Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/86166


Title: 人工股票市場的Agent-Based計算建模
On Agent-Based Computational Modeling of Artificial Stock Markets
Authors: 廖崇智
Liao, Chung-Chih
Contributors: 陳樹衡
Chen, Shu-Heng
廖崇智
Liao, Chung-Chih
Keywords: 人工股票市場
agent-based計算經濟學
複雜適應系統
遺傳規劃
演化經濟學
突現性質
社會模擬
人工經濟生命
artificial stock market
agent-based computational economics
complex adaptive system
genetic programming
evolutionary economics
emergent property
social simulation
artificial economic life
Date: 1999
Issue Date: 2016-04-26 10:25:15 (UTC+8)
Abstract: 我們把經濟體視為一個複雜適應系統(complex adaptive system), 強調系統中異質性(heterogeneous)agent的學習適應行為與agent之間的互動性交互作用, 此時主流經濟學裡的分析架構, 如:代表性個人模型(represesentive agent model)、理性預期(rational expectation)、固定點均衡分析(fixed-point equilibrium analysis)等將不再適用, 取而代之的是演化經濟學(evolutionary economics)的研究典範, 這樣的研究架構下, 並沒有適當的數學分析工具可資運用, 因此我們改以agent-based建模(agent-based modelng)的社會模擬(social simulation)來建構一個人工的經濟體(artificial economy), 以此為主要研究方法, 這就是agent-based計算經濟學(agent-based computational economics)或稱人工經濟生命(artificial economic life)。
本文中以股票市場為主要的研究課題, 我們以遺傳規劃(genetic programming)的人工智慧(artificial intelligence)方法來模擬股市中有限理性(bounded rational)異質交易者的交易策略學習行為, 建構出一個人工股票市場(artificial stock market), 在這樣的架構下, 我們成功地產生出類似真實股票市場的股價時間序列特性, 我們同時也檢定了人工股票市場中價量的因果關係, 說明了在沒有外生因素之下, 人工股票市場的複雜系統可自發地產生出雙向的價量因果關係, 進一步地, 我們研究下層agent(交易者)行為與上層股價時間序列行為的關聯性, 我們也發現個體的行為並不能直接加總或推論出複雜適應系統的總體行為, 這就是突現性質(emergent property)的發生, 最後, 本文描述了agent-based計算經濟學研究架構的優勢與缺點, 再附帶介紹一個用以進行agent-based建模相關研究的軟體程式庫-SWARM。
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高慈謙(1997), "股票價量因果關係的新檢定方法及其應用", 碩士論文, 國立台灣大學經濟學系, 台北.
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Description: 碩士
國立政治大學
經濟學系
86258001
Source URI: http://thesis.lib.nccu.edu.tw/record/#B2002001635
Data Type: thesis
Appears in Collections:[經濟學系] 學位論文

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