Estimating Distribution Sensitivity Using Generalized Likelihood Ratio Method

被引：0
作者：
Peng, Yijie [1 ]
Fu, Michael C. [2 ]
Hu, Jian-Qiang [1 ]
机构：
[1] Fudan Univ, Sch Management, Shanghai 200433, Peoples R China
[2] Univ Maryland, Robert H Smith Sch Business, College Pk, MD 20740 USA
来源：
2016 13TH INTERNATIONAL WORKSHOP ON DISCRETE EVENT SYSTEMS (WODES) | 2016年
关键词：
simulation; stochastic derivative estimation; distribution sensitivity; perturbation analysis; likelihood ratio method; ESTIMATING QUANTILE SENSITIVITIES; GRADIENT ESTIMATION; PERTURBATION ANALYSIS; DERIVATIVES; SIMULATION; SYSTEMS;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
We propose a generalized likelihood ratio estimator for the distribution sensitivity in a general framework. Applications on quantile sensitivity, sensitivity of distortion risk measure, and gradient-based maximum likelihood estimation are put together under a single umbrella, and addressed uniformly by the proposed estimator. Numerical experiments substantiate the efficiency of the new method.
引用
收藏
页码：123 / 128
页数：6
相关论文
共 35 条
[1]  
[Anonymous], 2004, Monte Carlo Methods in Financial Engineering
[2]   Monte Carlo methods for security pricing [J].
Boyle, P ;
Broadie, M ;
Glasserman, P .
JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 1997, 21 (8-9) :1267-1321
[3]   Estimating security price derivatives using simulation [J].
Broadie, M ;
Glasserman, P .
MANAGEMENT SCIENCE, 1996, 42 (02) :269-285
[4]  
Cao X. -R., 2014, MATH FINANCE
[5]  
Cao Xi- Ren, 2007, STOCHASTIC LEARNING
[6]  
CAO XR, 1994, REALIZATION PROBABIL
[7]  
Cassandras C. G., 2008, INTRO DISCRETE EVENT
[8]  
Cassandras Christos., 1993, Discrete Event Systems: Modeling and Performance Analysis
[9]   Malhavin Greeks without Malliavin calculus [J].
Chen, Nan ;
Glasserman, Paul .
STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 2007, 117 (11) :1689-1723
[10]  
Fourni E., 1999, Finance Stoch, V3, P391, DOI [DOI 10.1007/S007800050068, 10.1007/s007800050068]
1234