系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2007年
9期
38~46
,共null页
期望效用 参数不确定性 贝叶斯学习 动态资产组合
期望效用 參數不確定性 貝葉斯學習 動態資產組閤
기망효용 삼수불학정성 패협사학습 동태자산조합
expected utility; parametric uncertainty; Bayesian learning; dynamic portfolio
在不完全信息下,研究了风险资产收益前两阶矩的参数不确定性对动态资产组合选择的影响.在连续时间下假设资产的价格服从随机扩散过程,引入参数不确定性,利用随机动态规划方法推导出风险资产最优配置的封闭解,使投资者的终期财富期望幂效用最大;在离散时间下假设风险资产的连续复合月收益率服从独立同分布的正态分布,通过贝叶斯学习准则,以上证综合指数不同区间段的两个样本做实证研究.研究表明,当投资者的风险规避程度大于(小于)对数效用时,参数不确定性将导致负(正)的投资期效应;当投资者在估计过程中运用较多的历史数据、或者风险规避程度增加时,参数不确定性的影响将减弱;收益一阶矩的不确定性影响较其二阶矩强.研究突出了参数不确定性在动态资产组合选择过程中的重要性.
在不完全信息下,研究瞭風險資產收益前兩階矩的參數不確定性對動態資產組閤選擇的影響.在連續時間下假設資產的價格服從隨機擴散過程,引入參數不確定性,利用隨機動態規劃方法推導齣風險資產最優配置的封閉解,使投資者的終期財富期望冪效用最大;在離散時間下假設風險資產的連續複閤月收益率服從獨立同分佈的正態分佈,通過貝葉斯學習準則,以上證綜閤指數不同區間段的兩箇樣本做實證研究.研究錶明,噹投資者的風險規避程度大于(小于)對數效用時,參數不確定性將導緻負(正)的投資期效應;噹投資者在估計過程中運用較多的歷史數據、或者風險規避程度增加時,參數不確定性的影響將減弱;收益一階矩的不確定性影響較其二階矩彊.研究突齣瞭參數不確定性在動態資產組閤選擇過程中的重要性.
재불완전신식하,연구료풍험자산수익전량계구적삼수불학정성대동태자산조합선택적영향.재련속시간하가설자산적개격복종수궤확산과정,인입삼수불학정성,이용수궤동태규화방법추도출풍험자산최우배치적봉폐해,사투자자적종기재부기망멱효용최대;재리산시간하가설풍험자산적련속복합월수익솔복종독립동분포적정태분포,통과패협사학습준칙,이상증종합지수불동구간단적량개양본주실증연구.연구표명,당투자자적풍험규피정도대우(소우)대수효용시,삼수불학정성장도치부(정)적투자기효응;당투자자재고계과정중운용교다적역사수거、혹자풍험규피정도증가시,삼수불학정성적영향장감약;수익일계구적불학정성영향교기이계구강.연구돌출료삼수불학정성재동태자산조합선택과정중적중요성.
This paper studies the effects of parametric uncertainty of the first two moments about risky asset return on the choice of dynamic portfolio under incomplete information. In continuous-time framework, assuming that asset price follows stochastic diffusion process, it introduces parametric uncertainty, and applies stochastic dynamic programming to derive the closed-form solution of optimal portoho choice, which maximizes the expected power utility of investor's terminal wealth; in discrete-time framework, continuous compounding monthly returns of risky asset are assumed to be normal i.i.d., it applies the rule of Bayesian learning to do empirical study about two different sample of Shanghai Exchange Composite Index. Result shows, the uncertainty of parameter leads to negative (positive) investment horizon effects when investor's risk aversion is more (less) than that of logarithmic utility; the effects of parametric uncertainty will weaken when investor uses more past data in his estimation, or when his risk aversion increases; the effect of the first order moment's uncertainty is stronger than that of the second order moment's uncertainty. This study stresses the importance of parametric uncertainty in the context of dynamic portfolio choice.