Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/124936
題名: 以深度學習模型預測台灣ETF價格走勢
作者: 吳凱華
Wu, Kai-Hua
貢獻者: 蔡炎龍<br>蕭明福
吳凱華
Wu, Kai-Hua
關鍵詞: 深度學習
類神經網路
交易所買賣基金
日期: 2019
上傳時間: 7-Aug-2019
摘要: 交易所買賣基金(Exchange Traded Funds, ETF)有別於個股投資,具有分散風險的特性,是一種追蹤特定股價指數的投資商品,也就是一種將股票指數商品化並長期持有的金融商品。\n持有金融商品的目的就是獲利,因此價格或趨勢的預測準確率就變得相當的重要。文獻上實證發現類神經網路較傳統時間序列方法的預測能力高,加上近年機器學習快速發展,本文以類神經網路長短期記憶模型與生成對抗網路為研究方法,建立一個能廣泛運用在台灣非金融類交易所買賣基金的價格與走勢預測。變數除了有收盤價與成交量之外,交易所買賣基金屬於長期持有的商品,產業與總體的變化也是影響行情走勢的重要因素,因此加入匯豐台灣製造業採購經理人指數做為總體變數。此外,為了捕捉總體變數造成的價格影響,加入二十日與四十五日的收盤價移動平均捕捉價格趨勢。\n實證結果發現,使用長短期記憶模型具有預測波動較大的台灣非金融類交易所買賣基金之收盤價格能力,而生成對抗網路具有較高的預測漲跌能力,且行情確實為牛市的時候,生成對抗網路也有較高的能力夠捕捉此趨勢。
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描述: 碩士
國立政治大學
經濟學系
106258009
資料來源: http://thesis.lib.nccu.edu.tw/record/#G0106258009
資料類型: thesis
Appears in Collections:學位論文

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