預測之效果與評估－台灣加權股價指數之應用

Abstract

本文主要以時間序列為基礎，透過一般化自我相關條件異質變異模型、介入分析、誤差修正、多元轉換函數及組合預測等方法，來建立台灣加權股價指數的預測模型。\n從預測精確度之結果顯示，多元轉換函數納入介入分析模型為單一預測模式的最佳預測模型，且其預測績效具有穩定性，而透過最小誤差迴歸組合預測模型可以再改善預測模型在MSPE、RMSPE、MAPE及Theil’s U等量的預測績效。\n從多元轉換函數納入介入分析模型中發現，台灣加權股價指數會受到美國道瓊工業指數、台幣兌美元之匯率及消費者物價指數等經濟變數所影響。由於股票市場是重要景氣領先指標，因而當台灣或美國股票市場發生重大事件時，將會對台灣經濟發展產生衝擊，而從本文研究發現，政府可藉由短期政策的施行，產生另一股力量來平衡股市的波動，進而穩定台灣整體經濟發展。

This research introduces GARCH, ECM, transfer function, and combined forecasting model to predict the changes of TAIEX, and to evaluate the forecasting performance of different models. \nThe results show that the intervention analysis integrated into transfer function yields an accurate prediction model, and the forecasting performance is stable. According to the weighted average of forecasts by minimizing regression error, the resulting forecasting performance such as MSPE, RMSPE, MAPE and Theil’s U will be improved.\nThe intervention analysis integrated into transfer function model shows that the TAIEX is affected by external factors, INDU, exchange rate, and consumer price index. The stock market is one of the major leading indictor, when the Taiwan or U.S. stock market had been impacted, and then Taiwan’s economic development will also be fluctuated. This paper shows that short-term implementation of policies could result in another force to balance the fluctuations in the stock market, and to stabilize the economic development in Taiwan.