Using stochastic approximation for parameter estimation in option pricing

被引：0

作者：

Yin, G. ^{[1
]}

Zhang, Q. ^{[2
]}

Zhuang, C. ^{[2
]}

机构：

[1] Wayne State Univ, Dept Math, Detroit, MI 48202 USA

[2] Univ Georgia, Dept Math, Athens, GA 30602 USA

来源：

2007 AMERICAN CONTROL CONFERENCE, VOLS 1-13 | 2007年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper focuses on option pricing using a stochastic optimization algorithm. The underlying stock price changes according to a set of geometric Brownian motions coupled by a continuous-time finite state Markov chain. A recursive stochastic optimization algorithm is constructed to estimate the implied volatility. Convergence analysis of the algorithm is provided together with rate of convergence. Real market data is used to compare our algorithm with other schemes.

引用

页码：5951 / +

页数：2

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