Empirical study based on the model of rough fractional stochastic volatility (RFSV)

被引:0
|
作者
Zhang, Songyan [1 ]
Hu, Chaoyong [1 ]
机构
[1] Zhejiang Univ Sci & Technol, Sch Sci, Hangzhou 10023, Peoples R China
关键词
SSE 50ETF options; RFSV model; rBergomi model; Monte Carlo simulation; empirical analysis;
D O I
10.1142/S1793962323410039
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
To estimate the parameters of the model of option pricing based on the model of rough fractional stochastic volatility (RFSV), we have carried out the empirical analysis during our study on the pricing of SSE 50ETF options in China. First, we have estimated the parameters of option pricing model by adopting the Monte Carlo simulation. Subsequently, we have empirically examined the pricing performance of the RFSV model by adopting the SSE 50ETF option price from January 2019 to December 2020. Our research findings indicate that by leveraging the RFSV model, we are able to attain a more accurate and stable level of option pricing than the conventional Black-Scholes (B-S) model on constant volatility. The errors of option pricing incurred by the B-S model proved to be larger and exhibited higher volatility, revealing the significant impact imposed by stochastic volatility on option pricing.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Affine fractional stochastic volatility models
    Comte, F.
    Coutin, L.
    Renault, E.
    ANNALS OF FINANCE, 2012, 8 (2-3) : 337 - 378
  • [22] Stochastic volatility and fractional Brownian motion
    Gloter, A
    Hoffmann, M
    STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 2004, 113 (01) : 143 - 172
  • [23] Rough PDEs for Local Stochastic Volatility Models
    Bank, Peter
    Bayer, Christian
    Friz, Peter K.
    Pelizzari, Luca
    MATHEMATICAL FINANCE, 2025,
  • [24] Affine fractional stochastic volatility models
    F. Comte
    L. Coutin
    E. Renault
    Annals of Finance, 2012, 8 (2-3) : 337 - 378
  • [25] An empirical application of stochastic volatility models
    Mahieu, RJ
    Schotman, PC
    JOURNAL OF APPLIED ECONOMETRICS, 1998, 13 (04) : 333 - 359
  • [26] Risk minimization in stochastic volatility models: model risk and empirical performance
    Poulsen, Rolf
    Schenk-Hoppe, Klaus Reiner
    Ewald, Christian-Oliver
    QUANTITATIVE FINANCE, 2009, 9 (06) : 693 - 704
  • [27] Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm
    Takaishi, Tetsuya
    2013 INTERNATIONAL CONFERENCE ON SCIENCE & ENGINEERING IN MATHEMATICS, CHEMISTRY AND PHYSICS (SCIETECH 2013), 2013, 423
  • [28] Stochastic volatility models with volatility driven by fractional Brownian motions
    Duncan, T. E.
    Jakubowski, J.
    Pasik-Duncan, B.
    COMMUNICATIONS IN INFORMATION AND SYSTEMS, 2015, 15 (01) : 47 - 55
  • [29] Modeling the Volatility of Cryptocurrencies: An Empirical Application of Stochastic Volatility Models
    Zahid, Mamoona
    Iqbal, Farhat
    SAINS MALAYSIANA, 2020, 49 (03): : 703 - 712
  • [30] An Empirical Study of LMSV Model in China Stock Market Based on Realized Volatility
    Zheng, Yi
    Liang, Xun
    2015 12TH INTERNATIONAL CONFERENCE ON SERVICE SYSTEMS AND SERVICE MANAGEMENT (ICSSSM), 2015,