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研究生:邱敏鋒
研究生(外文):Min-Feng Chiu
論文名稱:運用支撐向量機建構營建材料供應商使用衍生性金融商品避險之預測模型
論文名稱(外文):Developing a SVM-based risk-hedging prediction model under using derivatives for construction material suppliers
指導教授:陳介豪陳介豪引用關係
指導教授(外文):Jieh-Haur Chen
學位類別:碩士
校院名稱:國立中央大學
系所名稱:營建管理研究所
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:76
中文關鍵詞:衍生性金融商品支撐向量機(SVM)邏輯斯回歸營建材料供應商避險預測模型
外文關鍵詞:support vector machine (SVM)risk hedgingConstruction Companymaterial supplierderivativefinancial ratio
相關次數:
  • 被引用被引用:9
  • 點閱點閱:407
  • 評分評分:
  • 下載下載:119
  • 收藏至我的研究室書目清單書目收藏:2
自1973年The Bretton Woods System崩潰後,各國相繼放棄固定匯率制度,轉而採用浮動匯率制度(Floating Exchange Rate System),導致利率及匯率之變動加劇。台灣為一小型開放之島國經濟型態,對外貿易活動頻繁,故會持續性地面臨匯率與利率波動風險。加上我國加入WTO後營建產業邁向國際化,營建材料供應商由於進出口頻繁,且因舉借外幣負債或進出口貿易業務之因素,勢必面臨利率與匯率波動之風險,此外近年來營建物價更是普遍大幅上揚,對國內工程更是帶來不小之衝擊。本研究以營建業中與匯率、利率、物價息息相關之營建材料供應商為研究對象,藉由支撐向量機(Support Vector Machines;SVM)所建立出之預測模型,提供營建材料供應商日後判斷是否使用衍生性金融商品避險之參考。本研究採上市32家營建材料供應商(包含7家水泥業與25家鋼鐵業)為研究對象,取其民國91~95年度之財務報表為樣本。藉由文獻回顧法初步確認本研究之衡量變數,並探討營建材料供應商公司內部財務資訊與使用衍生性金融商品避險之關連性。此外針對材料供應商使用衍生性金融商品規避匯率、利率之實際情形,以台灣經濟新報資料庫(Taiwan Economic Journal;TEJ)中公開之財務資訊,配合統計原理獨立樣本T檢定,篩選出具有顯著影響性之衡量變數,再以VIF檢定去除變數間之共線性關係,最後以支撐向量機建構預測模型,並與傳統統計方法中學者常用之邏輯斯回歸(Logistic)預測模型分析比較結果,進行驗證且探討營建材料供應商是否須使用衍生性金融商品規避匯率與利率之風險。因此本研究之研究成果有:1.瞭解營建材料供應商目前使用衍生性金融商品之概況。2.篩選出財務報表中影響企業使用衍生性金融商品之財務變數。3.由支撐向量機建立預測模型,提供營建材料供應商日後判斷是否使用衍生性金融商品之參考。
Floating exchange rates and interest rates have enhanced financial risks for those corporations which conduct international business or contain debt capital. Risk hedging, through the use of derivatives, has provided an effective solution toward such financial risks in recent years. Most construction material suppliers usually expose to these types of risks due to a high debt capital structure and the nature of material import business. A tool that is able to predict whether such a material supplier, based on its financial status, should use derivatives to hedge financial risks is demanded. This research objective is to develop a prediction model using Support Vector Machine (SVM) to provide suggestions for hedging financial risks. The scope limits the database to all 640 financial statements published in recent 5 years from 32 listed construction material suppliers. A total of 10 input factors were identified and determined using literature review, t-test, and co linearity diagnostics. Having data trimming and normalization, 640 sets were downsized to 520 sets which contain 248 effective and 272 ineffective risk-hedging sets. The SVM prediction model, thus, based on the kernel radial basis function and normalized data, yielded the prediction accuracy rate at 80.65%. The evaluation using the cross validation method shows the practicability and validation of the model. This study concludes that (1) 10 financial ratios are proved influential to financial risk hedging using derivative, and (2) the proposed SVM prediction model is feasible and applicable for the construction material suppliers. Future studies are recommended to apply the model to construction companies.
目錄..........................................................................................................................................vi
表目錄....................................................................................................................................viii
圖目錄......................................................................................................................................ix
第一章 緒論..............................................................................................................................1
1.1 研究背景與動機..............................................................................................................1
1.2 研究目的..........................................................................................................................2
1.3 研究範圍與限制..............................................................................................................2
1.4 研究流程..........................................................................................................................3
1.5 論文架構..........................................................................................................................5
第二章 文獻回顧......................................................................................................................6
2.1 衍生性金融商品..............................................................................................................6
2.1.1 衍生性金融商品定義...............................................................................................6
2.1.2 衍生性金融商品之種類...........................................................................................6
2.1.3 使用衍生性金融商品之目的...................................................................................7
2.1.4 財務風險移轉方式...................................................................................................7
2.1.5 各國使用衍生性金融商品避險之概況...................................................................8
2.1.6 各種衍生性金融商品之使用情形...........................................................................9
2.2 國內外避險與公司特質相關研究實證彙整..................................................................9
2.2.1 國外使用金融商品避險情形...................................................................................9
2.2.2 國內使用衍生性金融商品避險情形.....................................................................12
2.2.3 避險相關理論.........................................................................................................15
2.3 國內使用衍生性金融商品之近況................................................................................16
2.3.1 國內營建材料供應商中長期負債之近況.............................................................17
2.3.2 主要國家匯率.........................................................................................................19
2.3.3 國內營建材料進出口情形.....................................................................................19
2.3.4 小結: .....................................................................................................................21
2.4 財務分析方法之演進歷程............................................................................................22
2.5 邏輯斯回歸....................................................................................................................24
2.6 支撐向量機....................................................................................................................25
2.6.1 超平面.....................................................................................................................25
2.6.2 核心函數.................................................................................................................28
2.6.3 支撐向量機應用於財務分析之相關研究.............................................................29
第三章 資料收集與分析........................................................................................................30
3.1 財務資料來源................................................................................................................30
3.2 衡量變數選取................................................................................................................31
3.3 重要影響因子篩選........................................................................................................36
3.3.1 獨立樣本T 檢定.....................................................................................................36
3.3.2 T 檢定輸出結果......................................................................................................37
3.3.3 共線性診斷.............................................................................................................40
第四章 建構預測模型............................................................................................................42
4.1 模型假設........................................................................................................................42
4.2 邏輯斯回歸....................................................................................................................45
4.3 支撐向量機....................................................................................................................46
4.3.1 資料正規化.............................................................................................................47
4.3.2 分類方法與核心函數之選擇.................................................................................47
4.3.3 支撐向量機輸出結果............................................................................................49
4.4 SVM 預測模型驗證.......................................................................................................51
4.5 小結...............................................................................................................................53
第五章 結論與建議................................................................................................................56
5.1 結論...............................................................................................................................56
5.2 建議...............................................................................................................................57
參考文獻.................................................................................................................................59
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