Recent Advances on Nonlinear Models in Mathematical Finance, 2nd Edition

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 2572

Special Issue Editors


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Department of Applied Mathematics and Statistics Faculty of Mathematics, Physics and Informatics Comenius University, Bratislava, Slovakia
Interests: partial differential equations and their applications; curvature driven flows of curves and interfaces; financial mathematics; pricing derivative securities
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Applied Mathematics and Numeical Analysis, University of Wuppertal, Wuppertal, Germany
Interests: computational finance; sparse grids; artificial boundaries; splitting methods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mathematical finance provides a large set of theoretical and applied tools that range from pure branches of mathematics to more applied areas with the objective to deeply understand and solve current problems in finance.

In fact, a rigorous analysis of contemporary finance relies on advanced analytical and numerical methods and needs high-level mathematical skills with special emphasis on stochastic calculus with its rich mathematical structure, partial differential equations, partial integrodifferential equations, and fractional diffusion equations. Robust techniques of numerical analysis and computation are also required.

The aim of this Special Issue is to contribute to the enrichment of mathematical finance by broadening the knowledge in this area, with research papers on the following potential topics:

  • Stochastic analysis and control theory in finance;
  • fPDE and fractional models in finance;
  • PIDE and Lévy processes in finance;
  • Interest rate and credit risk modeling;
  • Models for portfolio and risk management;
  • Big data analytics;
  • Computational methods and high-performance computing in finance;
  • Machine learning in finance;
  • High-performance computing in finance;
  • Mathematical modeling in energy markets;
  • Methods for high-dimensional problems;
  • Applications of forward–backward stochastic differential equations;
  • Risk modeling and risk management;
  • Stochastic dynamic programming and Hamilton–Jacobi–Bellman equations;
  • Nonlinear option pricing models, generalizations of the Black–Scholes equation.

Prof. Dr. Daniel Sevcovic
Prof. Dr. Matthias Ehrhardt
Guest Editors

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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

  • fractional models in finance
  • PIDE, and Lévy processes in finance
  • interest rate and credit risk modeling
  • portfolio management
  • risk management
  • big data analytics
  • stochastic dynamic programming
  • Hamilton–Jacobi–Bellman equations
  • nonlinear option pricing models

Published Papers (3 papers)

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Research

13 pages, 4333 KiB  
Article
Projection and Contraction Method for Pricing American Bond Options
by Qi Zhang, Qi Wang, Ping Zuo, Hongbo Du and Fangfang Wu
Mathematics 2023, 11(22), 4689; https://doi.org/10.3390/math11224689 - 18 Nov 2023
Viewed by 656
Abstract
In this paper, an effective numerical method is proposed for a linear complementarity problem (LCP) arising in the valuation of American bond options under the Cox–Ingersoll–Ross (CIR) model. Firstly, a variable substitution is used to simplify the linear complementary model. Secondly, the finite [...] Read more.
In this paper, an effective numerical method is proposed for a linear complementarity problem (LCP) arising in the valuation of American bond options under the Cox–Ingersoll–Ross (CIR) model. Firstly, a variable substitution is used to simplify the linear complementary model. Secondly, the finite difference method is adopted to discretize the simplified model, and an equivalent variational form is obtained. Based on the positive definiteness of the discretized matrix, a projection and contraction method (PCM) is adopted for the resulting discretized variational problem. Finally, numerical experiments highlight the effectiveness and performance of the proposed algorithm. Full article
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28 pages, 786 KiB  
Article
Optimal Consumption and Robust Portfolio Choice for the 3/2 and 4/2 Stochastic Volatility Models
by Yuyang Cheng and Marcos Escobar-Anel
Mathematics 2023, 11(18), 4020; https://doi.org/10.3390/math11184020 - 21 Sep 2023
Viewed by 686
Abstract
This manuscript derives optimal consumption and investment strategies for risk-averse investors under the 4/2 stochastic volatility class of models. We work under an expected utility (EUT) framework and consider a Constant Relative Risk Aversion (CRRA) investor, who may also be ambiguity-averse. The corresponding [...] Read more.
This manuscript derives optimal consumption and investment strategies for risk-averse investors under the 4/2 stochastic volatility class of models. We work under an expected utility (EUT) framework and consider a Constant Relative Risk Aversion (CRRA) investor, who may also be ambiguity-averse. The corresponding Hamilton–Jacobi–Bellman (HJB) and HJB–Isaacs (HJBI) equations are solved in closed-form for a subset of the parametric space and under some restrictions on the portfolio setting, for complete markets. Conditions for proper changes of measure and well-defined solutions are provided. These are the first analytical solutions for the 4/2 stochastic volatility model and the embedded 3/2 model for the type of excess returns established in the literature. We numerically illustrate the differences between the 4/2 model and the embedded cases of the 1/2 model (Heston) as well as the 3/2 model under the same data, and for two main cases: risk-averse investor in a complete market with consumption, and ambiguity-averse investor in a complete market with no consumption. In general, the 4/2 and 1/2 models recommend similar levels of consumption and exposure, while the 3/2 leads to significantly different recommendations. Full article
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27 pages, 4683 KiB  
Article
Contagion Patterns Classification in Stock Indices: A Functional Clustering Analysis Using Decision Trees
by Jorge Omar Razo-De-Anda, Luis Lorenzo Romero-Castro and Francisco Venegas-Martínez
Mathematics 2023, 11(13), 2961; https://doi.org/10.3390/math11132961 - 03 Jul 2023
Viewed by 836
Abstract
This paper aims to identify the main determinants of the countries that present contagion during the period 2000–2021, based on the determination of the behavior patterns of 18 stock market indices of 15 of the main economies. To do that, first, the B-spline [...] Read more.
This paper aims to identify the main determinants of the countries that present contagion during the period 2000–2021, based on the determination of the behavior patterns of 18 stock market indices of 15 of the main economies. To do that, first, the B-spline method and Bezier curves are used to smooth observations by minimizing the noise. Subsequently, the Functional Principal Component Analysis (FPCA) methodology is applied. Then, the K-means clustering algorithm is used to determine the main groups using the silhouette method and cross-validation, considering the sum of squares of the distances as the function to minimize. Finally, classification trees and macroeconomic and financial analyses are used to determine the rules of variables that give a direct explanation of the contagion (clustering) between the stock indices. The main empirical results obtained suggest that the most significant macroeconomic variables are the Gross Domestic Product, the Consumer Price Index, and Foreign Direct Investment, while in the financial aspect and the most representative are Domestic Credit and number of companies listed on the stock market. It is worth noticing that government spending does not have a significant effect at any time as a determinant of contagion. Finally, it is important to mention, and surprising, that Mexico’s IPC was not clustered in the same group of US stock market indices anytime, despite the strong commercial relationship and the geographical closeness. Full article
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