Publications-Theses

題名 貝氏分量迴歸的探討與應用-以台灣股價報酬率資料為例
作者 陳繼舜
貢獻者 翁久幸
陳繼舜
關鍵詞 分量迴歸
貝氏分量迴歸
馬可夫鍊蒙地卡羅方法
股價報酬率
日期 2006
上傳時間 18-Sep-2009 20:09:42 (UTC+8)
摘要 分量迴歸在近幾年來的應用相當廣泛,但透過貝氏方法估計分量迴歸參數,是由Yu & Moyeed(2001)所提出,拜電腦運算發達之賜而生的新估計方法,因此在實證應用上的研究,貝氏分量迴歸仍在起步的狀態。並且應用馬可夫鍊蒙地卡羅方法的貝氏分量迴歸,在後驗分配的收斂上並沒有類似的探討文獻。因此本研究嘗試以馬可夫鍊蒙地卡羅方法的應用觀點出發,研究運用貝氏方法的分量迴歸估計是否達到馬可夫鍊所重視的收斂至穩態分配,也就是利用模擬資料,探討使用馬可夫鍊蒙地卡羅方法的貝氏分量迴歸在何種情況下,具有較好的收斂情形,以及選擇適當的提議分配。接著以台灣上市公司為例,依電子、紡織以及塑膠產業為別,利用貝氏分量迴歸,觀察民國86~90年,以及91~95年兩區間,股價報酬率在各分量下與財務比率的關連性,並依產業分別進行探討。

本論文研究結果指出,貝氏分量迴歸在使用時仍須注意馬可夫鍊的收斂情形,將馬可夫鍊的接受頻率定在約20%~30%為佳,且估計結果與Koenker & Bassett(1978)所提出的無母數方法相當一致。在實證資料的分析上,以電子、紡織以及塑膠產業各別的配適結果來看,都依產業別的不同而具有合理的解釋,但貝氏分量迴歸容易因自變數值域的問題,造成馬可夫鍊接受頻率不理想,以及收斂速度過慢的情形,因此在應用貝氏分量迴歸時,自變數值域的影響需要納入考慮,並仍須選擇適當的提議分配、馬可夫鍊重複次數,所得到的結果才會較佳。
參考文獻 徐美珍(2003),企業財務危機之預測,政治大學統計研究所碩士論文
鄭瑞美(2001)股票報酬與財務比率關係之研究--總體經濟因素與產業別之影響,政治大學會計研究所碩士論文
Bassett, G. & Chen H. L.(2001)”Return-Based Attribution Using Regression Quantiles”, Empirical Economics, Vol. 26, 293-305
Buchinsky, M.(1995)”Quantile regression, Box-Cox transformation model, and the U.S. wage structure, 1963-1987”, Journal of Econometrics, Volume 65, 109-154
Bhandari, L. C.(1988)”Debt/Equity Ratio and Expected Common Stock Returns: Empirical Evidence”, Journal of Finance, Vol. 43, 507-528
Diaconis, P. & Sturmfels, B.(1998)”Algebraic algorithms for sampling from conditional distributions”, Ann. Statist., Vol 26, 363-397
Eide, E. & Showalter, M. H.(1998)” The Effect of School Quality on Student Performance: A Quantile Regression Approach”, Economics Letters, Vol. 58, 345-350
Gelfand, A. E., Hills, S. E., Racine-Poon, A. & Smith, A. F. M.(1990)”Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling”, J. Am. Statist. Ass., Vol. 85, No. 412, 972-985
Gelman A.(1995)”Inference and monitoring convergence.” Markov Chain Monte Carlo in Practice, London: Chapman & Hall, 131-143
Gelman, A., Roberts, G.. O. & Gilks, W. R.(1996)”Efficient Metropolis jumping rules”, Bayesian Statistics, Vol. 5, 599-607
Gelman, A. & Rubin, D. B.(1992)”Inference from iterative simulation using multiple sequences” Statist. Sci., Vol. 7, 457-472
Geyer, C. J. & Thompson, E. A.(1995) ” Annealing Markov Chain Monte Carlo with Applications to Ancestral Inference”, J. Am. Statist. Ass., Vol. 90, No. 431, 909-920
Hastings, W. K.(1970)” Monte Carlo sampling methods using Markov chains and their applications”, Biometrika, Vol. 57(1), 97-109
Hendricks, W. & Koenker, R.(1992)” Hierarchical Spline Models for Conditional Quantiles and the Demand for Electricity”, J. Am. Statist. Ass., Vol. 87, No. 417,
Holthausen, R. W. & Lacker, D. F.(1992)”The Prediction of Stock Returns Using Financial Statement Information”, Journal of Accounting and Economics 15, 373-411
Hull, J. & White, A.(1998)” Value at risk when daily changes in market variables are not normally distributed”, J. Deriv., Vol. 5, No. 3, 9-19
Hobert, J. P. & Jones, G. L.(2001)”Honest Exploration of Intractable Probability Distributions via Markov Chain Monte Carlo”, Statist. Sci., Vol. 16, 312-334
Koenker, R. & Bassett Jr., G.(1978)”Regression Quantiles”, Econometrica, Vol. 46, No.1, 33-50
Koenker & Xiao(2006)”Quantile Autoregression”, J. Am. Statist. Ass., Vol. 101, No. 475, 980-1002
Martikainen, T.(1993)”Stock returns and classification pattern of firm-specific financial variables: empirical evidence with finnish data”, Journal of Business Finance & Accounting, vol. 20, No. 4, 537-557
McCulloch, C. E.(1997)” Maximum Likelihood Algorithms for Generalized Linear Mixed Models”, J. Am. Statist. Ass., Vol. 92, 162-170
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H. & Teller, E.(1953)”Equation of state calculations by fast computing machines”, J. Chem. Phys. 21, 1087-1092
Meyn & Tweedie(1993)Markov Chains and Stochastic Stability, London: Springer-Verlag
Muller, P.(1993)”A generic approach to posterior integration and Gibbs sampling”, Tech. Rep., ISDS, Duke University
Ou, J. A. & Penman S. H.(1989)”Financial Statement Analysis and the Prediction of Stock Return”, Journal of Accounting and Economics 11, 295-329
Pandey, G. R. & Nguyen, V. T. V.(1999)” A comparative study of regression based methods in regional flood frequency analysis”, Journal of Hydrology, Vol. 225,92-101
Raftery, A. E. & Lewis, S. M.(1995)” Implementing MCMC” Markov Chain Monte Carlo in Practice, London: Chapman & Hall, 115-130
Spiegelhalter, Thomas & Best(1999)” WinBUGS-A Bayesian modelling framework: Concepts, structure, and extensibility”, Statistics and Computing, Vol. 10, 325-337
Taylor(1999)”A quantile regression approach to estimating the distribution of multiperiod returns”, J. Deriv., Vol. 24, 64-78
Tierney, L.(1994)” Markov Chains for Exploring Posterior Distributions”, Ann. Statist., Vol. 22, No. 4, 1701-1762
Yu, K. & Moyeed, R. A.(2001)”Bayesian Quantile Regression”, Statistics and Probability Letters, Vol. 54, Issue 4, 437-447
Yu, K. & Stander, J.(2007)”Bayesian Analysis of a Tobit Quantile Regression Model ”
Yu, K., Lu, Z. & Stander, J.(2003)” Quantile Regression: Applications and Current Research Areas”, J. Roy. Statist. Soc. D, Vol. 55, 3-23
描述 碩士
國立政治大學
統計研究所
94354015
95
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0094354015
資料類型 thesis
dc.contributor.advisor 翁久幸zh_TW
dc.contributor.author (Authors) 陳繼舜zh_TW
dc.creator (作者) 陳繼舜zh_TW
dc.date (日期) 2006en_US
dc.date.accessioned 18-Sep-2009 20:09:42 (UTC+8)-
dc.date.available 18-Sep-2009 20:09:42 (UTC+8)-
dc.date.issued (上傳時間) 18-Sep-2009 20:09:42 (UTC+8)-
dc.identifier (Other Identifiers) G0094354015en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/36921-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計研究所zh_TW
dc.description (描述) 94354015zh_TW
dc.description (描述) 95zh_TW
dc.description.abstract (摘要) 分量迴歸在近幾年來的應用相當廣泛,但透過貝氏方法估計分量迴歸參數,是由Yu & Moyeed(2001)所提出,拜電腦運算發達之賜而生的新估計方法,因此在實證應用上的研究,貝氏分量迴歸仍在起步的狀態。並且應用馬可夫鍊蒙地卡羅方法的貝氏分量迴歸,在後驗分配的收斂上並沒有類似的探討文獻。因此本研究嘗試以馬可夫鍊蒙地卡羅方法的應用觀點出發,研究運用貝氏方法的分量迴歸估計是否達到馬可夫鍊所重視的收斂至穩態分配,也就是利用模擬資料,探討使用馬可夫鍊蒙地卡羅方法的貝氏分量迴歸在何種情況下,具有較好的收斂情形,以及選擇適當的提議分配。接著以台灣上市公司為例,依電子、紡織以及塑膠產業為別,利用貝氏分量迴歸,觀察民國86~90年,以及91~95年兩區間,股價報酬率在各分量下與財務比率的關連性,並依產業分別進行探討。

本論文研究結果指出,貝氏分量迴歸在使用時仍須注意馬可夫鍊的收斂情形,將馬可夫鍊的接受頻率定在約20%~30%為佳,且估計結果與Koenker & Bassett(1978)所提出的無母數方法相當一致。在實證資料的分析上,以電子、紡織以及塑膠產業各別的配適結果來看,都依產業別的不同而具有合理的解釋,但貝氏分量迴歸容易因自變數值域的問題,造成馬可夫鍊接受頻率不理想,以及收斂速度過慢的情形,因此在應用貝氏分量迴歸時,自變數值域的影響需要納入考慮,並仍須選擇適當的提議分配、馬可夫鍊重複次數,所得到的結果才會較佳。
zh_TW
dc.description.tableofcontents 第一章 緒論 1
第一節 研究背景及動機 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 股價報酬率的影響因素 5
第二節 分量迴歸的文獻探討 6
第三節 馬可夫鍊蒙地卡羅方法之相關文獻 8
第三章 研究方法 10
第一節 分量迴歸 10
第二節 貝氏分量迴歸 14
第三節 馬可夫鍊蒙地卡羅方法 17
第四章 模擬與實證分析 24
第一節 模擬資料之非線性分量迴歸 24
第二節 實證資料描述及來源 29
第三節 變數選取與說明 31
第四節 基本統計量分析 37
第五節 分量迴歸結果 41
第五章 結論與建議 47
參考文獻 49
附 錄 52
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dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0094354015en_US
dc.subject (關鍵詞) 分量迴歸zh_TW
dc.subject (關鍵詞) 貝氏分量迴歸zh_TW
dc.subject (關鍵詞) 馬可夫鍊蒙地卡羅方法zh_TW
dc.subject (關鍵詞) 股價報酬率zh_TW
dc.title (題名) 貝氏分量迴歸的探討與應用-以台灣股價報酬率資料為例zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 徐美珍(2003),企業財務危機之預測,政治大學統計研究所碩士論文zh_TW
dc.relation.reference (參考文獻) 鄭瑞美(2001)股票報酬與財務比率關係之研究--總體經濟因素與產業別之影響,政治大學會計研究所碩士論文zh_TW
dc.relation.reference (參考文獻) Bassett, G. & Chen H. L.(2001)”Return-Based Attribution Using Regression Quantiles”, Empirical Economics, Vol. 26, 293-305zh_TW
dc.relation.reference (參考文獻) Buchinsky, M.(1995)”Quantile regression, Box-Cox transformation model, and the U.S. wage structure, 1963-1987”, Journal of Econometrics, Volume 65, 109-154zh_TW
dc.relation.reference (參考文獻) Bhandari, L. C.(1988)”Debt/Equity Ratio and Expected Common Stock Returns: Empirical Evidence”, Journal of Finance, Vol. 43, 507-528zh_TW
dc.relation.reference (參考文獻) Diaconis, P. & Sturmfels, B.(1998)”Algebraic algorithms for sampling from conditional distributions”, Ann. Statist., Vol 26, 363-397zh_TW
dc.relation.reference (參考文獻) Eide, E. & Showalter, M. H.(1998)” The Effect of School Quality on Student Performance: A Quantile Regression Approach”, Economics Letters, Vol. 58, 345-350zh_TW
dc.relation.reference (參考文獻) Gelfand, A. E., Hills, S. E., Racine-Poon, A. & Smith, A. F. M.(1990)”Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling”, J. Am. Statist. Ass., Vol. 85, No. 412, 972-985zh_TW
dc.relation.reference (參考文獻) Gelman A.(1995)”Inference and monitoring convergence.” Markov Chain Monte Carlo in Practice, London: Chapman & Hall, 131-143zh_TW
dc.relation.reference (參考文獻) Gelman, A., Roberts, G.. O. & Gilks, W. R.(1996)”Efficient Metropolis jumping rules”, Bayesian Statistics, Vol. 5, 599-607zh_TW
dc.relation.reference (參考文獻) Gelman, A. & Rubin, D. B.(1992)”Inference from iterative simulation using multiple sequences” Statist. Sci., Vol. 7, 457-472zh_TW
dc.relation.reference (參考文獻) Geyer, C. J. & Thompson, E. A.(1995) ” Annealing Markov Chain Monte Carlo with Applications to Ancestral Inference”, J. Am. Statist. Ass., Vol. 90, No. 431, 909-920zh_TW
dc.relation.reference (參考文獻) Hastings, W. K.(1970)” Monte Carlo sampling methods using Markov chains and their applications”, Biometrika, Vol. 57(1), 97-109zh_TW
dc.relation.reference (參考文獻) Hendricks, W. & Koenker, R.(1992)” Hierarchical Spline Models for Conditional Quantiles and the Demand for Electricity”, J. Am. Statist. Ass., Vol. 87, No. 417,zh_TW
dc.relation.reference (參考文獻) Holthausen, R. W. & Lacker, D. F.(1992)”The Prediction of Stock Returns Using Financial Statement Information”, Journal of Accounting and Economics 15, 373-411zh_TW
dc.relation.reference (參考文獻) Hull, J. & White, A.(1998)” Value at risk when daily changes in market variables are not normally distributed”, J. Deriv., Vol. 5, No. 3, 9-19zh_TW
dc.relation.reference (參考文獻) Hobert, J. P. & Jones, G. L.(2001)”Honest Exploration of Intractable Probability Distributions via Markov Chain Monte Carlo”, Statist. Sci., Vol. 16, 312-334zh_TW
dc.relation.reference (參考文獻) Koenker, R. & Bassett Jr., G.(1978)”Regression Quantiles”, Econometrica, Vol. 46, No.1, 33-50zh_TW
dc.relation.reference (參考文獻) Koenker & Xiao(2006)”Quantile Autoregression”, J. Am. Statist. Ass., Vol. 101, No. 475, 980-1002zh_TW
dc.relation.reference (參考文獻) Martikainen, T.(1993)”Stock returns and classification pattern of firm-specific financial variables: empirical evidence with finnish data”, Journal of Business Finance & Accounting, vol. 20, No. 4, 537-557zh_TW
dc.relation.reference (參考文獻) McCulloch, C. E.(1997)” Maximum Likelihood Algorithms for Generalized Linear Mixed Models”, J. Am. Statist. Ass., Vol. 92, 162-170zh_TW
dc.relation.reference (參考文獻) Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H. & Teller, E.(1953)”Equation of state calculations by fast computing machines”, J. Chem. Phys. 21, 1087-1092zh_TW
dc.relation.reference (參考文獻) Meyn & Tweedie(1993)Markov Chains and Stochastic Stability, London: Springer-Verlagzh_TW
dc.relation.reference (參考文獻) Muller, P.(1993)”A generic approach to posterior integration and Gibbs sampling”, Tech. Rep., ISDS, Duke Universityzh_TW
dc.relation.reference (參考文獻) Ou, J. A. & Penman S. H.(1989)”Financial Statement Analysis and the Prediction of Stock Return”, Journal of Accounting and Economics 11, 295-329zh_TW
dc.relation.reference (參考文獻) Pandey, G. R. & Nguyen, V. T. V.(1999)” A comparative study of regression based methods in regional flood frequency analysis”, Journal of Hydrology, Vol. 225,92-101zh_TW
dc.relation.reference (參考文獻) Raftery, A. E. & Lewis, S. M.(1995)” Implementing MCMC” Markov Chain Monte Carlo in Practice, London: Chapman & Hall, 115-130zh_TW
dc.relation.reference (參考文獻) Spiegelhalter, Thomas & Best(1999)” WinBUGS-A Bayesian modelling framework: Concepts, structure, and extensibility”, Statistics and Computing, Vol. 10, 325-337zh_TW
dc.relation.reference (參考文獻) Taylor(1999)”A quantile regression approach to estimating the distribution of multiperiod returns”, J. Deriv., Vol. 24, 64-78zh_TW
dc.relation.reference (參考文獻) Tierney, L.(1994)” Markov Chains for Exploring Posterior Distributions”, Ann. Statist., Vol. 22, No. 4, 1701-1762zh_TW
dc.relation.reference (參考文獻) Yu, K. & Moyeed, R. A.(2001)”Bayesian Quantile Regression”, Statistics and Probability Letters, Vol. 54, Issue 4, 437-447zh_TW
dc.relation.reference (參考文獻) Yu, K. & Stander, J.(2007)”Bayesian Analysis of a Tobit Quantile Regression Model ”zh_TW
dc.relation.reference (參考文獻) Yu, K., Lu, Z. & Stander, J.(2003)” Quantile Regression: Applications and Current Research Areas”, J. Roy. Statist. Soc. D, Vol. 55, 3-23zh_TW