Zobrazeno 1 - 10 of 51 pro vyhledávání: '"Byeongchan Seong"'
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Akademický článek
Forecasting with a combined model of ETS and ARIMA.
Autor: Jiu Oh, Byeongchan Seong
Publikováno v: Communications for Statistical Applications & Methods; Jan2024, Vol. 31 Issue 1, p144-154, 11p
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5
Intervention analysis based on exponential smoothing methods: Applications to 9/11 and COVID-19 effects
Autor: Byeongchan Seong, Kiseop Lee
Publikováno v: Economic Modelling
This study extends intervention analysis beyond the ARIMA models, which are currently used by most scholars and practitioners, to exponential smoothing models. This allows us to obtain the benefits of exponential smoothing modeling in analyzing time
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cec38f182484447982047a6f662ebba9
https://doi.org/10.1016/j.econmod.2020.11.014
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6
Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models
Autor: Byeongchan Seong
Publikováno v: Economic Modelling. 91:463-468
The analysis of mixed-frequency (MF) time series has been limited mainly to the vector autoregressive integrated moving average (ARIMA) framework, even though the exponential smoothing (ETS) method—a competing model to ARIMA—has made considerable
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::776c6b90976618b0a61387b7457c1946
https://doi.org/10.1016/j.econmod.2020.06.020
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7
Diversification effect of ship investment funds in South Korea
Autor: Jae-Boong Lee, Jeong Seok Song, Keun-Sik Park, Su-Han Woo, Byeongchan Seong
Publikováno v: Journal of Korea Trade. 23:62-74
PurposeThe purpose of this paper is to examine the diversification effect of the Korean Ship Investment Fund (KSF) under Markowitz portfolio theory by analyzing short-term and long-term relationships with stocks and bonds.Design/methodology/approachF
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::beadb79ecc3b411c3de359d847cf33ba
https://doi.org/10.1108/jkt-06-2018-0051
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10
EMD based hybrid models to forecast the KOSPI
Autor: Hyowon Kim, Byeongchan Seong
Publikováno v: Korean Journal of Applied Statistics. 29:525-537
The paper considers a hybrid model to analyze and forecast time series data based on an empirical mode decomposition (EMD) that accommodates complex characteristics of time series such as nonstationarity and nonlinearity. We aggregate IMFs using the
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6a3ad048bac84a3ed51941e61e45abed
https://doi.org/10.5351/kjas.2016.29.3.525
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