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題名 財務時間序列中非線性特質的Agent-Based 基礎 : 遺傳規劃的應用 作者 郭子文 貢獻者 陳樹衡
郭子文日期 1998 上傳時間 2016-05-11 摘要 本論文先以Pagan(1996)所整理的實證結果為代表，對實際金融市場資料常具有的典型特質及其相關的檢定作介紹；接著嘗試建構一個簡單的經濟模型，在沒有很多的外生條件設定下，由模型內生的產生實際金融市場資料常具有的典型特質，本文應用Koza(1992)所發展的遺傳規劃(Genetic Programming)為工具，建立一個具有異質性、調適性的多決策者模型架構，模擬一個含生產者與投機者的人工市場，讓生產者、投機者的行為內生決定，並利用計量檢定分析此市場具有哪些實際市場常見的典型特質，並探討這些特質和經濟制度之間的關聯性。 參考文獻 [1] 張維娟(1 997) ，投機者的學習過程與其經濟效果:遺傳規劃在多決策者模型 上的應用，國立政治大學經濟研究所碩士論文。 [2] Arthur W. B， J. H. Holland, B. LeBaron, R. Palmer, and P. Tayler (1 996),“Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Santa Fe Institute SSRl Working Paper #9625 . [3] Barnet， William A., A. Ronald Gallant, Melvin J. Hinich, Jochen A. Jungeilges, Daniel T. KapJan, and Mark 1. Jensen (1996),“A Single-Blind Controlled Competition Among Tests for Nonlinearity and Chaos", Working Paper [4] Bollerslev, T. (1 986),“Generalized Autoregressive Conditional Heteroskedasticity," Journal of Econometrics, Vol 31， pp.307-327 [5] Brock, W. A., W. D. Dechert, B. LeBaron, and J. Scheinkman (1996), "A Test for Independence Based on the Correlation Dimension", Ecol1omelric Reviews 15 ， pp.197-235. [6] Brock, W. A., D. A. Hsieh, and Blake LeBaron (1 991), Nonlinear Dynαnucs， Chaos, and lnstability : Statistical TheOly ω/d Economic Evidence, Cambridge, MA.: M.I.T Press. [7] Chen, S.-H. and C. -H. Yeh (1 997), “Modelling Speculators with Genetic Programming",forthcoming in Evolutionary Programming VI， Springer-Verlag [8] Chen, S.-H. and C.-H. Yeh (1 997), “ Speculative Trades and Financial Regulations: Simulations Based on Genetic Programming", A11I7lIal Conference 011 Computationallnte/ligenGe for Finoncial Engil7eering (CIFER`97) [9] De Lima, P. F. (1998), "Nonlinearities and Nonstationarities in Stock Returns竹， American Statistical Associatiol7 Joumal of BusiJ/ess & EcoJ7omic SIαtistics， Vol 16. No. 2 [10] Kaplan, Daniel T. (1 994), “ Exceptional Events as Evidence for Determinism", Physicα D 73 , pp.38-48 [11] Koza, J. R. (1992), Genetic Pl`Ogmmming: 0n the Progmmming of Complltel`s by Means of Natuml Selectiol7, M. I.T Press [12] Koza, J. R. (1 994), Genetic Pl`Ogmmming 11 ,Chapter 2. M.I.T Press. [13] Kwiatowski， D., P. C.B. Phillips, P. Schmidt and Y. Shin (1992),“Testing the Null Hypothesis of Stationarity agaínst the Alternatíve of A Unít Root`\\ Journalof Econometrics 54, pp.159-178 . [14] Lux, T. (1996),“The Socío-Economíc Dynamics of Speclllative Markets Interactíng Agents, Chaos, and the Fat Tails ofReturn Distributions," forthcoming ín Joumal of Economic Be J(l` and Ol`gα， nizα110n. [15] Lux, T. (1 997) ，”Vlatility Clustering in Financial Markets: A Micro-Símulation of Interactive Agents," Technicα1 Repol`t, Department ofEconomlcs, University of Bamberg, Germany. [16] Muth, J. F. (1 961),“Rational Expectations and the Theory of Príce Movements", Ecol1ometrica 29, pp.315-33 5. [17] Pagan, A. (1996),“The Econometrics ofFinancial Markets," Journal of Enψirical Finance 3, pp.15-1 02. [18] Tayler, P. (1 995),“Modelling Artificial Stocks Markets lIsing Genetic Algoríthms," in S. Goonatilake and P. Treleaven (eds.), lntelligent Systemsfor Finαnce and Business, pp.271-288. [19]Tsay， R., (1986),“Nonlinearity Tests for Time Series", Biometrika 73} 461-466. 描述 碩士
國立政治大學
經濟學系資料來源 http://thesis.lib.nccu.edu.tw/record/#G91NCCU5882012 資料類型 thesis dc.contributor.advisor 陳樹衡 zh_TW dc.contributor.author (Authors) 郭子文 zh_TW dc.creator (作者) 郭子文 zh_TW dc.date (日期) 1998 en_US dc.date.accessioned 2016-05-11 - dc.date.available 2016-05-11 - dc.date.issued (上傳時間) 2016-05-11 - dc.identifier (Other Identifiers) G91NCCU5882012 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/96440 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經濟學系 zh_TW dc.description.abstract (摘要) 本論文先以Pagan(1996)所整理的實證結果為代表，對實際金融市場資料常具有的典型特質及其相關的檢定作介紹；接著嘗試建構一個簡單的經濟模型，在沒有很多的外生條件設定下，由模型內生的產生實際金融市場資料常具有的典型特質，本文應用Koza(1992)所發展的遺傳規劃(Genetic Programming)為工具，建立一個具有異質性、調適性的多決策者模型架構，模擬一個含生產者與投機者的人工市場，讓生產者、投機者的行為內生決定，並利用計量檢定分析此市場具有哪些實際市場常見的典型特質，並探討這些特質和經濟制度之間的關聯性。 zh_TW dc.description.tableofcontents 第一章 緒論..........1 第二章 文獻回顧..........5 2.1 簡要說明..........5 2.1.1 關於Agent-Based之說明 2.1.2 關於所列文章之說明 2.2 Lux(1996、1997)、Tayler(1995)和Arthur(1996)文章..........6 2.3 Lux、Tayler、Arthur文章與本論文的比較..........13 第三章 模型建構..........15 第四章 遺傳規劃的學習..........18 4.1 簡介..........18 4.2 遺傳規劃的設計與運作..........19 4.3 模擬結果的簡單敘述統計..........21 4.4 演化至9000代時，Tree平均的結點數和深度..........24 第五章 模擬結果的統計檢定分析..........33 5.1檢定進行步驟..........33 5.2檢定概述及有關設定..........35 5.3檢定結果分析..........40 第六章 結論與未來研究方向..........45 附錄 表格..........46 參考文獻..........95 zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G91NCCU5882012 en_US dc.title (題名) 財務時間序列中非線性特質的Agent-Based 基礎 : 遺傳規劃的應用 zh_TW dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) [1] 張維娟(1 997) ，投機者的學習過程與其經濟效果:遺傳規劃在多決策者模型 上的應用，國立政治大學經濟研究所碩士論文。 [2] Arthur W. B， J. H. Holland, B. LeBaron, R. Palmer, and P. Tayler (1 996),“Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Santa Fe Institute SSRl Working Paper #9625 . [3] Barnet， William A., A. Ronald Gallant, Melvin J. Hinich, Jochen A. Jungeilges, Daniel T. KapJan, and Mark 1. Jensen (1996),“A Single-Blind Controlled Competition Among Tests for Nonlinearity and Chaos", Working Paper [4] Bollerslev, T. (1 986),“Generalized Autoregressive Conditional Heteroskedasticity," Journal of Econometrics, Vol 31， pp.307-327 [5] Brock, W. A., W. D. Dechert, B. LeBaron, and J. Scheinkman (1996), "A Test for Independence Based on the Correlation Dimension", Ecol1omelric Reviews 15 ， pp.197-235. [6] Brock, W. A., D. A. Hsieh, and Blake LeBaron (1 991), Nonlinear Dynαnucs， Chaos, and lnstability : Statistical TheOly ω/d Economic Evidence, Cambridge, MA.: M.I.T Press. [7] Chen, S.-H. and C. -H. Yeh (1 997), “Modelling Speculators with Genetic Programming",forthcoming in Evolutionary Programming VI， Springer-Verlag [8] Chen, S.-H. and C.-H. Yeh (1 997), “ Speculative Trades and Financial Regulations: Simulations Based on Genetic Programming", A11I7lIal Conference 011 Computationallnte/ligenGe for Finoncial Engil7eering (CIFER`97) [9] De Lima, P. F. (1998), "Nonlinearities and Nonstationarities in Stock Returns竹， American Statistical Associatiol7 Joumal of BusiJ/ess & EcoJ7omic SIαtistics， Vol 16. No. 2 [10] Kaplan, Daniel T. (1 994), “ Exceptional Events as Evidence for Determinism", Physicα D 73 , pp.38-48 [11] Koza, J. R. (1992), Genetic Pl`Ogmmming: 0n the Progmmming of Complltel`s by Means of Natuml Selectiol7, M. I.T Press [12] Koza, J. R. (1 994), Genetic Pl`Ogmmming 11 ,Chapter 2. M.I.T Press. [13] Kwiatowski， D., P. C.B. Phillips, P. Schmidt and Y. Shin (1992),“Testing the Null Hypothesis of Stationarity agaínst the Alternatíve of A Unít Root`\\ Journalof Econometrics 54, pp.159-178 . [14] Lux, T. (1996),“The Socío-Economíc Dynamics of Speclllative Markets Interactíng Agents, Chaos, and the Fat Tails ofReturn Distributions," forthcoming ín Joumal of Economic Be J(l` and Ol`gα， nizα110n. [15] Lux, T. (1 997) ，”Vlatility Clustering in Financial Markets: A Micro-Símulation of Interactive Agents," Technicα1 Repol`t, Department ofEconomlcs, University of Bamberg, Germany. [16] Muth, J. F. (1 961),“Rational Expectations and the Theory of Príce Movements", Ecol1ometrica 29, pp.315-33 5. [17] Pagan, A. (1996),“The Econometrics ofFinancial Markets," Journal of Enψirical Finance 3, pp.15-1 02. [18] Tayler, P. (1 995),“Modelling Artificial Stocks Markets lIsing Genetic Algoríthms," in S. Goonatilake and P. Treleaven (eds.), lntelligent Systemsfor Finαnce and Business, pp.271-288. [19]Tsay， R., (1986),“Nonlinearity Tests for Time Series", Biometrika 73} 461-466. zh_TW
