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題名 財務市場資訊不對稱下之市場現象與參與者行為之研究
作者 謝易霖
貢獻者 陳樹衡
謝易霖
關鍵詞 資訊不對稱
資訊散佈
雙方喊價市場
實驗經濟學
強化學習模型
日期 2007
上傳時間 18-Sep-2009 16:06:20 (UTC+8)
摘要 財務市場資訊不對稱的現象已由不少學者研究, 本文利用真人實驗方法對此一議題再檢驗, 依照擁有資訊的程度分為: 完全知訊者、不完全知訊者與外部者。結果發現, 價格收斂情形與知訊者的多寡有顯著相關, 然而卻與知訊品質的高低相關性較低。成交量與價格收斂情形呈反向關係, 雖顯著但相關性有限, 我們推測對資產定價的落差雖是交易動機的原因之一,但並非僅只有此原因。市場內財富差異性亦與價格收斂有所相關, 價格收斂越好的市場, 市場吉尼係數就越小, 顯示參與者間貧富落差越小。與過去文獻差異較多是擁有較多資訊的參與者不見得有較好的利得,因此, 擁有資訊的程度不再是決定利得的唯一因素, 策略的選擇將是影響利潤的重要因素之一。

根據實驗結果, 發現限價單使用比例與期末利得有顯著的正相關, 且排名較為前面的參與者能較快學習到此一結果。本文將限價單使用比例的增減做為一策略選擇, 並利用三種強化學習模型解釋市場現象, 此三種模型皆從Roth 與Erev 的文獻中而來, 前二種模型中有二種參數: 新進因子與經驗因子, 新進因子表示前一期策略的動機對本期採同一策略動機的影響,經驗因子則表示前其策略所引發的利潤對本期策略動機的影響, 此一參數亦隱含了參與者強化學習之能力。第三種模型則多增加了參與者對利潤敏感的的測度。結果發現, 無論是此三種模型的何種參數, 在不同資訊結構的市場與不同類型的參與者間幾無差異。然而, 若以參與者利得的表現區分, 參與者對過去利潤的反應, 即經驗因子, 有顯著的差異, 說明了利潤高低與是否能從過去利潤結果學習到經驗(即強化學習能力) 有密切關係。上述三個現象說明, 參與者的行為參數在進入實驗室前就已決定了,因此利用市場環境與參與者身份將之分類比較的差異性不大, 但這樣的差異卻會影響之後的利得。故本文的結論與過去文獻不同的是, 在此實驗中決定參與者利得
多寡的不再是資訊掌握程度, 而是其學習(策略) 之能力。
參考文獻 中文部分:
謝宗林(1988)。股票市場與內線交易。經濟前瞻第九號。
唐恕(民87)。異質訊息下內線交易與交易策略與市場績效之研究。輔仁大學金融研究所碩士論文。
詹場．胡星陽(2001.7)。流動性衡量方法之綜合評論。國家科學委員會研究彙刊。11卷3期。205-221。
張萬同(2003)。衍生性金融市場之管理、運作、及效率。桂冠圖書。
周星．林清勝(2004)。實驗經濟學最新發展動動態述評。學術月刊
楊曉嵐．金雪軍(2005)。基於實驗經濟學方法的證卷市場信息有效性研究。浙江大學學報,Vol.35,No6,p80–88。
李家瑋(民94)。比較遺傳演算法語強化學習: 以代理人彩券市場為例。國立政治大學經濟學系碩士論文。
Bibliography
Anand, A. and Martell, T. (2001). ”informed” limit order trading. working paper.
Ang, J. and Schwarz, T. (1985). Risk aversion and information structure:An experimental study of price variability in securities markets.The Journal of Finance, 40:825–844.
Banks, J. (1985). Price-conveyed information versus observed insider behavior: A note on rational expectations convergence. The Journal of Political Economy, 94(4):807–81.
Chan, N., LeBaron, B, L. A., and Poggio, T. (1998). Information dissemination and aggregation in asset markets with simple intelligent traders. working paper.
Chmura, T. and Piz, T. (2007). An extended reinforcement algorithm for estimation of human behaviour in experimental congestion games. Journal of Artificial Societies and Social Simulation,10(2).
Cliff, D. (2001). Evolution of market mechanism through a continuous space of auction-types. Techreport HPL-2001-326, Information Infrastructure Laboratory HP Laboratories Bristol.
Duffy, J. and Unver, M. (2006). Asset price bubble and crashes with near-zero-intelligence traders. Economic theory, 27:537–563.
Erev, I. and Roth, A. E. (1998). Prediciting how people play games: Reinforcement learning in experimental games with unique, mixed strategy euqilibri. The American Economic Review, 88(4):848–881.
Fama, E. (1970). Efficient capital markets: a review of theory an empirical work. The Journal of Finance, 25(2):383–417.
Feltovich, N. (2000). Reinforcement-based vs. belief-based learning models in experimental asymmetric-information games. Econometrica, 68(3):605–641.
Figlewski, S. (1978). ”market efficiency” in a market with heterogeneous
information. The Journal of Political Economy, 86(4):581–
579.
Flood, M., Koedijk, K., van Dijk, M., and van Leeuwen, I. (2002). Dividing the pie: Asymmetrically informed dealers and market transparency.working paper.
Forsythe, R. and Lundholm, R. (1990). Information aggregation in an experimental market. Econometrica, 58(2):309–347.
Foster, F. and Viswanathan (1994). Strategic trading with asymmetrically informed traders and long-lived information. The Journal of Financial and Quantitative Analysis, 29(24):499–518.
Friedman, D. and Sunder, S. (1994). Experimental methods: A primer for economists. Cambridge university press.
Gil-Bazo, J.and Moreno, D. and Tapia, M. (2005). Price dynamics, informational efficiency and wealth distribution in continuous double auction markets. working paper.
Glosten, L. and Milgrom, P. (1985). Bid, ask and transaction prices in a specialist market with heterogeneously informed traders. Journal of Financial Economics, 114:71–100.
Gode, D. K. and Sunder, S. (1993). Allocative efficiency of markets with zero-intelligence traders: Market as a partial substutute for individual rationality. The Journal of Political Economy, 101(1):119-137.
Gresik, T. A. and Satterthwaite, M. A. (1985). The rate at which a simple market becomes efficient as the number of traders increases:An asymptotic result for optimal trading mechanisms. Discussion Paper.
Grossklags, J. and Schmidt, C. (2006). Software agents and market (in) efficiency: a human trader experiment. In Forthcoming in IEEE Trans SMC Part C., Special Issue on Game-theoretic Analysis & Simulation of Negotiation Agents.
Kyle, A. (1985). Continuous auctions and insider trading. Econometrica, 53(6):1315–1336.
LeRoy, S. F. and LaCivita, C. (1981). Risk aversion and the dispersion of asset price. The Journal of Business, 54(4):535–547.
Matsui, H., Koyama, Y., and Ishiyama, K. (2005). A report of large scale gaming simulation using a u-mart system in economic education.In Proceedings of the Third International Conference on Creating, Connecting and Collaborating through Computing.
Nakajim, Y., Ono, I., Sato, H., Mori, N., Kita, H., Matsui, H., Taniguchi, K., Deguchi, H., Terano, T., and Shiozawa, Y. (2004). Introducing virtual futures market systemu-mart. In EES 2004 :Experiments in Economic Sciences - New Approaches to Solving Real-world Problems.
O’Brien, J. and Srivastava, S. (1991). Dynamic stock markets with multiple assets: an experiment analysis. The Journal of Finance, 46(5):1111–1138.
Plott, C. and Sunder (1988). Rational expectation and the aggregation of diverse information in laboratory security markets. Econometrica, 56(5):1085–1118.
Plott, C. and Sunder, S. (1982). Efficiency of experimental security markets with insider information: an application of rational expectation models. The Journal of Political Economy, 90(40):663–698.
Roth, A. E. and Erev, I. (1995). Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term. Games and Economic Behavior, 8:164–212.
Sarin, R. and Vahid, F. (2001). Predicting how people play games: A simple dynamic model of choice. Games and Economic Behavior,34:104–122.
Sato, H., Matsui, H., Ono, I., Kita, H., Terano, T., Deguchi, H., and Shiozawa, Y. (2001). U-mart project: learning economic principles from the bottom by both human and software agents. In JSAI2001 workshop, pages 121–131.
Sunder, S. (1995). Experimental asset markets: A survey 　, The handbook of experimental economics. Princeton university press.
Theissen, E. (2000). Market structure, informational efficiency and liquidity: An experimental comparison of auction and dealer markets. Journal of financial markets, 3:333–363.
Victoire, T. and Suganthan, P. N. (2007). Differential evolution and evolutionary programming for solving non-convex economic dispatch problems. Technical report, Agency for Science, Technology and Reasearch. Agency for Science, Technology and Reasearch.
Wang, S., Tseng, J., Tai, C., Lai, K., Chen, S., and Li, S. (2008). Network topology of an experimental futures exchange. European Physical Journal B, 26:105–111.
描述 碩士
國立政治大學
經濟研究所
93258012
96
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0932580121
資料類型 thesis
dc.contributor.advisor 陳樹衡zh_TW
dc.contributor.author (Authors) 謝易霖zh_TW
dc.creator (作者) 謝易霖zh_TW
dc.date (日期) 2007en_US
dc.date.accessioned 18-Sep-2009 16:06:20 (UTC+8)-
dc.date.available 18-Sep-2009 16:06:20 (UTC+8)-
dc.date.issued (上傳時間) 18-Sep-2009 16:06:20 (UTC+8)-
dc.identifier (Other Identifiers) G0932580121en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/35812-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經濟研究所zh_TW
dc.description (描述) 93258012zh_TW
dc.description (描述) 96zh_TW
dc.description.abstract (摘要) 財務市場資訊不對稱的現象已由不少學者研究, 本文利用真人實驗方法對此一議題再檢驗, 依照擁有資訊的程度分為: 完全知訊者、不完全知訊者與外部者。結果發現, 價格收斂情形與知訊者的多寡有顯著相關, 然而卻與知訊品質的高低相關性較低。成交量與價格收斂情形呈反向關係, 雖顯著但相關性有限, 我們推測對資產定價的落差雖是交易動機的原因之一,但並非僅只有此原因。市場內財富差異性亦與價格收斂有所相關, 價格收斂越好的市場, 市場吉尼係數就越小, 顯示參與者間貧富落差越小。與過去文獻差異較多是擁有較多資訊的參與者不見得有較好的利得,因此, 擁有資訊的程度不再是決定利得的唯一因素, 策略的選擇將是影響利潤的重要因素之一。

根據實驗結果, 發現限價單使用比例與期末利得有顯著的正相關, 且排名較為前面的參與者能較快學習到此一結果。本文將限價單使用比例的增減做為一策略選擇, 並利用三種強化學習模型解釋市場現象, 此三種模型皆從Roth 與Erev 的文獻中而來, 前二種模型中有二種參數: 新進因子與經驗因子, 新進因子表示前一期策略的動機對本期採同一策略動機的影響,經驗因子則表示前其策略所引發的利潤對本期策略動機的影響, 此一參數亦隱含了參與者強化學習之能力。第三種模型則多增加了參與者對利潤敏感的的測度。結果發現, 無論是此三種模型的何種參數, 在不同資訊結構的市場與不同類型的參與者間幾無差異。然而, 若以參與者利得的表現區分, 參與者對過去利潤的反應, 即經驗因子, 有顯著的差異, 說明了利潤高低與是否能從過去利潤結果學習到經驗(即強化學習能力) 有密切關係。上述三個現象說明, 參與者的行為參數在進入實驗室前就已決定了,因此利用市場環境與參與者身份將之分類比較的差異性不大, 但這樣的差異卻會影響之後的利得。故本文的結論與過去文獻不同的是, 在此實驗中決定參與者利得
多寡的不再是資訊掌握程度, 而是其學習(策略) 之能力。		zh_TW
dc.description.tableofcontents 1 緒論. . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.1 研究背景與動機. . . . . . . . . . . . . . . . . . . . 14
1.2 研究方法. . . . . . . . . . . . . . . . . . . . . . . 16
1.3 本文架構. . . . . . . . . . . . . . . . . . . . . . . 17
2 文獻回顧. . . . . . . . . . . . . . . . . . . . . . . . 18
2.1 市場總體面分析. . . . . . . . . . . . . . . . . . . . 19
2.2 參與者的行為與策略. . . . . . . . . . . . . . . . . . 28
2.3 本章結論. . . . . . . . . . . . . . . . . . . . . . . 31
3 實驗設計. . . . . . . . . . . . . . . . . . . . . . . . 33
3.1 實驗概述. . . . . . . . . . . . . . . . . . . . . . . 33
3.2 實驗架構. . . . . . . . . . . . . . . . . . . . . . . 35
3.3 實驗流程. . . . . . . . . . . . . . . . . . . . . . . 37
4 實驗結果: 市場表徵與特性39
4.1 市場總體面分析. . . . . . . . . . . . . . . . . . . . 39
4.1.1 價格收斂. . . . . . . . . . . . . . . . . . . . . . 39
4.1.2 市場交易量. . . . . . . . . . . . . . . . . . . . . 53
4.1.3 財富分配. . . . . . . . . . . . . . . . . . . . . . 64
4.2 市場個體面分析. . . . . . . . . . . . . . . . . . . . 83
4.2.1 參與者與財富表現. . . . . . . . . . . . . . . . . . 84
4.2.2 參與者與成交數目. . . . . . . . . . . . . . . . . . 94
4.3 本章結論. . . . . . . . . . . . . . . . . . . . . . . 97
5 實驗結果: 參與者策略對市場的影響與演進. . . . . . . . . 100
5.1 參與者策略與利潤. . . . . . . . . . . . . . . . . . . 100
5.2 參與者策略的學習. . . . . . . . . . . . . . . . . . . 107
5.3 學習行為與市場現象. . . . . . . . . . . . . . . . . . 119
5.3.1 模型估計結果與解釋力. . . . . . . . . . . . . . . . 120
5.3.2 市場結構差異與參數. . . . . . . . . . . . . . . . . 122
5.3.3 參與者類別與參數. . . . . . . . . . . . . . . . . . 131
5.3.4 參與者財富表現與參數. . . . . . . . . . . . . . . . 138
5.4 本章結論. . . . . . . . . . . . . . . . . . . . . . . 148
6 結論與未來發展. . . . . . . . . . . . . . . . . . . . . 151
6.1 實驗結果總整理. . . . . . . . . . . . . . . . . . . . 151
6.2 未來研究展望. . . . . . . . . . . . . . . . . . . . . 153
Appendices. . . . . . . . . . . . . . . . . . . . . . . . 155
A 實驗說明. . . . . . . . . . . . . . . . . . . . . . . . 156
B 真實價值資訊的產生. . . . . . . . . . . . . . . . . . . 167
C 實驗參與者的分析. . . . . . . . . . . . . . . . . . . . 169
D 參與者參數估計值. . . . . . . . . . . . . . . . . . . . 172
E 參數分佈圖. . . . . . . . . . . . . . . . . . . . . . . 190		zh_TW
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dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0932580121en_US
dc.subject (關鍵詞) 資訊不對稱zh_TW
dc.subject (關鍵詞) 資訊散佈zh_TW
dc.subject (關鍵詞) 雙方喊價市場zh_TW
dc.subject (關鍵詞) 實驗經濟學zh_TW
dc.subject (關鍵詞) 強化學習模型zh_TW
dc.title (題名) 財務市場資訊不對稱下之市場現象與參與者行為之研究zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 中文部分:zh_TW
dc.relation.reference (參考文獻) 謝宗林(1988)。股票市場與內線交易。經濟前瞻第九號。zh_TW
dc.relation.reference (參考文獻) 唐恕(民87)。異質訊息下內線交易與交易策略與市場績效之研究。輔仁大學金融研究所碩士論文。zh_TW
dc.relation.reference (參考文獻) 詹場．胡星陽(2001.7)。流動性衡量方法之綜合評論。國家科學委員會研究彙刊。11卷3期。205-221。zh_TW
dc.relation.reference (參考文獻) 張萬同(2003)。衍生性金融市場之管理、運作、及效率。桂冠圖書。zh_TW
dc.relation.reference (參考文獻) 周星．林清勝(2004)。實驗經濟學最新發展動動態述評。學術月刊zh_TW
dc.relation.reference (參考文獻) 楊曉嵐．金雪軍(2005)。基於實驗經濟學方法的證卷市場信息有效性研究。浙江大學學報,Vol.35,No6,p80–88。zh_TW
dc.relation.reference (參考文獻) 李家瑋(民94)。比較遺傳演算法語強化學習: 以代理人彩券市場為例。國立政治大學經濟學系碩士論文。zh_TW
dc.relation.reference (參考文獻) Bibliographyzh_TW
dc.relation.reference (參考文獻) Anand, A. and Martell, T. (2001). ”informed” limit order trading. working paper.zh_TW
dc.relation.reference (參考文獻) Ang, J. and Schwarz, T. (1985). Risk aversion and information structure:An experimental study of price variability in securities markets.The Journal of Finance, 40:825–844.zh_TW
dc.relation.reference (參考文獻) Banks, J. (1985). Price-conveyed information versus observed insider behavior: A note on rational expectations convergence. The Journal of Political Economy, 94(4):807–81.zh_TW
dc.relation.reference (參考文獻) Chan, N., LeBaron, B, L. A., and Poggio, T. (1998). Information dissemination and aggregation in asset markets with simple intelligent traders. working paper.zh_TW
dc.relation.reference (參考文獻) Chmura, T. and Piz, T. (2007). An extended reinforcement algorithm for estimation of human behaviour in experimental congestion games. Journal of Artificial Societies and Social Simulation,10(2).zh_TW
dc.relation.reference (參考文獻) Cliff, D. (2001). Evolution of market mechanism through a continuous space of auction-types. Techreport HPL-2001-326, Information Infrastructure Laboratory HP Laboratories Bristol.zh_TW
dc.relation.reference (參考文獻) Duffy, J. and Unver, M. (2006). Asset price bubble and crashes with near-zero-intelligence traders. Economic theory, 27:537–563.zh_TW
dc.relation.reference (參考文獻) Erev, I. and Roth, A. E. (1998). Prediciting how people play games: Reinforcement learning in experimental games with unique, mixed strategy euqilibri. The American Economic Review, 88(4):848–881.zh_TW
dc.relation.reference (參考文獻) Fama, E. (1970). Efficient capital markets: a review of theory an empirical work. The Journal of Finance, 25(2):383–417.zh_TW
dc.relation.reference (參考文獻) Feltovich, N. (2000). Reinforcement-based vs. belief-based learning models in experimental asymmetric-information games. Econometrica, 68(3):605–641.zh_TW
dc.relation.reference (參考文獻) Figlewski, S. (1978). ”market efficiency” in a market with heterogeneouszh_TW
dc.relation.reference (參考文獻) information. The Journal of Political Economy, 86(4):581–zh_TW
dc.relation.reference (參考文獻) 579.zh_TW
dc.relation.reference (參考文獻) Flood, M., Koedijk, K., van Dijk, M., and van Leeuwen, I. (2002). Dividing the pie: Asymmetrically informed dealers and market transparency.working paper.zh_TW
dc.relation.reference (參考文獻) Forsythe, R. and Lundholm, R. (1990). Information aggregation in an experimental market. Econometrica, 58(2):309–347.zh_TW
dc.relation.reference (參考文獻) Foster, F. and Viswanathan (1994). Strategic trading with asymmetrically informed traders and long-lived information. The Journal of Financial and Quantitative Analysis, 29(24):499–518.zh_TW
dc.relation.reference (參考文獻) Friedman, D. and Sunder, S. (1994). Experimental methods: A primer for economists. Cambridge university press.zh_TW
dc.relation.reference (參考文獻) Gil-Bazo, J.and Moreno, D. and Tapia, M. (2005). Price dynamics, informational efficiency and wealth distribution in continuous double auction markets. working paper.zh_TW
dc.relation.reference (參考文獻) Glosten, L. and Milgrom, P. (1985). Bid, ask and transaction prices in a specialist market with heterogeneously informed traders. Journal of Financial Economics, 114:71–100.zh_TW
dc.relation.reference (參考文獻) Gode, D. K. and Sunder, S. (1993). Allocative efficiency of markets with zero-intelligence traders: Market as a partial substutute for individual rationality. The Journal of Political Economy, 101(1):119-137.zh_TW
dc.relation.reference (參考文獻) Gresik, T. A. and Satterthwaite, M. A. (1985). The rate at which a simple market becomes efficient as the number of traders increases:An asymptotic result for optimal trading mechanisms. Discussion Paper.zh_TW
dc.relation.reference (參考文獻) Grossklags, J. and Schmidt, C. (2006). Software agents and market (in) efficiency: a human trader experiment. In Forthcoming in IEEE Trans SMC Part C., Special Issue on Game-theoretic Analysis & Simulation of Negotiation Agents.zh_TW
dc.relation.reference (參考文獻) Kyle, A. (1985). Continuous auctions and insider trading. Econometrica, 53(6):1315–1336.zh_TW
dc.relation.reference (參考文獻) LeRoy, S. F. and LaCivita, C. (1981). Risk aversion and the dispersion of asset price. The Journal of Business, 54(4):535–547.zh_TW
dc.relation.reference (參考文獻) Matsui, H., Koyama, Y., and Ishiyama, K. (2005). A report of large scale gaming simulation using a u-mart system in economic education.In Proceedings of the Third International Conference on Creating, Connecting and Collaborating through Computing.zh_TW
dc.relation.reference (參考文獻) Nakajim, Y., Ono, I., Sato, H., Mori, N., Kita, H., Matsui, H., Taniguchi, K., Deguchi, H., Terano, T., and Shiozawa, Y. (2004). Introducing virtual futures market systemu-mart. In EES 2004 :Experiments in Economic Sciences - New Approaches to Solving Real-world Problems.zh_TW
dc.relation.reference (參考文獻) O’Brien, J. and Srivastava, S. (1991). Dynamic stock markets with multiple assets: an experiment analysis. The Journal of Finance, 46(5):1111–1138.zh_TW
dc.relation.reference (參考文獻) Plott, C. and Sunder (1988). Rational expectation and the aggregation of diverse information in laboratory security markets. Econometrica, 56(5):1085–1118.zh_TW
dc.relation.reference (參考文獻) Plott, C. and Sunder, S. (1982). Efficiency of experimental security markets with insider information: an application of rational expectation models. The Journal of Political Economy, 90(40):663–698.zh_TW
dc.relation.reference (參考文獻) Roth, A. E. and Erev, I. (1995). Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term. Games and Economic Behavior, 8:164–212.zh_TW
dc.relation.reference (參考文獻) Sarin, R. and Vahid, F. (2001). Predicting how people play games: A simple dynamic model of choice. Games and Economic Behavior,34:104–122.zh_TW
dc.relation.reference (參考文獻) Sato, H., Matsui, H., Ono, I., Kita, H., Terano, T., Deguchi, H., and Shiozawa, Y. (2001). U-mart project: learning economic principles from the bottom by both human and software agents. In JSAI2001 workshop, pages 121–131.zh_TW
dc.relation.reference (參考文獻) Sunder, S. (1995). Experimental asset markets: A survey 　, The handbook of experimental economics. Princeton university press.zh_TW
dc.relation.reference (參考文獻) Theissen, E. (2000). Market structure, informational efficiency and liquidity: An experimental comparison of auction and dealer markets. Journal of financial markets, 3:333–363.zh_TW
dc.relation.reference (參考文獻) Victoire, T. and Suganthan, P. N. (2007). Differential evolution and evolutionary programming for solving non-convex economic dispatch problems. Technical report, Agency for Science, Technology and Reasearch. Agency for Science, Technology and Reasearch.zh_TW
dc.relation.reference (參考文獻) Wang, S., Tseng, J., Tai, C., Lai, K., Chen, S., and Li, S. (2008). Network topology of an experimental futures exchange. European Physical Journal B, 26:105–111.zh_TW