學界間廣泛地認為一般金融資產報酬具有的特性是:線型不可預測性,條件

異質變異數,非條件尖峰態 ... 等特性o 固然金融資產報酬具有線型不可

預測之特性,可是並不能否決其間可能有非線型依存關係的存在o目前大部

份經濟計量分析方法中的模式建構問題均是在假設模式的結構訊息已知的

條件下求解,然若真實體系的結構訊息未知或不明朗時,貿然地假設為某種

特定的模式結構,則可能又難於避免模式設定錯誤的困擾,因而對於真實體

系行為的描述亦將可能是誤導且不合理的,這意味著:除非該特定的模式結

構正是真實體系的表徵, 否則無論該特定模式的結構特性多完美,均難以

建構一令人信服的數理化模式來表徵真實體系之行為o 不幸地,此一問題

在高度非線型的動態隨機體系中尤其嚴重, 甚至是否存在一 ``真實''

模式來據以表徵體系之行為,亦是相當值得懷疑, 故考慮一種無需特定結

構訊息假設的無母數方法或函數逼近法實屬必要o 類神經網路中的倒傳遞

網路模式即是符合此種特性的方法之一o然而學界間仍無法確定的是金融

資產報酬序列資料所產生的 ARCH 效果本身是否為真實序列資料產生機制

特性之顯現, 還是應歸咎於被忽略掉條件均數方面之非線性所衍生模式設

定錯誤情況下的代用模式, 並不得而知;另一方面, ARCH 模式的顯著成就

及其價值亦不能予以輕易地漠視, 因此, 試圖將 ARCH 模式所能提供的攸

關訊息納入倒傳遞網路模式的考量之中而形成倒傳遞網路-自迴歸條件異

質變異數 (BPN-ARCH) 模式以增進樣本外預測能力的精度便是本論文最

主要的嘗試重點與目的o

[1J 毛維凌[民80]，“從方法論看非線型動態經濟模型"，政治大學經濟所演
講稿。
[2] 何祖平[民80]，“多元自迴歸條件異質變異數模型一主要國際貨幣間關
聯性之研究"，政治大學國際貿易研究所碩士論文。
[3] 吳柏林，劉文卿，陳奕光[民81 ]，“隨機模式與混沌模式立預測穩健性探
討"中國統計學報，第30 卷第2 期， 169-189 頁。
[4] 莊委桐[民81]，“非線型動態模型檢定與在總體經濟模型之應用"政治
大學經濟研究所碩士論文。
[5J 許怡隆[民78]，“外匯市場風險性溢價之探討一異質條件變異數分析法
之研究"政治大學國際貿易研究所碩士論文。
[6] 葉怡成[民82]，“顯神經網路模式應用與實作"儒林圖書公司。
[7] 張淑玲[民80]，“總體時間數列非恆定性之研究"，政治大學國際貿易研
究所碩士論文。

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