跳到主要內容

臺灣博碩士論文加值系統

(44.212.99.208) 您好!臺灣時間:2024/04/17 19:51
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:陳清南
研究生(外文):Chin-Nan Chen
論文名稱:台灣IC產業最適供應鏈模擬與風險評估
論文名稱(外文):The Optimal Supply Chain Simulation and Risk Evaluation of Taiwan IC Industry
指導教授:蘇明俊蘇明俊引用關係
指導教授(外文):Min-Jiun Su
學位類別:碩士
校院名稱:國立中興大學
系所名稱:企業管理學系研究所
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:中文
論文頁數:105
中文關鍵詞:基因演算法最佳供應鏈模擬風險值期望尾端損失歷史模擬法蒙地卡羅法拔靴法回溯測試風險調整資本報酬率
外文關鍵詞:Genetic Algorithm (GA)Optimal Supply Chain SimulationCapital Asset Pricing Model (CAPM)Autoregressive Integrated Moving Average (ARIMA)Autoregressive Conditional Heteroscedasticty (ARCH)Value-at-Risk (VaR)Expected Tail Loss (ETL)Historical SimulationBootstrapsMonte Carlo SimulationKupiec testChristoffersen testLopez testRisk Adjusted Return on Capital (RAROC)
相關次數:
  • 被引用被引用:0
  • 點閱點閱:356
  • 評分評分:
  • 下載下載:78
  • 收藏至我的研究室書目清單書目收藏:4
在目前供應鏈管理領域研究中,大多以生產策略、模型建置及資訊科技的運用作為切入點,最終仍是回歸到利潤創造之主軸。然而,在追求整體利潤極大化之前提下,對於供應鏈之風險控管機制卻付之闕如。因此本研究將風險值與期望尾端損失等觀念引入到供應鏈體系中,使供應鏈管理和財務觀念作結合,提出供應鏈整體風險量化觀念與評估對策。本文主要在探討IC產業供應鏈的最佳化與風險評估。首先,分別以六種財務領域的獲利指標作為分析資料,並使用基因演算法進行最佳化模擬。其次,透過ARIMA與ARCH混合雙因子CAPM型態模型,配置各供應鏈組合之最適模型,以求取模型參數與配適數據(fitted data),並透過歷史模擬法、蒙地卡羅法與拔靴法進行風險值(VaR)與期望尾端損失值(ETL)的估計。最後,以風險調整資本報酬率型態(RAROC-type)的績效指標來進行各模擬供應鏈與實際IC代工策略聯盟的整體評估與比較。並得到下列結論:
一、六組利潤極大化為目標的供應鏈組合:(一) 每股盈餘:聯詠-茂德-日月光;(二) 資產報酬率:聯詠-力晶-矽品;(三) 股東權益報酬率:合邦-世界先進-日月光;(四)營業利益佔實收資本比率:偉詮電-聯電-超豐;(五) 稅前純益佔實收資本比率:聯發科-台積電-超豐;(六) 純益率:盛群-台積電-超豐。
二、整體而言,本研究所模擬之六組供應鏈的風險值相對低於實際IC代工鏈聯盟;特別是以股東權益報酬率與純益率兩種指標所模擬之組合風險值最低。另外在RAROC-Type績效方面,以股東權益報酬率與營業利益佔實收資本比率的名列前三名,明顯優於實際IC代工鏈聯盟。
三、根據前兩點結論,以股東權益報酬率來模擬最佳供應鏈,為本研究所建議之標竿指標。
In the field of supply chain management, we found that the most researches were focused on manufacturing strategies, models constructing and information technologies performing but always regressed to the basic point - profit creation. However, all the alliance partners in chain are seeking to maximize the co-profit but doing nothing for the risk control mechanism of the supply chain. For this reason, our research introduced the viewpoints of value-at-risk (VaR) and expected-tail-loss (ETL) into the supply chain framework to adopt the financial concepts combined in supply chain management and therefore provided the risk quantification and evaluation solutions of strategies.
This study mainly aims at optimization simulation and risk evaluation for the IC industry supply chain of Taiwan. First, we take six different financial profitability ratios as the input data in Excel model and use the Genetic Algorithm to simulate the optimal supply chain for each ratio. Second, we use the two-factor CAPM-Type regression with mixing ARIMA and ARCH model to extract the purified fitted-data of each simulated supply chain portfolio that we can use it as the input for assessing the VaR and ETL by Historical Simulation, Bootstraps and Monte-Carlo Simulation method. Further, we also test on VaR and ETL under each assessing method by Kupiec test, Christoffersen test and Lopez test that helps for selecting the best method for each chain. Finally, we adopt RAROC-Type index to compare the performance of each supply chain portfolio. Our research is concluded as follows:
1.The six simulated optimal supply chains in Taiwan IC industory:(a) Earning per Share: NovaTek→ ProMOS→ ASE; (b) Return on Assets: NovaTec→ PSC→ SIPIN; (c) Return on Equity: AVID→ VIS→ ASE; (d) Operating Profit Margin on Capital: Weltrend→ UMC→ GreaTek; (e)Income before Tax on Paid-up Capital: MediaTek→ TSMC→ GreaTek; (f) Net Profit Margin: HOLTek→ TSMC→ GreaTek.
2.Relative to the IC OEM chains, the simulated ones roughly have lower risk and higher performance. The ROE and Net Profit Margin could be made use of simulating the best two risk-less supply chain and the ROE could be made use of simulating the chain with the highest performance.
3.Following to the previous two conclusions, we suggest that the Return on Equity (ROE) could be treated as the best benchmark financial profitable ratio of simulating the optimal risk-less but profit-maximized supply chain portfolio.
第一章 緒論
第一節 研究背景與動機……………………………………………… 1
第二節 研究目的……………………………………………………… 2
第三節 研究對象與範圍……………………………………………… 3
第四節 論文架構……………………………………………………… 4
第二章 文獻探討
第一節 供應鏈財務績效指標相關研究……………………………… 6
第二節 供應鏈最佳模式相關研究…………………………………… 8
第三節 基因演算法應用的相關研究…………………………………10
第四節 資產定價模式相關研究………………………………………12
第五節 風險值相關理論與研究………………………………………15
第六節 回溯測試相關理論……………………………………………23
第七節 風險調整資本報酬率相關研究………………………………26
第三章 研究方法
第一節 研究流程………………………………………………………29
第二節 基因演算法模擬最佳化………………………………………30
第三節 恆定數列檢定…………………………………………………38
第四節 ARIMA 與 ARCH 混合模型……………………………………39
第五節 VaR與ETL之衡量 ……………………………………………43
第六節 回溯測試………………………………………………………49
第七節 風險調整資本報酬率…………………………………………51
第四章 實證結果分析
第一節 資料選取………………………………………………………53
第二節 最佳化供應鏈模擬結果………………………………………55
第三節 樣本之敘述統計分析…………………………………………56
第四節 恆定數列檢定結果……………………………………………56
第五節 模型選擇與評估………………………………………………58
第六節 VaR與ETL之實證結果 ………………………………………61
第七節 回溯測試與最適風險評價模型………………………………62
第八節 風險調整資本報酬率之實證結果……………………………67
第五章 研究結論與建議
第一節 研究結論………………………………………………………69
第二節 研究建議………………………………………………………70
參考文獻
中文文獻…………………………………………………………………72
英文文獻…………………………………………………………………74
附 錄
附 錄 一……………………………………………………………… 80
附 錄 二……………………………………………………………… 83
附 錄 三……………………………………………………………… 88
附 錄 四……………………………………………………………… 97
壹、中文文獻
王毓敏。民國81年6 月。「β係數穩定性分析--資本資產訂價模型適用性之實證研究」。私立淡江大學財務金融研究所碩士論文。
林萍珍。民國87年6 月。「遺傳演算法在使用者導向的投資組合選擇之應用」。國立中央大學資訊管理學系研究所碩士論文。
張士杰。民國87年6月。「運用拔靴複製法構建風險值(VaR)估計量之分配」。銘傳大學金融研究所碩士論文。
傅家齊。民國88年6月。「運用參數型非中心t分配之拔靴複製估計模型改進涉險值評估模式」。銘傳大學管理科學研究所碩士論文。
黃冠瑋。民國88年。「結合蒙地卡羅模擬法與波動性模型之涉險值分析」。淡江大學財務金融學系碩士論文。
何傳駿。民國88年6 月。「台灣上市公司外匯風險受曝係數衡量與決定因素分析」。國立中正大學企業管理研究所碩士論文。
李俊緯。民國89年6 月。「台灣股市β係數穩定性之研究 - Nonparametric Kernel Method 之應用」。私立實踐大學企業管理研究所碩士論文。
穆炫良。民國89年6 月。「我國上市資訊電子業策略聯盟財務績效之實證研究」。私立東吳大學會計研究所碩士論文。
楊嘉瑜。民國90年6 月。「探討企業購併與策略聯盟對財務績效之影響-以台灣資訊電子產業為例」。私立中原大學企業管理研究所碩士論文。
李忠輝。民國90年6 月。「隨機波動率選擇權定價---基因演算法之運用」。國立東華大學/國際經濟研究所碩士論文。
陳柏年。民國90年6 月。「應用遺傳演算法於財務指標選股策略之探討」。國立中央大學資訊管理學系研究所碩士論文。
江吉雄。民國91年6 月。「遺傳演算法於股市選股與擇時策略之研究」。國立中央大學資訊管理學系研究所碩士論文。
劉慧敏。民國91年6 月。「多目標遺傳演算法於基本面選股策略之應用」。國立中央大學資訊管理學系研究所碩士論文。
李政軒。民國90年6 月。「匯率對股票報酬率影響及暴露係數決定因素之探討」。國立政治大學國際貿易研究所碩士論文。
陳哲瑜。民國92年6 月。「風險值在共同基金績效評估上之應用」。國立中正大學企業管理研究所碩士論文。
林保霖。民國91年6月。「增進蒙地卡羅模擬法評估風險值之績效研究」。國立台北大學企業管理學系碩士論文。
章長原。民國92年6 月。「全球半導體市場趨勢與台灣IC設計產業經營績效之關連性研究」。私立中原大學企業管理研究所碩士論文。
蔡佩怡。民國93年6月。「台灣高度外銷導向公司之風險評估」。國立中興大學企業管理學系碩士論文。
詹菲如。民國93年6 月。「貸款訂價與績效評估-運用選擇權評價模式」。私立淡江大學財務金融研究所碩士論文。
林政寬。民國93年6月。「台灣金控公司的RAROC評估:VaR及ETL之應用」。國立中興大學企業管理學系碩士論文。
賴姵君。民國92年6 月。「供應鏈上合作夥伴市場風險管理之研究-以IC產業為例」。國立成功大學交通管理科學研究所碩士論文。
邱煥能、葉淑君、黃浩良。民國89年。「中心與衛星廠JIT供應鏈存貨整合模式之研究」。工業工程學刊。第17卷第3期。頁301-312。
倪衍森、劉明慧。民國88。「台灣銀行業股票報酬之敏感性分析」。台銀季刊,第23卷第2期。頁159-175。
楊踐為、陳玲慧。民國86年。「台灣股票之系統風險與無風險利率於不同景氣市場時之穩定性探討」。企銀季刊。第21卷第3期。頁57-72。
蘇木春、張孝德。民國93年。機器學習類神經網路、模糊系統以及基因演算法則。全華科技圖書股份有限公司。三版。
王興毅。民國85年。IC製造業營運發展專題。工業技術研究院。
陳鴻碁、王俊程。民國88年。資訊產業傳。中華徵信所股份有限公司。初版。
David Simchi-Levi、Philip Kaminsky、Edith Smithi-Levi著。蘇雄義譯。民國90年。供應鏈之設計與管理。美商麥格羅國際股份有限公司希爾。初版一刷。
Harrell Tumay著。簡聰海、鄒靜寧譯。民國87年。系統模擬。高立圖書股份有限公司。初版。
楊維楨。民國92年。系統分析在經營決策上的應用。五南圖書出版股份有限公司。初版。
邱振崑。民國90年。EXCEL在會計學與財務管理之應用。松崗電腦圖書資料股份有限公司。初版。
張兆旭。民國88年。EXCEL函數應用。松崗電腦圖書資料股份有限公司。初版。
李雅明。民國89年。半導體的故事。新新聞文化事業股份有限公司。初版三刷。
王建華、謝東和、郭秋鈴、覃禹華、彭茂榮、范哲豪、楊雅嵐、謝孟玹、簡志勝、陳俊儒、孟祥鈞及外邀作者。民國93年。半導體工業年鑑。工研院產業經濟與資訊服務中心。

貳、英文文獻
Box, G.E. and G.W. Jenkins, 1970, “Time Series Analysis: Forecasting and Control,” San Francisco: Holden Day.
Blume, M., 1971, “On the assessment of risk,” Journal of Finance 26, pp.1-10.
Booth, J. R. and D. T. Officer, 1985, “Expectations, Interest Rates, and Commercial Bank Stocks,” Journal of Financial Research 18 , pp.51-58.
Bollerslev, T., 1986, “Generalized Autoregressive Conditional Hetero- skedasticity,” Journal of Econometrics 31, pp.307-327
Brown, G.G., Graves, G.W. and M.D. Honczarenko, 1987, “Design and Operation of a Multi-commodity Production/Distribution System Using Primal Goal Decomposition,” Management Science 33(11), pp.1469-1480.
Beder, T.S., 1995, “VaR: Seductive but Dangerous.” Financial analysts Journal, pp.12-24.
Beaman, B.M., 1998, “Supply Chain Design and Analysis: Models and Methods”, Int. J. Production Economics, vol. 55, pp.281-294.
Brook, D., Robert, W., and Mckenzie, D., 1998, “Time-Varying Beta Risk of Australian Industry Portfolios: A Comparison of Modelling Techniques,” Australian Journal of Management 23, pp.1-22.
Jennifer L. Baljko, 1999, “Turmoil in Taiwan – OEMs, Chip makers scramble for answers,” Electronic Buyers’ News.
Berkowiz, J., 2001, “Testing Density Forecasts, with Applications to Risk Management.” Journal of Business and Economic Statistics 19, pp. 465-474
Cohen, K. J. and J. A. Pogue,1967, “An Empirical Evaluation of Alternative Portfolio- Selection Models,” Journal of Business, pp.166-193.
Cohen, M.A., and H.L. Lee, 1985, “Manufacturing Strategy Concept and Methods,” The Management of Productivity and Technology in Manufacturing, pp.153-188.
Cohen, M.A. and Fisher, M., and R. Jaikumar, 1989, “International Manufacturing and Distribution Network: A Normative Model Framework,” Managing International Manufacturing, pp.67-93.
Cohen, M.A. and S. Moon, 1990, “An Integrated Plant Loading Model with Economies of Scale and Scope,” European Journal of Operations Research 50, pp.266-279.
Crnkovic, C. and J. Drachman, 1996, “Quality Control,” Risk 9, pp.138-143
Christoffersen, P. F. , Hahn J. , and A. Inoue, 2001, “Testing and comparing value at risk measures,” Journal of Empirical Finance 8, pp.325-342.
Cohen, M.A. and H.L. Lee, 1989, “Resource Deployment Analysis of Global Manufacturing and Distribution Networks,” Journal of Manufacturing Operation Management 2, pp.81-104.
Duffie, D., and J. Pan, 1997, “An Overview of Value at Risk,” The Journal of Derivatives, Spring, pp.7-49
Dowd. K., 2000, “Adjusting for risk: An improved Sharpe Ratio,” International Review of Economics and Finance 9, pp. 209-222.
Dowd, K., 2002, Measuring Market Risk, John Wiley and Son, Inc.
Efron, B., 1979, “Bootstrap Methods: Another Look at the Jackknife,” The Annals of Statistics 7, pp.1-26
Engle, R.F., 1982, “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of U.K. inflation,” Econometrica 50, pp.987-1008.
Elyasiani, E.and I. Mansur, 1998, “Sensitivity of the Bank Stock Returns Distribution to Changes in the Level and Volatility of Interest Rate: A GARCH-M Model,” Journal of Banking & Finance 22 ,pp.535-563.
Fabozzi, F. J. and J. C. Francis, 1977, “Stability tests for alphas and betas over bull and bear market conditions,” Journal of Finance 32, pp.1093-1099.
Flannery, M. J. and C. M. James, 1984, “The Effect Interest Rate Changes on the Common Stock Returns of Financial Institutions,” Journal of Finance 39, pp.1141-1153.
Fama, E.F. and K.R. French, 1993, “Common Risk Factors in the Return on Stock and Bonds,” Journal of Financial Economics 33, pp.3-56.
Faff, R.W., Hillier and Hillier, 2000, “The Time Beta Risk: An Analysis of Alternative Modeling Techniques,” Journal of Business Finance Accounting 27(5), pp.523-554.
Granger, C.W. J. and P. Newblod, 1974, “Spurious Regression in Econometric,” Journal of Econometrics 12, pp.111-120.
Geoffrion, A.M., and G.W. Graves, 1974, “Multi-commodity Distribution System Design by Bender Decomposition,” Management Sience 20(5), pp.822-844.
Glosten, L.R., Jaganathan, R. and D. Runkle, 1993, “Relationship between the Expected Value and the Volatility of the Nominal Excess Return on Stocks,” Journal of Finance 48, pp.1779-1802
Groenewold and Fraser, 1999, “Time-Varying Estimates of CAPM Betas,” Mathematics and Computers in Simulation 48, pp.531-539.
Holland, J. H., 1975, “Adaptation in natural and artificial systems,” University of Michigan Press, Ann Arbor.
Hendricks, D., 1996, “Evaluation of Value at Risk Models Using Historical Data”, Economics Policy Review 2, pp.37-71.
Hull, J. and A. White, 1998, “Value at Risk When Daily Changes in Market Variable Are Not Normally Distributed,” The Journal of Derivatives, pp.9-19
He J. and L.K. Ng, 1998, “The Foreign Exchange Exposure of Japanese Multinational Corporation,” The Journal of Finance 53(2), pp.733-753.
Hasan Pirkul and Jayaraman Vaidyanathan, 1998, “A Multi-commodity, Multi-plant, Capacitated Facility Location Problem: Formulation and Efficient Heuristic Solution,” Computers Operation Research 25(10), pp. 869-878.
Hull, J. and A. White, 1998, “Value at Risk when Daily Changes in Market Variable Are Not Normally Distributed,” The Journal of Derivatives, pp.9-99
Jorion, P.,1990, “The Exchange-Rate Exposure of U.S. Multinationals,” Journal of Buniness 63, pp.331-345.
J.P. Morgan, 1995, “RiskMetrics.sup.TM - Technical Document, 3rd ed.,” New York, NY, Morgan Guaranty Trust Company.
Jorion, P. and S. J. Khoury, 1996, Financial Risk Management:Domestic and International Dimensions, Cambridge, MA:Blackwell Publishers.
Jorin, P., 1996, “Value at Risk: The New Benchmark for Controlling Market Risk,” University of California, Irvine.
Jorion, P., 1997, Value at Risk: The New Benchmark for Controlling Market Risk, McGraw-Hill Companies, Irwin Professional Publishing.
King, Benjamin F., 1966 “Market and Industry Factors in Stock Price Behavior,” Journal of Business 39, No. 1, pp. 139-190.
Koutmos, G., Lee, U., and Theodossiou, 1994, “Time-Varying Betas and Volatility Persistence in International Stock Markets,” Journal of Economics and Business 46, pp.101-112.
Koray Dogan and Goetschalckx Marc, 1999, “A Primal Decomposition Method for the Integrated Design of Multi-period Production-distribution Systems,” IIE Transactions 31, pp.1027-1036.
Lintner, J., 1965 “Security prices, risk and maximal gains from diversification”, Journal of Finance 20, pp.587-615.
Livingston, Miles, 1977, “Industry Movements of Common Stocks,” Journal of Finance 32(3), pp.861-874
Ljung, G.M., and G.E.P. Box, 1978, “On a Measure of Lack of Fit in Time Series Models,” Biometrika 65, pp.297-303
Lopez, J. A.,1998, ”Methods for evaluating value-at-risk estimates,” Federal Reserve Bank of New York Economic Policy.
Markowitz, H.M., 1952, “Portfolio Selection,” Journal of Finance 7, pp.77-91.
Meyers, Stephen L., 1973, “A Re-examination of Market and Industry Factors in Stock Price Behavior,” Journal of Finance 28(3), pp. 695-705.
Nelson, C.R. and C.I. Plosser, 1982, “Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications,” Journal of Monetary Economics 10, pp.139-162.
Phillips, P.C. and P.Perron, 1988, “Testing for Unit Roots in Time Series Regression,” Biometrica 75, pp.335-346.
Palisade Corporation, 2004, Guide to Evolver: The Genetic Algorithm Solver for Microsoft Excel, Windows Version Release 4.0, N.Y. USA
Reyse, Mario G., 1999, “Size, Time-Varying Beta, and Conditional Heteroscedasticity in UK Stock Returns,” Review of Financial Economics 8, pp.1-10.
Sharpe, W.F., 1964, “Capital Asset Price: A Theory of Market Equilibrium under Conditions of Risk,” Journal of Finance 19, pp.425-442.
Stone, B. K., 1974, “Systematic Interest-Rate Risk in a Two -Index Model of Returns,” Journal of Financial and Quantitative Analysis 9, pp.709-721.
Schwert, G.W., and P.J. Seguin, 1990, “Herteroscedasticity in Stock Returns,” Journal of Finance 45, pp.1129-1155.
Sharpe, W. F., Alexander, G. J., and J. V. Bailey, 1999, Investments, 6th ed., Englewood Cliffs, NJ:Prentice Hall.
Sharpe W.F., 1994, “The Sharpe Ratio”, Journal of Portfolio Management Fall, pp.49-58.
Shan, H., Peter, N., Koyluoglu, H.U. and C. Olivier, 1999, “A Catalyst for Improved Capital Management in the Property and Casualty Insurance Industry”, Journal of Risk Finance, pp.1-18.
Taylor, J.,2001, “Rethinking the Credit-loss Distribution: The Implication for RAROC Modeling,” Commercial Lending Review Vol.16(1), pp.7~13.
Venkatraman, N. and V. Ramanujam, 1986, “Measurement of Business Performance in Strategy Research: A Comparison of Approaches.” The Academy of Management Review, pp.801-815.
Wetmore, J. L. and J. R. Brick, 1994, “Commercial Bank Risk: Market, Interest Rate and Foreign Exchange, “ Journal of Financial Research 17 , pp.585-596.
Wetmore, J. L. and J. R. Brick, 1998, “The Basis Risk Component of Commercial Bank Stock Returns,” Journal of Economics and Business 50 ,pp.67-76.
Yamai Y. and Y. Yoshiba, 2002, “Comparative analyses of expected shortfall and Value-at-Risk (3): Their validity under stress,” Monetary and Economic Studies 20, pp.181-237.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top