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[1]Akram, M., Hyndman, R. J., and Ord, J. K., “Exponential smoothing and non-negative data,” Australian & New Zealand Journal of Statistics, vol. 51, no. 4, pp. 415-432, Dec, (2009). [2]Apley, D. W., “Time series control charts in the presence of model uncertainty,” Journal of Manufacturing Science and Engineering-Transactions of the Asme, vol. 124, no. 4, pp. 891-898, Nov, (2002). [3]Baillie, R. T., Bollerslev, T., and Mikkelsen, H. O., “Fractionally integrated generalized autoregressive conditional heteroskedasticity,” Journal of Econometrics, vol. 74, no. 1, pp. 3-30, (1996). [4]Beck, S., “Autoregressive conditional heteroscedasticity in commodity spot prices,” Journal of Applied Econometrics, vol. 16, no. 2, pp. 115-132, Mar-Apr, (2001). [5]Bollerslev, T., “Generalized autoregressive conditional heteroskedasticity,” Journal of Econometrics, vol. 31, no. 3, pp. 307-327, (1986). [6]Brooks, C., and Chong, J., “The cross-currency hedging performance of implied versus statistical forecasting models,” Journal of Futures Markets, vol. 21, no. 11, pp. 1043-1069, Nov, (2001). [7]Chang, J. R., Wei, L. Y., and Cheng, C. H., “A hybrid ANFIS model based on AR and volatility for TAIEX forecasting,” Applied Soft Computing, vol. 11, no. 1, pp. 1388-1395, Jan, (2011). [8]Chen, C. W. S., Gerlach, R., Cheng, N. Y. P. et al., “The impact of structural breaks on the integration of the ASEAN-5 stock markets,” Mathematics & Computers in Simulation, vol. 79, no. 8, pp. 2654-2664, (2009). [9]Cheng, C. H., and Wei, L. Y., “Volatility model based on multi-stock index for TAIEX forecasting,” Expert Systems with Applications, vol. 36, no. 3, pp. 6187-6191, Apr, (2009). [10]Dickinson, D. G., “Stock market integration and macroeconomic fundamentals: An empirical analysis, 1980-95,” Applied Financial Economics, vol. 10, no. 3, pp. 261-276, (2000). [11]Engle, R. F., and Mustafa, C., “Implied ARCH models from options prices,” Journal of Econometrics, vol. 52, no. 1-2, pp. 289-311, (1992). [12]Engle, R. F., Granger, C. W. J., and Kraft, D., “Combining competing forecasts of inflation using a bivariate arch model,” Journal of Economic Dynamics and Control, vol. 8, no. 2, pp. 151-165, (1984). [13]Eun, C. S., and Shim, S., “International transmission of stock-market movements,” Journal of Financial and Quantitative Analysis, vol. 24, no. 2, pp. 241-256, Jun, (1989). [14]Gardner, E. S., “Note: Rule-based forecasting vs. damped-trend exponential smoothing,” Management Science, vol. 45, no. 8, pp. 1169-1176, Aug, (1999). [15]Gardner, E. S., “Exponential smoothing: The state of the art - Part II,” International Journal of Forecasting, vol. 22, no. 4, pp. 637-666, (2006). [16]Gardner, E. S., and McKenzie, E., “Forecasting trends in time-series,” Management Science, vol. 31, no. 10, pp. 1237-1246, (1985). [17]Gould, P. G., Koehler, A. B., Ord, J. K. et al., “Forecasting time series with multiple seasonal patterns,” European Journal of Operational Research, vol. 191, no. 1, pp. 207-222, Nov, (2008). [18]Huarng, K. H., Yu, T. H. K., and Hsu, Y. W., “A multivariate heuristic model for fuzzy time-series forecasting,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 37, no. 4, pp. 836-846, (2007). [19]Hung, J. C., “A Fuzzy Asymmetric GARCH model applied to stock markets,” Information Sciences, vol. 179, no. 22, pp. 3930-3943, (2009). [20]Hung, J. C., “Adaptive Fuzzy-GARCH model applied to forecasting the volatility of stock markets using particle swarm optimization,” Information Sciences, vol. 181, no. 20, pp. 4673-4683, Oct, (2011). [21]Hyndman, R. J., and Koehler, A. B., “Another look at measures of forecast accuracy,” International Journal of Forecasting, vol. 22, no. 4, pp. 679-688, (2006). [22]Hyndman, R. J., Koehler, A. B., Snyder, R. D. et al., “A state space framework for automatic forecasting using exponential smoothing methods,” International Journal of Forecasting, vol. 18, no. 3, pp. 439-454, Jul-Sep, (2002). [23]Jiang, Y., Xu, L., and Wang, H., “Influencing factors for predicting financial performance based on genetic algorithms,” Systems Research and Behavioral Science, vol. 26, no. 6, pp. 661-673, (2009). [24]Kim, S. W., and Rogers, J. H., “International stock price spillovers and market liberalization: Evidence from Korea, Japan, and the United States,” Journal of Empirical Finance, vol. 2, no. 2, pp. 117-133, (1995). [25]Kuen, T. Y., and Hoong, T. S., “Forecasting volatility in the Singapore stock market,” Asia Pacific Journal of Management, vol. 9, no. 1, pp. 1-13, (1992). [26]Makridakis, S., and Hibon, M., “The M3-Competition: results, conclusions and implications,” International Journal of Forecasting, vol. 16, no. 4, pp. 451-476, Oct-Dec, (2000). [27]McKenzie, E., and Gardner, E. S., “Damped trend exponential smoothing: A modelling viewpoint,” International Journal of Forecasting, vol. 26, no. 4, pp. 661-665, Oct-Dec, (2010). [28]Miller, D. M., and Williams, D., “Damping seasonal factors: Shrinkage estimators for the X-12-ARIMA program,” International Journal of Forecasting, vol. 20, no. 4, pp. 529-549, Oct-Dec, (2004). [29]Miller, T., and Liberatore, M., “Seasonal exponential smoothing with damped trends - an application for production planning,” International Journal of Forecasting, vol. 9, no. 4, pp. 509-515, Dec, (1993). [30]Park, C. W., and Yi, A. C., “Mispricing of US Shocks in the Korean Stock Market,” Asia-Pacific Journal of Financial Studies, vol. 40, no. 3, pp. 347-376, Jun, (2011). [31]Roberts, S. W., “Control chart tests based on geometric moving averages,” Technometrics, vol. 1, no. 1, pp. 239-250, (1959). [32]Sheu, S. H., and Griffith, W. S., “Optimal number of minimal repairs before replacement of a system subject to shocks,” Naval Research Logistics, vol. 43, pp. 319-333, Aug, (1996). [33]Sheu, S. H., and Lin, T. C., “The generally weighted moving average control chart for detecting small shifts in the process mean ” Quality Engineering, vol. 16, no. 2, pp. 209-231, Dec, (2003). [34]Shi, S., Xu, L. D., and Liu, B., “Applications of artificial neural networks to the nonlinear combination of forecasts,” Expert Systems, vol. 13, no. 3, pp. 195-201, (1996). [35]Shi, S. M., Xu, L. D., and Liu, B., “Improving the accuracy of nonlinear combined forecasting using neural networks,” Expert Systems with Applications, vol. 16, no. 1, pp. 49-54, (1999). [36]Shin, H. W., and Sohn, S. Y., “Application of an EWMA combining technique to the prediction of currency exchange rates,” IIE Transactions (Institute of Industrial Engineers), vol. 39, no. 6, pp. 639-644, (2007). [37]Snyder, R. D., and Koehler, A. B., “Incorporating a tracking signal into a state space model,” International Journal of Forecasting, vol. 25, no. 3, pp. 526-530, Jul-Sep, (2009). [38]Wu, M. C., Lin, S. Y., and Lin, C. H., “An effective application of decision tree to stock trading,” Expert Systems with Applications, vol. 31, no. 2, pp. 270-274, (2006). [39]Zhang, L. Y., Govindaraju, K., Lai, C. D. et al., “Poisson DEWMA control chart,” Communications in Statistics-Simulation and Computation, vol. 32, no. 4, pp. 1265-1283, (2003). [40]Zheng, F., Xu, L. D., and Tang, B., “Forecasting regional income inequality in China,” European Journal of Operational Research, vol. 124, no. 2, pp. 243-254, (2000). [41]Zhu, X., Wang, H., Xu, L. et al., “Predicting stock index increments by neural networks: The role of trading volume under different horizons,” Expert Systems with Applications, vol. 34, no. 4, pp. 3043-3054, (2008).
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