自 2007 年次貸風暴後，不動產價格產生劇烈的波動，過往不動產價格之預測模型大多係以傳統財務模型為基礎，市場假設基礎係依據效率市場假說，假設市場參與者為理性且追求利潤極大化，然而自 1980 年代後，部分學者提出對傳統經濟模型的反思，即所謂著重於探討市場參與者之決策行為之行為財務學，其中異質代理模型係一種可使行為財務理論具體化的一種方法，異質代理透過假設市場參與者有不同投資策略進行分析，其中分為逐市者(Chartist)與基本面分析者(Fundamentalist)。
本文將透過行為財務理論，假設不動產市場存有不同之異質參與者，並將需求者分為逐市者與基礎分析者，透過異質代理模型進行假設運算，使用台北市各區實際租金資料作為市場基本價值之計算依據，市場價格採用國泰房價指數作為計算基準，研究結果發現台灣之不動場市場中，逐市者對價格之影響程度遠大於一般投資者，且台灣不動產市場價值偏離基礎價值情況嚴重，有泡沫化之隱憂，經觀察實證結果，發現原本因對價格產生負面影響之基本面分析者於台灣市場中，對於價格之影響為正，因此本研究認為有以下推論，總體經濟因素推升市場，導致基本面分析者對於期望未來租金成長，因此對不動產之價格產生正向影響。

Since Subprime mortgage crisis in 2007, the price of real estate has chan ged extremely. The forecast models of real estate price in the past were mostly based on traditional financial models, and market assumption is according to Efficient-market hypothesis, which assumes that participants are rational and pursuit the maximum profit in the market. However, after 1980s some scholars had reflections on traditional financial models. As known as Behavioral Finance that focuses on the decision-making of market participants and heterogeneous agent-based model is one of methods to make Behavioral Finance concrete. Heterogeneous agent analyzes market participants on the hypothesis that they have different invest strategies and they can be classified into Chartist and Fundamentalist.
This study based on Behavioral Finance and heterogeneous agent-based model, assuming that there are different heterogeneous participants in real estate market, classifying the demand into Chartist and Fundamentalist. We used actual rent data of each district in Taipei to calculate the underlying value and Cathay housing index to calculate the market price. We found that the effect on real estate price of Chartist is far more than that of Fundamentalist in real estate market in Taiwan. Furthermore, the situation of market price deviating from underlying value is very serious and there is a potential problem of burst. The empirical results show that Fundamentalist which originally has negative effect on market price turns out to have positive effect on market price. Accordingly, this study proposed the inference that macroeconomic factors push the market price, making Fundamentalist expects the rent would grow in the future so as to have positive effect on market price.

1. 高瑩芳,2008, 「財務市場顯著異質性: 簡單代理人基財務模型之實證研究」,中央大學經濟學系碩士論文
2. 李紅權，2009，「異質投資者、噪音與金融市場波動的仿真研究」，『计算机工程与应用』，第 15 期，30-32
3. 池秉聰、陳樹衡,2007，「經濟學中的創新-代理人基計算建模」，政治大學經濟學系博士論文
4. 王永钦、包特( 2011) : 《异质交易者、房地产泡沫与房地产政策》,《世界经济》第 11 期。
5. 陳佳甫， 張金鶚， 謝博明，2012，「知人知面不知心-購屋者房價預期之分析」，『都市與計畫』，第 39 卷第 4 期，pp.349-373
6. 陳明吉、Patel, L. ，2002，「An empirical analysis of determination of housing prices in the Taipei area」，『經濟論文叢刊』，第 30 卷第 4期，pp.563-595。
7. 陳明吉、曾婉婷，2008，「台灣不動產市場從眾行為之檢視」，『管理與系統 (TSSCI) 』，第 15 卷第 4 期，591-615。
8. 林左裕、程于芳，2014 ，「影響不動產市場之從眾行為與總體經濟因素之研究」，『應用經濟論叢』，第 95 期，pp.61-99。
9. 林左裕、傅聖元，2015 ，「住宅市場處置效應之研究」，『都市與計畫』，第 42卷第 3 期，pp.273-294。
10. 林祖嘉、林素菁，1995 ，「台灣地區住宅價格的泡沫現象」，台灣經濟學會論文集。
11. 張金鶚、陳明吉、鄧筱蓉與楊智元，2009 ，「台北市房價泡沫知多少？—房價 vs.租金、房價 vs.所得」，『住宅學報』，第 18 卷第 2 期，pp.1-22。

1. Axelrod, R., and Tesfatsion, L., 2006, “A guide for newcomers to agent-based modeling in the social sciences.,” pp.1647-1659 in Handbook of Computational Economics: Agent-Based Computational Economics edited by Tesfatsion and Judd, K. L.
2. Barberis, N., Shleifer, A., and Vishny, R., 1998, “A Model of Investor Sentiment.,” Journal of Financial Economics Volume 49, 307-345.
3. Black, A., P. Fraser, and Hoesli M. “House Prices, Fundamentals and Bubbles.,” Journal of Business Finance and Accounting, Volume 33:9/10, 1535–1555.
4. Black, F.,1986, "Noise.," Finance , Volume 41, 529-43.
5. Bolt, W., Demertzis, M., Diks, C., Hommes, C., Van der Leij, M., 2013, “Bubbles and Crashes in House Prices under Heterogeneous Expectations.,” Amsterdam: Universiteit van Amsterdam working papers.
6. Brock, W. and Hommes, C.H., 1997, “A Rational Route to Randomness.,” Econometrica 65(5), 1059-1095.
7. , 1998, “Heterogeneous Beliefs and Routes to Chaos in a Simple Asset Pricing Model.,” Journal of Economic Dynamics and Control 22(8-9), 1235-1274.
8. Case, K.E. and Shiller, R. J., 1989, “The Efficiency of the Market for Single Family Homes”, American Economic Review, Volume 79(1): 125–37.
9. Cho, M., 1996, “House Price Dynamics: A Survey of Theoretical and Empirical Issues”, Journal of Housing Research, Volume 7, 145-172.
10. Cutler, D.M., Poterba, J.M., and Summers, L.H., 1990, “Speculative Dynamics and the Role of Feedback Traders.,” American Economic Review, Volume 80(2): 63-68.
11. Daniel, K., Hirshleifer, D., and Subrahmanyam, A., 1998, “Investor Psychology and Security Market Under and Overreactions,” Journal of Finance, Volume 53, 1839-1885.
12. De Grauwe, P. and Grimaldi, M., 2006, “Exchange Rate Puzzles: A Tale of Switching Attractors.,” European Economic Review, Volume 50, 1–33.
13. De Long, J. B., Shleifer, A., Summers, L., and Waldmann, R., 1990, “Noise Trader Risk in Financial Markets.,” Journal of Political Economy,Volume 98, 703-738.
14. Dieci, R., and Westerhoff, F., 2012, “A Simple Model of A Speculative Housing Market.,” Journal of Evolutionary Economics, Volume 22(2), 303-329.
15. Fama, E. F., 1970, “Efficient Capital Market: A Review of Theory and Empirical Work,” Journal of Finance, Volume 25, 383-417
16. Fama, E. F. and Kenneth, R., 2000, “The Equity Premium.,” CRSP Working Paper No. 522, University of Chicago.
17. Frankel, J.A. and Froot, K.A., 1991, “Chartists, Fundamentalists, and the Demand for Dollars.,” Private Behaviour and Government Policy in Interdependent Economies edited by A. Courakis and M. Taylor, Oxford: Clarendon.
18. Gallin, J., 2008, “The Long-Run Relationship Between House Prices and Rents. Real Estate Economics.,” Real Estate Economics, Volume 36 (4), 635–658.
19. Haugen, R., 1994, The New Finance: The Case Against Efficient Markets, Englewood Cliffs, NJ: Prentic-Hall, Inc.
20. Himmelberg, C., Mayer, C., and Sinai, T., 2005, “Assessing High House Prices: Bubbles, Fundamentals and Misperceptions.,” NBER Working Paper No. 11643.
21. Hott, C., and Monnin, P., 2008. “Fundamental Real Estate Prices: An Empirical Estimation with International Data.,” The Journal of Real Estate Finance and Economics, Volume 36(4), 427-450.
22. Judd, K. L., 2006, “Computationally Intensive Analyses in Economics”, pp.881-893, in Handbook of Computational Economics: Agent-Based Computational Economics edited by Tesfatsion, L.and Judd, K. L.
23. Kanhnman, D. and Tversky, A., 1979, “Prospect Theory: An Analysis of Decision under Risk,” Econometrica, Volume 47,263-291.
24. Kouwenberg, R. and Zwinkels, R., 2011, “Chasing trends in the US housing market.,” Working Paper, Erasmus University Rotterdam.
25. Kyle, A. S., "Continuous Auctions and Insider Trading.," Econometrica, Volume 53, 1315-1335.
26. Leamer, E., 2002, “Bubble Trouble? Your Home Has a P/E Ratio Too”, UCLA Anderson Forecast.
27. Malpezzi, S. and Wachter, S.M., 2005, “The Role of Speculation in Real Estate Cycles.,” Journal of Real Estate Literature, Volume 13(2), 143-164.
28. Mayer, C. J., and Sinai, T., 2007, “Housing and Behavioral Finance.,” the Federal Reserve Bank of Boston Conference, Boston, September 25.
29. Poterba, J. M., and Summers, L. H. “Mean Reversion in Stock Prices: Evidence and Implications.,” Journal of Financial Econmics, Volume 22, 27-59.
30. Shiller, R.J., 1984, “Stock Price and Social Dynamics.,” Economic Activity, Volume(2), 457-498
31. , 2005, “Behavioral Economics and Institutional Innovation.,” Cowles Foundation Discussion Paper No. 1499, Yale University.
32. , 2008, “Derivatives Markets for Home Prices.,” NBER Working Paper 13962.
33. Shleifer, A., 2000, “Inefficient Market: An Introduction to Behavioral Finance.,” Oxford University, Oxford.
34. Sommervoll, D.E., Borgersen, T.A. and Wennemo, T., 2010, „Endogenous Housing Market Cycles.,” Journal of Banking and Finance.