Carlo Experiments, the Principal Component Analysis  using estimator MCD has the better performance than the estimator MVE and also classic estimator.  
PERAMALAN VOLATILITAS INDEKS HARGA SAHAM MENGGUNAKAN MODEL ASIMETRIK GARCH (GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY) DENGAN DISTRIBUSI SKEWED STUDENT-t Wahyuni, Susi Tri; Iriawan, Nur; AW, Dwi Atmono
MATEMATIKA Vol 8, No 1 (2005): JURNAL MATEMATIKA
Publisher : MATEMATIKA

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Abstract

The condition of Indonesian economic in the last fiew years fluctuatics following  konjungtur cycle. Besides in economic problem, non economic problem such as social and politic are also influence that fluctuation. It means, the instability had influenced of stock exchange practition in analyzing and predicting return. Financial data, such as stock exchange price indices often has heteroscedasticity. One of modeling technique to analyze the condition is using GARCH models. Unfortunately, GARCH models often do not fully capture the thick  tails property of high frequency financial time series. To cope this weakness, we’ll an Asymmetric GARCH model will be used. Using Box-Jenkins methods, the Composite Price Indices have mean model ARIMA (10 17 69,1,0). With the same data we can having  GARCH (2,1) model.  The Asymmetric GARCH (AGARCH) model in this research was not properly  proper to model the Composite Price Indices Volatility.
Co-Authors Irwan Sujatmiko Nur Iriawan Susanti Linuwih Susi Tri Wahyuni