Nonparametric Estimation of Fractional Option Pricing Model
Joint Authors
Liu, Songlin
Li, Qing
Zhou, Misi
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-15
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
The establishment of the fractional Black–Scholes option pricing model is under a major condition with the normal distribution for the state price density (SPD) function.
However, the fractional Brownian motion is deemed to not be martingale with a long memory effect of the underlying asset, so that the estimation of the state price density (SPD) function is far from simple.
This paper proposes a convenient approach to get the fractional option pricing model by changing variables.
Further, the option price is transformed as the integral function of the cumulative density function (CDF), so it is not necessary to estimate the distribution function individually by complex approaches.
Finally, it encourages to estimate the fractional option pricing model by the way of nonparametric regression and makes empirical analysis with the traded 50 ETF option data in Shanghai Stock Exchange (SSE).
American Psychological Association (APA)
Li, Qing& Liu, Songlin& Zhou, Misi. 2020. Nonparametric Estimation of Fractional Option Pricing Model. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1201742
Modern Language Association (MLA)
Li, Qing…[et al.]. Nonparametric Estimation of Fractional Option Pricing Model. Mathematical Problems in Engineering No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1201742
American Medical Association (AMA)
Li, Qing& Liu, Songlin& Zhou, Misi. Nonparametric Estimation of Fractional Option Pricing Model. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1201742
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201742