Access the full text.
Sign up today, get DeepDyve free for 14 days.
Ching-Hsue Cheng, Liang-Ying Wei (2009)
Volatility model based on multi-stock index for TAIEX forecastingExpert Syst. Appl., 36
Tse Kuen, Tung Hoong (1992)
Forecasting volatility in the Singapore stock marketAsia Pacific Journal of Management, 9
Cheol Eun, Sangdal Shim (1989)
International Transmission of Stock Market MovementsJournal of Financial and Quantitative Analysis, 24
Cheng-Yi Lin, S. Sheu, Tsung-Shin Hsu, Yan-Chun Chen (2013)
Application of generally weighted moving average method to tracking signal state space modelExpert Systems, 30
Chris Brooks, James Chong (2001)
The Cross‐Currency Hedging Performance of Implied Versus Statistical Forecasting ModelsJournal of Futures Markets, 21
Yanxia Jiang, Li Xu, Huacheng Wang, Hui Wang (2009)
Influencing factors for predicting financial performance based on genetic algorithmsSystems Research and Behavioral Science, 26
S. Roberts (2000)
Control Chart Tests Based on Geometric Moving AveragesTechnometrics, 42
He received a PhD in Department of Industrial Management from National Taiwan University of Science and Technology. His research includes GWMA and prediction model, quality engineering
V. Polimenis, I. Neokosmidis (2014)
The global financial crisis and its transmission to Asia Pacific, 1
Li Xu (2011)
Information architecture for supply chain quality managementInternational Journal of Production Research, 49
Jing-Rong Chang, Liang-Ying Wei, Ching-Hsue Cheng (2011)
A hybrid ANFIS model based on AR and volatility for TAIEX forecastingAppl. Soft Comput., 11
Kyoung-jae Kim, Ingoo Han (2001)
The Extraction of Trading Rules From Stock Market Data Using Rough SetsExpert Systems, 18
S. Sheu, W. Griffith (1996)
Optimal number of minimal repairs before replacement of a system subject to shocksNaval Research Logistics, 43
(1979)
He was a Chair Professor of the Industrial Management Department at the National Taiwan University of Science and Technology. He received his MSc
R. Engle, C. Mustafa (1992)
Implied ARCH models from options pricesJournal of Econometrics, 52
Sang Kim, J. Rogers (1995)
International Stock Price Spillovers and Market Liberalization: Evidence from Korea, Japan, and the United StatesJournal of Empirical Finance, 2
Xiaotian Zhu, Hong Wang, Li Xu, Huaizu Li (2008)
Predicting stock index increments by neural networks: The role of trading volume under different horizonsExpert Syst. Appl., 34
S. Sheu, Tse-Chieh Lin (2003)
The Generally Weighted Moving Average Control Chart for Detecting Small Shifts in the Process MeanQuality Engineering, 16
His research interests are in the area of quality, production management, and design of quality control charts. Related papers have appeared in journals such as
Muh-Cherng Wu, Sheng Lin, Chia-Hsin Lin (2006)
An effective application of decision tree to stock tradingExpert Syst. Appl., 31
Hyungwon Shin, S. Sohn (2007)
Application of an EWMA combining technique to the prediction of currency exchange ratesIIE Transactions, 39
J. Hung (2011)
Adaptive Fuzzy-GARCH model applied to forecasting the volatility of stock markets using particle swarm optimizationInf. Sci., 181
L. Li, J. Warfield (2011)
Perspectives on quality coordination and assurance in global supply chainsInternational Journal of Production Research, 49
T. Bollerslev (1986)
Generalized autoregressive conditional heteroskedasticityJournal of Econometrics, 31
D. Dickinson (2000)
Stock market integration and macroeconomic fundamentals: an empirical analysis, 1980-95Applied Financial Economics, 10
J. Hung (2009)
A Fuzzy Asymmetric GARCH model applied to stock marketsInf. Sci., 179
(2018)
and Systems Engineering, and International Journal of Operations and Quantitative Management. How to cite this article
K. Huarng, T. Yu, Yu Hsu (2007)
A Multivariate Heuristic Model for Fuzzy Time-Series ForecastingIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 37
(2014)
Hsin‐NanTsai received the MSc degree
Globalization has increased the volatility of international financial transactions, particularly those related to international stock markets. An increase in the volatility of one country's stock market spreads throughout the globe, affecting other countries' stock markets. In particular, the Dow Jones Industrial Average plays an extremely important role in the international stock market. This paper uses the generally weighted moving average method and data from the Dow Jones Industrial Average, the National Association of Securities Dealers Automated Quotations, Japan's Nikkei 225, the Korea Composite Stock Price Index, and the Hong Kong Hang Seng Index to predict the performance of the Taiwan Capitalization Weighted Stock Index. This paper attempts to find the smallest prediction error using the optimal combination of generally weighted moving average model parameters and combinations of various international stock market data and compares the results to that found using the exponentially weighted moving average model to explore differences between the two types of forecasting models.
Expert Systems – Wiley
Published: Jan 1, 2018
Keywords: ; ; ;
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.