English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 109948/140897 (78%)
Visitors : 46097140      Online Users : 853
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/35796


    Title: 學習行為與軟體交易策略之比較:個體心智能力對學習行為之影響
    Authors: 戴中擎
    Tai, Chung Ching
    Contributors: 陳樹衡
    Chen, Shu Heng
    戴中擎
    Tai, Chung Ching
    Keywords: 代理人基計算經濟模型
    雙方喊價市場
    交易策略
    學習
    智商
    異質性個體
    Agent-based Computational Economic Models
    Double Auction Markets
    Trading Strategies
    Learning
    IQ
    Heterogeneous Agents
    Date: 2007
    Issue Date: 2009-09-18 16:04:01 (UTC+8)
    Abstract: 因應電子化交易興起而進行的一系列人機互動研究顯示, 縱使人類會透過學習而改善其表現, 電腦化的交易程式獲利能力還是遠勝於真人交易者之表現。本研究遂以遺傳規劃演算法作為學習型交易者之代表, 與一系列電腦化交易策略相競爭, 以探討學習的功效及其限制。

    本研究採用離散型雙方喊價機制, 摒除了計算能力所造成之決策時間差異所會帶來的影響, 亦排除掉人類情緒、預期、相關知識不足等可能因子, 在計算能力對等的情況下, 單純地來評估學習與理性設計策略的結果。並且首次嘗試將影響學習至鉅的智商因子帶入模型之中,

    實驗結果顯示學習具有相當的能力, 即使是在對環境缺乏認識的情況下, 隨著時間的經過其表現最終可凌駕理性設計的策略之上, 然而學習所需的時間是學習型交易者的一大弱點。同時, 本研究也顯示對於以遺傳規劃建構的學習型交易者而言, 其虛擬智商的參數愈高, 學習的效果也愈佳。此研究因此可作為未來在代理人基經濟學模型中, 更深入地探討智商水準不同所造成之行為差異的基礎。
    The study of a series of human-agent interactions as well as computerized trading tournaments in double auction markets has exhibited a general superiority of computerized trading strategies over learning agents. The ineffectiveness
    of learning motivates the study of learning versus designed trading agents in this research. We therefore initiates a series of experiments to test the capability of learning GP agents and rationally-designed trading strategies. The results shows that with the cost of time, eventually learning agents can beat all other trading strategies.

    At the same time, the notion of intelligence is introduced into the model to investigate the influence of individual intelligence on learning ability. We utilize the population size of the GP trader as the proxy variable of IQ which
    is a measure of general intelligence. The results show that individuals with higher intelligence can perform better than those with lower intelligence, which manifests its importance discovered in Psychological research.
    Reference: Anand, P. (1993). Foundations of Rational Choice Under Risk. Oxford: Oxford University Press.
    Brenner, T. (1999). Modelling Learning in Economics. Edward Elgar Publishing.
    Brenner, T. (2006). Agent learning representation: Advice on modelling economic learning. In Tesfatsion, L. and Judd, K., editors, Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics. North Holland.
    Chamberlin, E. H. (1948). An experimental imperfect market. Journal of Political Economy, 56(2):95–108.
    Chan, N., LeBaron, B., Lo, A., and Poggio, T. (1999). Agent-based models of financial markets: A comparison with experimental markets. MIT Artificial Markets Project, Paper No. 124. Available at
    http://people.brandeis.edu/˜blebaron/wps/disagg.pdf.
    Chen, S.-H. and Huang, Y.-C. (forthcoming). Risk preference, forecasting accuracy and survival dynamics: Simulations based on a multi-asset agentbased artificial stock market. Journal of Economic Behavior and Organization. Forthcoming.
    Cliff, D. and Bruten, J. (1997). Zero is not enough: On the lower limit of agent intelligence for continuous double auction markets. Technical Report HPL-97-141, Hewlett-Packard Laboratories. Available at http://citeseer.ist.psu.edu/cliff97zero.html.
    Das, R., Hanson, J. E., Kephart, J. O., and Tesauro, G. (2001). Agenthuman interactions in the continuous double auction. In Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI). San Francisco, CA: Morgan-Kaufmann.
    Duffy, J. (2006). Agent-based models and human subject experiments. In Tesfatsion, L. and Judd, K., editors, Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics. North Holland.
    Easley, D. and Ledyard, J. O. (1993). Theories of price formation and exchange in double oral auction. In Friedman, D. and Rust, J., editors, The Double Auction Market-Institutions, Theories, and Evidence. Addison-Wesley.
    Evans, J. S. B. (2003). In two minds: Dual-process accounts of reasoning. Trends in Cognitive Sciences, 7(10):454–459.
    Feigenbaum, E. A. and Simon, H. A. (1984). EPAM-like models of recognition and learning. Cognitive Science, 8:305–336.
    Fink, D. (1997). A compendium of conjugate priors. Technical report, Environmental Statistics Group, Department of Biology, Montana State University, USA.
    Fonseca, G. L. (n.d.). Vilfredo Pareto. Retrieved May 6, 2008, from http://cepa.newschool.edu/het/.
    Forsythe, R., Rietz, T. A., and Ross, T. W. (1999). Wishes, expectations and actions: A survey on price formation in election stock markets. Journal of Economic Behavior Organization, 39(1):83–110.
    Friedman, D. (1991). A simple testable model of double auction markets. Journal of Economic Behavior and Organization, 15:47–70.
    Gigerenzer, G. and Selten, R., editors (2001). Bounded Rationality: The Adaptive Toolbox. The MIT Press.
    Gjerstad, S. and Dickhaut, J. (1998). Price formation in double auctions. Games and Economic Behavior, 22:1–29.
    Gode, D. K. and Sunder, S. (1993). Allocative efficiency of markets with zero-intelligence traders: Market as a partial substitute for individual rationality. Journal of Political Economy, 101(1):119–137.
    Gottfredson, L. S. (1997). Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography. Intelligence, 24(1):13–23.
    Grosjean, P., Spirlet, C., and Jangoux, M. (2003). A functional growth model with intraspecific competition applied to a sea urchin. Canadian Journal of Fisheries and Aquatic Sciences, 60:237–246.
    Grossklags, J. and Schmidt, C. (2006). Software agents and market (in)efficiency - a human trader experiment. IEEE Transactions on System, Man, and Cybernetics: Part C, Special Issue on Game-theoretic Analysis & Simulation of Negotiation Agents, 36(1):56–67.
    Herrnstein, R. J. and Murray, C. (1994). The Bell Curve: Intelligence and Class Structure in American Life. New York: Free Press.
    Jones, G. and Schneider, W. J. (2006). Intelligence, human capital, and economic growth: A bayesian averaging of classical estimates (BACE) approach. Journal of Economic Growth, 11:71–93.
    Lynn, R. and Vanhanen, T. (2002). IQ and the Wealth of Nations. Westport, CT: Praeger.
    Lynn, R. and Vanhanen, T. (2006). IQ and Global Inequality. Washington Summit Publishers.
    Mandelbrot, B. and Hudson, R. L. (2004). The (Mis)behavior of Markets. Basic Books.
    Murray, C. (1998). Income Inequality and IQ. Washington: AEI Press. Available at http://www.aei.org/books/filter.all,bookID.443/book detail.asp.
    Murray, C. (2002). IQ and income inequality in a sample of sibling pairs from advantaged family backgrounds. American Economic Review, 92(2):339–343.
    Payne, J. W., Bettman, J. R., and Johnson, E. J. (1993). The Adaptive Decision Maker. Cambridge University Press.
    R Development Core Team (2008). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.
    Ram, R. (2007). IQ and economic growth: Further augmentation of Mankiw-Romer-Weil model. Economic Letters, 94:7–11.
    Rubinstein, A. (1986). Finite automata play the repeated prisoner`s dilemma. Journal of Economic Theory, 39(1):83–96.
    Rust, J., Miller, J., and Palmer, R. (1994). Characterizing effective trading strategies: Insights from a computerized double auction tournament. Journal of Economic Dynamics and Control, 18:61–96.
    Rydval, O. and Ortmann, A. (2004). How financial incentives and cognitive abilities affect task performance in laboratory settings: An illustration. Economic Letters, 85:315–320.
    Smith, V. L. (1991). Experimental economics: Behavioral lessons for microeconomic theory and policy. 1990 Nancy Schwartz Lecture, KGSM, Northwestern University.
    Taniguchi, K., Nakajima, Y., and Hashimoto, F. (2004). A report of U-Mart experiments by human agents. In Shiratori, R., Arai, K., and Kato, F., editors, Gaming, Simulations, and Society: Research Scope and Perspective, pages 49–57. Springer.
    Thaler, R. H. (2000). From homo economicus to homo sapiens. Journal of Economic Perspectives, 14(1):133–141.
    Wolpert, D. and Macready, W. (1995a). No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1(1):67–82.
    Wolpert, D. and Macready, W. (1995b). No free lunch theorems for search. Technical Report 95-02-010, Santa Fe Institute.
    Zhan, W. and Friedman, D. (2007). Markups in double auction markets. Journal of Economic Dynamics and Control, 31:2984–3005.
    Description: 博士
    國立政治大學
    經濟研究所
    90258503
    96
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0902585032
    Data Type: thesis
    Appears in Collections:[經濟學系] 學位論文

    Files in This Item:

    File Description SizeFormat
    58503201.pdf145KbAdobe PDF2945View/Open
    58503202.pdf715KbAdobe PDF2947View/Open
    58503203.pdf725KbAdobe PDF2816View/Open
    58503204.pdf832KbAdobe PDF2895View/Open
    58503205.pdf890KbAdobe PDF21337View/Open
    58503206.pdf1099KbAdobe PDF21161View/Open
    58503207.pdf1300KbAdobe PDF22116View/Open
    58503208.pdf1320KbAdobe PDF21583View/Open
    58503209.pdf1532KbAdobe PDF22176View/Open
    58503210.pdf1368KbAdobe PDF21788View/Open
    58503211.pdf945KbAdobe PDF21027View/Open
    58503212.pdf93KbAdobe PDF21080View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback