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

Civil Engineering

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