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題名：	行為財務學觀點下的動態資產配置
作者：	葉宗穎
作者(外文)：	Chung-Ying Yeh
校院名稱：	國立臺灣大學
系所名稱：	財務金融學研究所
指導教授：	鍾經樊
學位類別：	博士
出版日期：	2009
主題關鍵詞：	損失趨避；框架效果；風險反饋；馬可夫轉換；投資人情緒；扭曲的信念；dynamic asset allocation；narrow framing/loss aversion；volatility feedback
原始連結：	連回原系統網址
相關次數：	被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0) 排除自我引用:0 共同引用:0 點閱:26

摘要
第一章提出了一個一般化的隨機動態風險模型(stochastic volatility model)，我們稱為「隨機動態風險反饋模型(stochastic volatility feedback model)」，來研究槓桿效果(leverage effect) 與風險反饋效果(volatility feedback
effect)在實證上與經濟上的重要性。在實證方法上，我們使用Gallant and Tauchen (1996)所提出的Efficient Method of Moment(EMM)來估計。在評價實證上的重要性，我們是比較哪種效果是決定重製風險與報酬cross-correlations 的首要因素。在經濟上的重要性，我們是以動態資產配置的觀點來衡量。主要結果為：風險反饋效果不論在實證上與經濟上的重要性都高於槓桿效果。
第二章我們研究投資人的動態資產配置問題，其中該投資人的偏好包含了損失趨避(loss aversion)與框架效果(narrow framing)。而股票價格的動態是帶有可預期機制的(predictability)，既為上一章所提的風險反饋效果(volatility feedback effect)。從理論上我們發現損失趨避與框架效果對投資人資產配置的影響是不同的，其中損失趨避會減少投資人對股票的需求，然而框架效果可以放大或減少對股票的需求，而這決定於投資的輸贏的賠率與心理主觀賠率的相對大
小。主要結果：當有考慮風險反饋效果的可預期機制時，損失趨避與框架效果並不像Barberis, Huang and Santos (2001), Barberis and Thaler (2003)所言的可以解釋equity premium puzzle/participation puzzle。
第三章我們同樣研究投資人的動態資產配置問題，其中該投資人的信念受到心理情緒因素所影響。我們試圖比較不同型態投資人的投資表現。為了比較的一致性與合理性，我們在不完全訊息架構下擴充Campbell, Chan and Viceira (2003)的動態資產配置模型，使其能包含投資人的信念，進而分析能投資組合與評價投資表現。我們主要發現：樂觀的投資人的投資表現是最高的，其次才是貝氏投資人；樂觀投資人的投資策略是較積極的，以在牛市市場有最大獲利做為投資法
則。

以文找文

Abstract
Chapter 1 proposes a general continuous-time stochastic volatility model, the stochastic volatility feedback (SVF) model, to investigate the empirical and economic importance of the leverage and volatility feedback e ects, both of which are the two main explanations for volatility asymmetry. We empirically estimate our model by the Gallant and Tauchen''s (1996) e cient method of moment (EMM) approach using S&P 500 index returns. To assess the empirical importance of the leverage and volatility feedback e ects, we calculate the simulated cross-correlations between returns and volatility under various speci cations and the make a comparison to its realistic ones. To evaluate the economic importance, we perform the dynamic asset allocation model under various settings for the budget constraint and then compare the economic performances for the corresponding optimal investment strategies. Our ndings are as follows. (1) On comparing the magnitude of the two e ects, the volatility feedback e ect dominates the leverage e ect empirically. The volatility feedback e ect is the key determinant to replicate the sample cross-correlations between returns and volatility. The conventional stochastic volatility models with/without jumps fail to replication; (2) the volatility feedback e ect drives the intertemporal hedging demand, in contrast, the leverage e ect has a minor e ect on it; (3) a longer investment horizon or a higher current volatility enhance the volatility feedback e ect; (4) ignoring the volatility feedback e ect would su er from tremendous economic loss.
In chapter 2, we study the dynamic asset allocation problem in a general framework where the representative investor''s preferences include narrow framing/loss aversion parameters
while the intertemporal budget constraint contains the empirically-validated volatility feedback e ect. The optimal dynamic allocation of wealth among investment,
consumption, and savings can be solved in an analytically tractable way and is found to be profoundly in
uenced by the interactions between narrow framing/loss aversion and the volatility feedback e ect. In other words, a more elaborated speci cation of the intertemporal budget constraint including the volatility feedback e ect is indispensable to a complete analysis of narrow framing/loss aversion preferences in a dynamic asset allocation problem. In particular, we nd that introducing narrow framing/loss aversion without the volatility feedback e ect does help reduce investment and transfer the weights to savings, which implies that narrow framing/loss aversion can explain the equity premium puzzle as previous literature has suggested. However, the direction of weight shifts reverses noticeably once the volatility feedback e ect is incorporated. It seems that the preferences of narrow framing/loss aversion alone may not explain the equity premium puzzle in our general framework where the intertemporal budget constraint is more carefully speci ed.
In chapter 3, the classical nance theory claimed that irrational investors, who misperceive asset returns, would buy high and sell low, causing them to lose their wealth.
The recent researches, such as De Long, Shleifer, Summers and Waldman (1991), and Kogan, Ross, Wang and Wester eld (2006) advocated that irrational investors might form
portfolio allocations performing a higher growth rates that outgrow that of the Bayesian investor in market quilibrium. This paper addresses this issue in terms of investor''s asset
allocation. We conduct the empirical analysis of the investor''s asset allocation decision considering psychological biases. We specify a regime-switching dynamics of the investment opportunity set and use regime predicting and updating procedures to characterize
investor sentiment. Our ndings are as follows. (i) In comparison with the Bayesian investor, the optimistic one would like to bet on good states of the economy, more aggressively chasing /shorting the assets with higher rewards in good/bad times. In contrast, the pessimistic investor would take the opposite positions to the optimistic one; (ii) the optimistic investor has the best empirical performance of the portfolio allocation and
in turn outperforms the Bayesian one. The other irrational investors underperform the Bayesian one in most cases; (iii) while the predictability in the investment opportunity set is removed, the outperformance of the optimistic investor disappears. It suggests that the
bene t from the intertemporal hedging induced by the return predictability is a potential explanation to the domination of the optimistic investor in our analysis.

以文找文

Ait-Sahalia, Y., 1996, Nonparametric Pricing of Interest Rate Derivative Securities," Econometrica, 64, 527-560.
Andersen, T., L. Benzoni and J. Lund, 2002, An Empirical Investigation of Continuous- Time Models for Equity Returns," Journal of Finance, 57, 1239-1284.
Andersen, T., and J. Lund, 1997, Estimating Continuous Time Stochastic Volatility Models of the Short Term Interest Rate," Journal of Econometrics, 77, 343-378.
Barberis, N., and M. Huang, 2001, Mental Accounting, Loss Aversion and Individual Stock Returns," Journal of Finance, 56, 1247-1292.
Barberis, N., and M. Huang, 2007a, Preferences with Frames: A New Utility Speci cation that Allows for the Framing of Risks," Working Paper, Yale University.
Barberis, N., and M. Huang, 2007b, The Loss Aversion / Narrow Framing Approach to Stock Market Pricing and Participation Puzzles," forthcoming in Handbook of
Investments: Equity Risk Premium, R. Mehra ed., North Holland, Amsterdam.
Barberis, N., M. Huang and T. Santos, 2001, Prospect Theory and Asset Prices," Quarterly Journal of Economics, 116, 1-53.
Barberis, N., M. Huang and R. Thaler, 2006, Individual Preferences, Montary Gambles and Equity Premium," American Economic Review, 96, 1069-1090.
Barberis, N., and R. Thaler, 2003, A Survey of Behavior Finance," , in Handbook of the Economics and Finance, George Constantinides, Milton Harris, and Rene Stulz
eds., North-Holland.
Benartzi, S., and R. Thaler, 1995, Myopic Loss Aversion and the Equity Premium Puzzle," Quarterly Journal of Economics, 52, 75-92.
Bekaert, G., and G. Wu, 2000, Asymmetric Volatility and Risk in Equity Market," Review of Financial Studies, 13, 1-42.
Berkelaar, A., R. Kouwenberg, and T. Post, 2004, Optimal Portfolio Choice under Loss Aversion," Review of Economics and Statistics, 84, 973-987.
Brennan, M. J., E. S. Schwartz, and R. Lagnado, 1997, Strategic Asset Allocation," Journal of Economic Dynamics and Control, 21, 1377-1403.
Campbell, J. Y., 1991, A Variance Decomposition for Stock Returns," Economic Journal, 101, 157-179.
Campbell, J. Y., and L. Hentschel, 1992, No News is Good News. An Asymmetric Model of Changing Volatility in Stock Return," Journal of Financial Economics, 31, 281-318.
Campbell, J. Y., and R. Shiller, 1988, The Dividend-Price Ratio and Expectation of Future Dividends and Discount Factors," Review of Financial Studies, 1, 195-227. new window

Chernov, M., and E. Ghysels, 2000, A Study Towards a Uni ed Approach to the Joint Estimation of Objective and Risk Neutral Measures for the Purpose of Options Valuation,"
Journal of Financial Economics, 56, 407-458.
Chernov, M., A. R. Gallant, E. Ghysels and G. Tauchen, 2003, Alternative Models for Stock Price Dynamics," Journal of Econometrics, 116, 225-258.
Chung, K. L., and R. Williams, 1990, An Introduction to Stochastic Integration, 2nd ed. Boston: Birkhauser.
Dai, Q., and J. Singleton, 2001, Speci cation Analysis of A ne Term Structure Models," Journal of Finance, 55, 1943-1978.
Das, S. R., and R. Uppal, 2004, Systemic Risk and International Portfolio Choice," Journal of Finance, 59, 2809-2834.
Duan, J.-C., 1997, Augmented GARCH (p,q) Process and its Di usion Limit," Journal of Econometrics, 79, 97-127.
Du e, D., J. Pan, and K. Singleton, 2000, Transform Analysis and Asset Pricing for A ne Jump Di usion," Econometrica, 68, 1343-1376.
Du e, D., and K. J. Singleton, 1993, Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, 61, 929-952.
Elerian, O., S. Chib and N. Shephard, 2001, Likelihood Inference for Discretely Observed Nonlinear Di usions," Econometrica, 69, 959-994.
Eraker, B., 2001, MCMC Analysis of Di usion Models with Application to Finance," Journal of Business and Economic Statistics, 19, 177-191.
Eraker, B., 2004, Do stock prices and volatility jump? Reconciling evidence from spot and option prices," Journal of Finance, 59, 1367-1403.
Gallant, A. R., and G. Tauchen, 1996, Which Moments to Match?," Econometric Theory, 12, 657-681.
Gallant, A. R., and G. Tauchen, 2002, Simulated Score Methods and Indirect Inference for Continuous-time Models," prepared for the Handbook of Financial Econometrics,
available at http://www.econ.duke.edu/ get/wpapers.
Gomes, F., 2005, Portfolio Choice and Trading Volume with Loss Averse Investors," Journal of Business, 78, 675-706.
Hansen, L. P., and J. A. Scheinkman, 1995, Back to the Future: Generating Moment Implication for Continuous-Time Markov Process," Econometrica, 63, 767-804.
Heston, S. L., 1993, A Closed Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," Review of Financial Studies, 6,
327-389.
Kahneman, D., and D. Lovallo, 1993, Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk Taking," Management Science, 39, 17-31.
Kahneman, D., and A. Tversky, 1979, Prospect Theory: An Analysis of Decision under Risk," Econometirca, 47, 263-291.
Klebaner, F., 1998, Introduction to Stochastic Calculus with Application, Imperial College Press.
Liu, J., 2007, Portfolio Selection in Stochastic Environments," Review of Financial Studies, 20, 1-39.
Liu, J., F. Longsta , and J. Pan, 2003, Dynamic Asset Allocation with Event Risk," Journal of Finance, 58, 231-259.
Maenhout, P., 2004, Robust Portfolio Rules and Asset Pricing," Review of Financial Studies, 17, 951-984.
Mankiw, N., and S. Zeldes, 1991, The Consumption of Stockholders and Non-stockholders," Journal of Financial Economics, 29, 97-112.
Mehra R., and E. C. Prescott, 2003, The Equity Premium in Retrospect," in Handbook of the Economics of Finance, Ed. by G.M. Constantinides, M. Harris and R. Stulz,
Elsevier B.V.
Nelson, D. B., 1990, ARCH Models As Di usion Approximation," Journal of Econometrics, 45, 7-38.
Nelson, D. B., 1992, Filtering and Forecasting with Misspeci cation ARCH Models I: Getting the Right Variance with the Wrong Model," Journal of Econometrics, 52,
61-90.
Nelson, D. B. and D. P. Foster, 1994, Asymptotic Filtering Theory for Univariate ARCH Models," Econometrica, 62, 1-41.
Read, D., G. Loewenstein, and M. Rabin, 1999, Choice Bracketing," Journal of Risk and Uncertainty, 19, 171-197.
Shumway, T., 1997, Explaining Returns with Loss Aversion," Working Paper, University of Michigan.
Thaler, R., 1980, Toward A Positive Theory of Consumer Choice," Journal of Economic Behavior and Organization, 1, 39-60. new window

Thaler, R., A. Tversky, D. Kahneman and A. Schwartz, 1997, The E ect of Myopic and Loss Aversion on Risk-Taking: An Experiment Test," Quarterly Journal of Economics, 112, 643-660.
Tversky, A., and D. Kahneman, 1991, Loss Aversion in Riskless Choice: A Reference-Dependent Model," Quarterly Journal of Economics, 106, 1039-1061.
Tversky, A., and D. Kahneman, 1992, Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, 5, 297-323.
Uppal, R., and T. Wang, 2003, Model Misspeci cation and Under Diversi cation," Journal of Finance, 58, 2465-2486.
Van der Sluis, P. J., 1997, EmmPack 1.01: C/C++ Code for Use with Ox for Estimation of Univariate Stochastic Volatility Models with the E cient Method of Moments," new window

Nonlinear Dynamics and Econometrics, 2, 77-94.
Wu, G., 2001, The Determinants of Asymmetric Volatility," Review of Financial Studies, 14, 837-859
Xia, Y., 2001, Learning About Predictability: The E ects of Parameter Uncertainty on Dynamic Asset Allocation," Journal of Finance, 56, 205-246.

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