Application of Fractal Processes and Fractional Derivatives in Finance, 2nd Edition

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "General Mathematics, Analysis".

Deadline for manuscript submissions: 25 November 2024 | Viewed by 2017

Special Issue Editor


E-Mail Website
Guest Editor
School of Mathematics and Statistics, University of New South Wales, Sydney, NSW 2052, Australia
Interests: asset pricing models; regime-switching model; volatility derivatives; stochastic volatility models; consumption and investment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the past four decades, fractional calculus has represented a rapidly advancing research area, both in its theory and application in practical problems arising in various fields, such as econophysics and mathematical finance, in which self-similar processes, such as the Brownian motion, the Levy stable process and the fractional Brownian motion, are employed. Brownian motion was firstly introduced and applied in finance by Bachelier (1900). 

In 1973, the log-price of a stock was modelled as a Brownian motion named the Black–Scholes–Merton model. The Levy stable processes are widely employed in financial econometrics to model the dynamics of stock, commodity, currency exchange prices, etc. The fractional Brownian motion was introduced by Kolmogorov in 1940 and later by Mandelbrot in 1965, and has been applied in hydrology and climatology as well as finance. The dynamics of the volatility of asset prices have been modelled as a fractional Brownian motion in finance and are called rough volatility models. Its applications in finance engender several novel stochastic analysis problems. Fractional diffusion processes are also applied to model the dynamics of underlying assets. The option price under the fractional diffusion setting induces the fractional partial differential equations involving the fractional derivatives with respect to the time. Some closed-form solutions might be found via transform methods in some applications, and numerical methods to solve fractional partial differential equations are developing.

In this Special Issue, we welcome the submission of original research and review articles exploring fractal processes, fractional derivatives and integration, and their applications in finance. The scope of this Special Issue includes, but is not limited to, the following topics:

  • The rough volatility model;
  • Fractal processes applied in finance and other fields;
  • Fractional differential equations;
  • Fractional diffusions;
  • Transform methods applied in fractional differential equations;
  • Numerical methods for fractional partial differential equations;
  • Fractional operators.

Dr. Leung Lung Chan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fractal and Fractional is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • rough volatility model
  • fractal processes applied in finance and other fields
  • fractional differential equations
  • fractional diffusions
  • fractional calculus
  • transform methods applied in fractional differential equations
  • numerical methods for fractional partial differential equations
  • fractional operators

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Related Special Issue

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

10 pages, 1899 KiB  
Article
Application of the Fractal Brownian Motion to the Athens Stock Exchange
by John Leventides, Evangelos Melas, Costas Poulios, Maria Livada, Nick C. Poulios and Paraskevi Boufounou
Fractal Fract. 2024, 8(8), 454; https://doi.org/10.3390/fractalfract8080454 - 31 Jul 2024
Viewed by 723
Abstract
The Athens Stock Exchange (ASE) is a dynamic financial market with complex interactions and inherent volatility. Traditional models often fall short in capturing the intricate dependencies and long memory effects observed in real-world financial data. In this study, we explore the application of [...] Read more.
The Athens Stock Exchange (ASE) is a dynamic financial market with complex interactions and inherent volatility. Traditional models often fall short in capturing the intricate dependencies and long memory effects observed in real-world financial data. In this study, we explore the application of fractional Brownian motion (fBm) to model stock price dynamics within the ASE, specifically utilizing the Athens General Composite (ATG) index. The ATG is considered a key barometer of the overall health of the Greek stock market. Investors and analysts monitor the index to gauge investor sentiment, economic trends, and potential investment opportunities in Greek companies. We find that the Hurst exponent falls outside the range typically associated with fractal Brownian motion. This, combined with the established non-normality of increments, disfavors both geometric Brownian motion and fractal Brownian motion models for the ATG index. Full article
Show Figures

Figure 1

13 pages, 2004 KiB  
Article
Forward Starting Option Pricing under Double Fractional Stochastic Volatilities and Jumps
by Sumei Zhang, Haiyang Xiao and Hongquan Yong
Fractal Fract. 2024, 8(5), 283; https://doi.org/10.3390/fractalfract8050283 - 8 May 2024
Viewed by 782
Abstract
This paper aims to provide an effective method for pricing forward starting options under the double fractional stochastic volatilities mixed-exponential jump-diffusion model. The value of a forward starting option is expressed in terms of the expectation of the forward characteristic function of log [...] Read more.
This paper aims to provide an effective method for pricing forward starting options under the double fractional stochastic volatilities mixed-exponential jump-diffusion model. The value of a forward starting option is expressed in terms of the expectation of the forward characteristic function of log return. To obtain the forward characteristic function, we approximate the pricing model with a semimartingale by introducing two small perturbed parameters. Then, we rewrite the forward characteristic function as a conditional expectation of the proportion characteristic function which is expressed in terms of the solution to a classic PDE. With the affine structure of the approximate model, we obtain the solution to the PDE. Based on the derived forward characteristic function and the Fourier transform technique, we develop a pricing algorithm for forward starting options. For comparison, we also develop a simulation scheme for evaluating forward starting options. The numerical results demonstrate that the proposed pricing algorithm is effective. Exhaustive comparative experiments on eight models show that the effects of fractional Brownian motion, mixed-exponential jump, and the second volatility component on forward starting option prices are significant, and especially, the second fractional volatility is necessary to price accurately forward starting options under the framework of fractional Brownian motion. Full article
Show Figures

Figure 1

Back to TopTop