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研究生:曾立崴
研究生(外文):Tseng, Li-Wei
論文名稱:一個結合特徵選取與機器學習演算法的匯率預測模型
論文名稱(外文):An Exchange Rate Prediction Model By Combining Feature Selection And Machine Learning Algorithms
指導教授:許育峯
指導教授(外文):Hsu, Yu-Feng
口試委員:王明昌吳徐哲
口試委員(外文):WANG,MING-CHANGWU,XU-ZHE
口試日期:2022-07-23
學位類別:碩士
校院名稱:國立中正大學
系所名稱:會計與資訊科技研究所
學門:商業及管理學門
學類:會計學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:70
中文關鍵詞:匯率機器學習特徵選取模糊認知圖小波轉換總體經濟
外文關鍵詞:ForexExchangeMachine learningFeature selectionFuzzy cognitive mapWavelet transformGeneral economic
相關次數:
  • 被引用被引用:0
  • 點閱點閱:172
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
過往外匯預測研究中,多僅以匯率的價格資料進行實驗,然而經濟指標對匯率走勢具有相當大的影響,因此本研究將總體經濟指標也加入資料集中,幫助模型提升學習能力。本研究利用特徵選取與機器學習的技術,探討何種混合模型的組合具有較佳的類別預測能力,及模糊認知圖作為特徵選取工具的預測能力,再進行時間序列的數值預測,以小波轉換結合模糊認知圖與七種傳統時間序列方法比較,探討何種模型具有較佳的數值預測能力。本研究透過TEJ & Capital IQ…等資料庫收集2001年7月31日至2021年12月31日之台灣匯率、總體經濟資料。透過兩階段的實驗,探討模糊認知圖在類別與數值預測方面的表現如何,能否打敗傳統的模型與方法。
In the past foreign exchange forecasting research, most of the experiments were conducted with the price data of the exchange rate. However, economic indicators have a considerable impact on the exchange rate trend. Therefore, this study also added the overall economic indicators to the data set to help the model improve its learning ability. This study uses the technology of feature selection and machine learning to explore which combination of hybrid models has better predictive ability of categories, and the predictive ability of fuzzy cognitive map as a feature selection tool, and then carries out numerical prediction of time series, combine fuzzy cognitive map with wavelet transform and compare with seven traditional time series methods to explore which model has better numerical prediction ability. This research collects Taiwan exchange rate and general economic data from July 31, 2001 to December 31, 2021 through databases such as TEJ & Capital IQ. Through a two-stage experiment, we explore how the fuzzy cognitive map performs in category and numerical prediction, and whether it can beat traditional models and methods.
圖目錄 iv
表目錄 iii
第一章、緒論 1
第一節、研究背景與動機 1
第二節、研究目的 3
第三節、研究架構 4
第二章、文獻探討 5
第一節、匯率預測 5
第二節、深度學習 11
第三節、影響因素 27
第四節、模型績效評估 28
第三章、研究方法 31
第一節、資料來源 31
第二節、實驗設計 32
第三節、研究流程 32
第四章、實驗結果與分析 37
第一節、第一部分實驗結果 37
第二節、第二部分實驗結果 44
第五章、結論 61
第一節、研究結論 61
第二節、研究限制 61
第三節、未來研究建議 62
參考文獻 63
中文文獻 63
附錄 67
附錄1、總體經濟指標整理 67
附錄2、經特徵選取後之特徵整理 71


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