Pricing geometric averaging asian call option under stochastic volatility model

被引:0
|
作者
Li P. [1 ]
Yang J. [1 ]
机构
[1] School of Business Administration, South China University of Technology, Guangzhou
来源
Yang, Jianhui | 1600年 / American Scientific Publishers卷 / 13期
关键词
Geometric Average Asian Call; Path-Dependent Options; Singular Perturbation; Stochastic Volatility Model;
D O I
10.1166/jctn.2016.4846
中图分类号
学科分类号
摘要
Options give the holder the right to buy or sell the underlying asset without obligation. Under the assumptions that asset price is a geometric Brownian process and the price volatility is constant, BS model is an ideal pricing model for European options. Despite the success and popularity of BS model, studies in empirical finance reveal that the implied volatility obtained from financial market data is not a constant but shows the implied volatility "smile" phenomena, thus the assumption of constant volatility is unrealistic. More general non constant volatility models are needed to fix this problem. In particular, lots of attention has been paid to stochastic volatility models in which the volatility is randomly fluctuating driven by an additional Brownian motion. One of these approaches is dropping the assumption of constant volatility and assumes that the underlying asset is driven by a stochastic volatility. By assuming that volatility follows a stochastic process, studies show that stochastic volatility model can better explain the volatility "smile". This paper assumes that asset volatility follows a mean-reverting stochastic process, and studies the pricing problem of geometric average Asian call option which belongs to path-dependent options. By singular perturbation analysis, the corresponding partial differential equation of the stochastic volatility model is obtained, and analytical approximation formula for the geometric average Asian call option is derived. © 2016 American Scientific Publishers All rights reserved.
引用
收藏
页码:593 / 599
页数:6
相关论文
共 42 条
  • [1] Pricing arithmetic Asian option under a two-factor stochastic volatility model with jumps
    Mehrdoust, Farshid
    Saber, Naghmeh
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2015, 85 (18) : 3811 - 3819
  • [2] An efficient algorithm to solve the geometric Asian power option price PDE under the stochastic volatility model
    Alsenafi, Abdulaziz
    Alazemi, Fares
    Alavi, Javad
    NUMERICAL ALGORITHMS, 2025, 98 (01) : 287 - 306
  • [3] PRICING OF QUANTO OPTION UNDER THE HULL AND WHITE STOCHASTIC VOLATILITY MODEL
    Park, Jiho
    Lee, Youngrok
    Lee, Jaesung
    COMMUNICATIONS OF THE KOREAN MATHEMATICAL SOCIETY, 2013, 28 (03): : 615 - 633
  • [4] A remark on a singular perturbation method for option pricing under a stochastic volatility model
    Yamamoto K.
    Takahashi A.
    Asia-Pacific Financial Markets, 2009, 16 (4) : 333 - 345
  • [5] Numerical solution for option pricing with stochastic volatility model
    Mariani, Andi
    Nugrahani, Endar H.
    Lesmana, Donny C.
    WORKSHOP AND INTERNATIONAL SEMINAR ON SCIENCE OF COMPLEX NATURAL SYSTEMS, 2016, 31
  • [6] Pricing multi-asset American option under Heston stochastic volatility model
    Samimi, Oldouz
    Mehrdoust, Farshid
    INTERNATIONAL JOURNAL OF FINANCIAL ENGINEERING, 2018, 5 (03)
  • [7] OPTION PRICING USING STOCHASTIC VOLATILITY MODEL UNDER FOURIER TRANSFORM OF NONLINEAR DIFFERENTIAL EQUATION
    Liu, Zhichao
    Wang, Yunchen
    Cheng, Ya
    Saeed, Tareq
    Ye, Yong
    FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY, 2022, 30 (02)
  • [8] Stochastic volatility models with application in option pricing
    Gong H.
    Thavaneswaran A.
    Singh J.
    Journal of Statistical Theory and Practice, 2010, 4 (4) : 541 - 557
  • [9] PRICING AMERICAN LOOKBACK OPTIONS UNDER A STOCHASTIC VOLATILITY MODEL
    Kim, Dunonghyun
    Woo, Junhui
    Yoon, Ji-Hun
    BULLETIN OF THE KOREAN MATHEMATICAL SOCIETY, 2023, 60 (02) : 361 - 388
  • [10] Stock option pricing and executive stock option incentive compensation: An empirical investigation under general error distribution stochastic volatility model
    Pan Min
    Tang Sheng-qiao
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON RISK MANAGEMENT & GLOBAL E-BUSINESS, VOLS I AND II, 2009, : 107 - 111