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系統識別號 U0026-0507201712045100
論文名稱(中文) 結合文字探勘與金融指標之匯率預測模型
論文名稱(英文) Forecasting Exchange Rate with Text Mining and Financial Indicators
校院名稱 成功大學
系所名稱(中) 資訊管理研究所
系所名稱(英) Institute of Information Management
學年度 105
學期 2
出版年 106
研究生(中文) 陳琮翰
研究生(英文) Chung-Han Chen
學號 R76041061
學位類別 碩士
語文別 中文
論文頁數 51頁
口試委員 指導教授-王惠嘉
口試委員-劉任修
口試委員-高宏宇
口試委員-盧文祥
中文關鍵字 匯率預測  支援向量迴歸  文字探勘 
英文關鍵字 Forecasting Exchange rate  Support Vector Regression  Text Mining 
學科別分類
中文摘要 隨著貿易自由化的發展,各國家之間的貿易往來日趨頻繁,台灣因為地理環境的關係許多資源都需仰賴國際貿易來取得,經濟發展更是依賴與各國之間的貿易。貿易利潤通常需要透過進出口的價格衡量,進出口的價格則受到匯率的影響深遠,因此匯率的波動是造成利潤多寡的關鍵,但匯率的波動常受許多因素影響,而這些因素常會出現於新聞中。
過往研究鮮少利用情感分析及多國新聞資料進行匯率預測,大多研究僅以線性迴歸方法將歷史紀錄做為未來預測之依據,或以Rule-Based方法觀察經濟指標的變化進行預測,但許多研究指出新聞對於匯率波動的影響在短期內是相當明顯。
為了能夠在短時間結合大量資訊進行匯率預測,本研究將文字探勘技術納入預測方法中,透過蒐集新聞網站之新聞內容,包含了中文及英文新聞並提出兩種特徵選取方法,根據特徵選取方法分別以Pointwise Mutual Information(PMI)和情感分析方法將字詞轉換成分數,並將金融指標與新聞內容進行整合,採用支援向量迴歸(Support Vector Regression)方法建立預測模型進行匯率預測。
最後經實驗結果發現,在中文新聞與英文新聞對於匯率的影響效益上,中文新聞對於匯率的影響效益相較於英文新聞是較短暫的,而在假日新聞與平日新聞對匯率的影響性上,雖然假日新聞通常屬非工作日新聞但在對於匯率的影響性上則與平日新聞無明顯差異,在匯率預測的準確度上,金融指標相較於新聞內容在匯率的預測表現較不精準,而中文新聞在匯率預測上的表現不及英文新聞的預測表現好。
英文摘要 Because of the geographical environment in Taiwan, many resources rely on international trade. Trade profits are measured by the price of imports and exports, affected by exchange rate. Volatility of the exchange rate is the key to the amount of profit, but fluctuations of exchange rate are often affected by many factors, which can be known by the news. Most research done to date has used linear regression or Rule-Based method to forecast exchange rate, but some of studies show that the impact of news on exchange rate is significant in the short term.
In order to forecast exchange rate in a short time, we build a forecasting model with text mining and try to find out financial indicators, including the Chinese and English news, by two features selection methods. According to the selected features, Pointwise Mutual Information (PMI) and sentiment analysis are used to evaluate feature word scores. Finally Support Vector Regression is adopted to build the forecasting model.
The result of experiment can find the impact of Chinese news on the exchange rate compared to the English news is relatively lower. The impact of holiday news on the exchange rate is the same as the weekday news. The financial indicators has lowest impact on prediction is the worst. We also find using English news on the accuracy prediction is better than using Chinese news.
論文目次 第1章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 4
1.3 研究範圍與限制 4
1.4 研究流程 5
1.5 論文大綱 6
第2章 文獻探討 8
2.1 匯率預測 8
2.1.1 支援向量迴歸(Support Vector Regression) 8
2.1.2 類神經網路(Neural Network) 10
2.2 特徵選取 12
2.2.1 Term Frequency–Inverse Document Frequency (TF-IDF) 13
2.2.2 Chi-Square 14
2.2.3 Mutual Information 14
2.2.4 Information Gain 14
2.3 情感分析 15
2.4 小結 17
第3章 研究方法 18
3.1 研究架構 18
3.2 資料前處理模組 19
3.3 特徵選取模組 20
3.4 特徵字分析模組 23
3.5 匯率預測模組 28
第4章 系統建置與驗證 32
4.1 系統環境建置 32
4.2 實驗方法 32
4.2.1 資料來源 34
4.2.2 評估指標 35
4.3 實驗結果 36
4.3.1 實驗一:特徵字數量之門檻值 36
4.3.2 實驗二:資料追溯時間對預測準確率之影響 38
4.3.3 實驗三:新聞類別對預測準確率之影響 39
4.3.4 實驗四:特徵字詞性比較 41
4.3.5 實驗五:考量平日新聞與假日新聞之比較 42
4.3.6 實驗六:資料來源對預測準確率之影響 43
第5章 結論及未來研究方向 45
5.1 研究成果 45
5.2 未來研究方向 47
參考文獻 48

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