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      • GARCH-X(1, 1) model allowing a non-linear function of the variance to follow an AR(1) process

        Nugroho Didit B,Wicaksono Bernadus AA,Larwuy Lennox 한국통계학회 2023 Communications for statistical applications and me Vol.30 No.2

        GARCH-X(1,1) model specifies that conditional variance follows an AR(1) process and includes a past exogenous variable. This study proposes a new class from that model by allowing a more general (non-linear) variance function to follow an AR(1) process. The functions applied to the variance equation include exponential, Tukey's ladder, and Yeo–Johnson transformations. In the framework of normal and student-t distributions for return errors, the empirical analysis focuses on two stock indices data in developed countries (FTSE100 and SP500) over the daily period from January 2000 to December 2020. This study uses 10-minute realized volatility as the exogenous component. The parameters of considered models are estimated using the adaptive random walk metropolis method in the Monte Carlo Markov chain algorithm and implemented in the Matlab program. The 95% highest posterior density intervals show that the three transformations are significant for the GARCH-X(1,1) model. In general, based on the Akaike information criterion, the GARCH-X(1,1) model that has return errors with student-t distribution and variance transformed by Tukey's ladder function provides the best data fit. In forecasting value-at-risk with the 95% confidence level, the Christoffersen’s independence test suggest that non-linear models is the most suitable for modeling return data, especially model with the Tukey's ladder transformation.

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        Performance of Magnetic Switching at the Recording Temperature in Perpendicularly Magnetized Nanodots

        Nur Aji Wibowo,Didit Budi Nugroho,Cucun Alep Riyanto 한국자기학회 2019 Journal of Magnetics Vol.24 No.1

        A temperature-dependent micromagnetic study has been conducted to examine the spin dynamics of the perpendicularly magnetized nanodot in a thermally induced magnetic switching (TIMS) scheme. The magnetic parameters used in this study represent the properties of BaFe. The impact of writing-temperatures below the Curie point on the magnetization reversal characteristic of nanodot with three damping levels, which related to the minimum writing-field as well as the zero-field-switching probability, were discussed systematically. The spins configuration of the nanodot was also presented to visualize the modes of the magnetization switching. The simulation reveals that the writing-field decreases concerning with the writing-temperature and reaches its lowest value at the temperature of 0.4 % below its Curie point. During the heating phase, the mechanism of demagnetization is coupled with the writing-temperature. Meanwhile, the magnetic damping takes over the role in the magnetic switching mechanism during the freezing.

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