Special Issue "Application of Stochastic Analysis in Mathematical Finance"

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Financial Mathematics".

Deadline for manuscript submissions: 31 January 2021.

Special Issue Editors

Prof. Dr. Elisa Alòs
Website
Guest Editor
Department d’Economia i Empresa and Barcelona Graduate School of Economics, University of Pompeu Fabra, Barcelona, Spain
Interests: mathematical finance; stochastic modeling; fractional Brownian motion
Prof. Dr. Jorge A. León

Guest Editor
Control Automático, CINVESTAV-IPN, Mexico City, Mexico

Special Issue Information

Dear Colleagues,

This Special Issue is devoted to applications of stochastic analysis to the area of quantitative finance. The increasing complexity of markets needs the tools of stochastic analysis to be implemented to address problems associated with quantitative finance as, for example, hedging, option pricing, portfolio optimization, and study of volatilities, among others. Indeed, we cannot think about addressing or understanding problems of modern quantitative finance without using tools of stochastic analysis such as the Feynman–Kac formula, Girsanov’s theorem, Itô’s lemma, derivatives in the Malliavin calculus sense, the results used for the study of local volatilities, etc.

This Special Issue will contain 5 invited survey papers written by prestigious experts in quantitative finance, as well as research papers on applications of stochastic analysis to quantitative finance.

Prof. Dr. Elisa Alòs
Prof. Dr. Jorge A. León
Guest Editors

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 papers will be 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. Mathematics 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 1200 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

  • Applications of stochastic analysis
  • Modeling
  • Numerical methods
  • Option pricing
  • Portfolio optimization
  • Stochastic volatility models
  • Study of volatility

Published Papers (1 paper)

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Research

Open AccessArticle
Examining the Feasibility of the Sturm–Liouville Theory for Ross Recovery
Mathematics 2020, 8(4), 550; https://doi.org/10.3390/math8040550 - 09 Apr 2020
Abstract
Recent studies have suggested that it is feasible to recover a physical measure from a risk-neutral measure. Given a market state variable modeled as a Markov process, the key concept is to extract a unique positive eigenfunction of the generator of the Markov [...] Read more.
Recent studies have suggested that it is feasible to recover a physical measure from a risk-neutral measure. Given a market state variable modeled as a Markov process, the key concept is to extract a unique positive eigenfunction of the generator of the Markov process. In this work, the feasibility of this recovery theory is examined. We prove that, under a restrictive integrability condition, recovery is feasible if and only if both endpoints of the state variable are limit-point. Several examples with explicit positive eigenfunctions are considered. However, in general, a physical measure cannot be recovered from a risk-neutral measure. We provide a financial and mathematical rationale for such recovery failure. Full article
(This article belongs to the Special Issue Application of Stochastic Analysis in Mathematical Finance)
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