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Mathematics
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Advances in Computational Methods for Finance and Insurance
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Advances in Computational Methods for Finance and Insurance

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

Deadline for manuscript submissions: 31 January 2025 | Viewed by 5613

Special Issue Editors

Dr. Stefania Corsaro

E-Mail Website
Guest Editor
Department of Management and Quantitative Studies, Parthenope University of Naples, 80133 Naples, Italy
Interests: computational finance; numerical methods
Dr. Zelda Marino

E-Mail Website
Guest Editor
Department of Management and Quantitative Studies, Parthenope University of Naples, 80133 Naples, Italy
Interests: computational finance; numerical methods

Special Issue Information

Dear Colleagues,

This Special Issue aims to collect novel contributions in the field of computational methods designed to solve a broad class of problems arising in finance and insurance.

The complexity of modern financial contracts makes computational techniques mandatory for their evaluation. Risk and value estimates must be accurate in order to meet regulation requirements, and must be computed in a suitable turnaround time. It is then a challenging matter to focus on numerical simulation, with the aim of obtaining adaptive solution processes, that are capable of being properly scaled to balance accuracy and computational efficiency on demand, depending on the evaluation context. In addition, the availability of a huge amount of data has driven research towards new methodologies based on artificial intelligence. This Special Issue covers the rapidly growing field of computational methods used to solve problems arising in finance and insurance. We invite authors to submit research papers which present original contributions that focus on numerical methods, also based on artificial intelligence techniques. Topics of interest include, but are not limited to, risk management, derivative pricing, asset allocation, forecasting, and life and non-life insurance, among the others.

Dr. Stefania Corsaro
Dr. Zelda Marino
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 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. Mathematics is an international peer-reviewed open access semimonthly 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 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

  • actuarial science
  • asset and derivative pricing
  • forecasting
  • machine learning
  • numerical methods
  • portfolio selection
  • retirement plan
  • risk management
  • Solvency II

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

Published Papers (3 papers)

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Research

15 pages, 299 KiB  
Article
The Boyle–Romberg Trinomial Tree, a Highly Efficient Method for Double Barrier Option Pricing
by Guillaume Leduc
Mathematics 2024, 12(7), 964; https://doi.org/10.3390/math12070964 - 24 Mar 2024
Cited by 1 | Viewed by 1240
Abstract
Oscillations in option price convergence have long been a problematic aspect of tree methods, inhibiting the use of repeated Richardson extrapolation that could otherwise greatly accelerate convergence, a feature integral to some of the most efficient modern methods. These oscillations are typically caused [...] Read more.
Oscillations in option price convergence have long been a problematic aspect of tree methods, inhibiting the use of repeated Richardson extrapolation that could otherwise greatly accelerate convergence, a feature integral to some of the most efficient modern methods. These oscillations are typically caused by the fluctuating positions of nodes around the discontinuities in the payoff function or its derivatives. Our paper addresses this crucial gap that typically prohibits the use of lattice methods when high efficiency is needed. Focusing on double barrier options, we develop a trinomial tree in which the positions of the nodes are precisely adjusted to align with these discontinuities throughout the option’s lifespan and across various time steps. This alignment enables the use of repeated extrapolation to achieve high order convergence, including near barriers, a well-known challenge in many tree methods. Maintaining the inherent simplicity and adaptability of tree methods, our approach is easily applicable to other models and option types. Full article
(This article belongs to the Special Issue Advances in Computational Methods for Finance and Insurance)
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16 pages, 310 KiB  
Article
A New Look on the Profitability of Fixed and Indexed Mortgage Products
by Paoyu Huang, Chih-Te Yang, Yuhsin Chen and Yensen Ni
Mathematics 2023, 11(17), 3631; https://doi.org/10.3390/math11173631 - 22 Aug 2023
Cited by 1 | Viewed by 1577
Abstract
This study presents a novel approach to analyzing the present value of total profit for fixed and indexed mortgage products in order to determine the optimal mortgage interest rate that would maximize the bank’s expected total profit based on applying the approach used [...] Read more.
This study presents a novel approach to analyzing the present value of total profit for fixed and indexed mortgage products in order to determine the optimal mortgage interest rate that would maximize the bank’s expected total profit based on applying the approach used in operations research to the field of finance. The study considers the impact of lending rate, demand, prepayment, and defaults on bank profits and emphasizes the trade-offs between potential gains and losses when setting the lending rate. As such, we not only used a fixed-rate mortgage model or an index mortgage model with the interest rate as the decision variable, but also employed mathematical analysis methods to find out the loan rate that maximizes the present value of the bank’s expected total profit. The findings revealed that an increase in interest rate, loan amount, and demand positively impacted the bank profits, while prepayment had an adverse effect. The study highlights the importance of carefully evaluating various factors that influence revenue in order to arrive at the most appropriate lending rate that will optimize profits. The results provide valuable insights into the optimal mortgage interest rate and the factors that determine the revenue and profits of a bank, with implications for cost–benefit analysis, fixed-rate mortgage, indexed mortgage, lending rate, defaults, and maximum profit. This study contributes to the existing literature on mortgage products. It provides practical implications for banks in managing their mortgage products efficiently in order to enhance their financial performance and recommends optimizing mortgage interest rates for maximum bank profits by taking the lending rate, demand, and prepayment effects into account. Full article
(This article belongs to the Special Issue Advances in Computational Methods for Finance and Insurance)
16 pages, 312 KiB  
Article
Decoding the Profitability of Insurance Products: A Novel Approach to Evaluating Non-Participating and Participating Insurance Policies
by Chih-Te Yang, Yensen Ni, Mu-Hsiang Yu, Yuhsin Chen and Paoyu Huang
Mathematics 2023, 11(13), 2926; https://doi.org/10.3390/math11132926 - 29 Jun 2023
Cited by 1 | Viewed by 2176
Abstract
This study presents a novel approach to analyzing the present value of total profit for non-participating and participating insurance policies in order to determine the optimal profitability of non-participating and participating insurance policies based on applying the approach used in operations research to [...] Read more.
This study presents a novel approach to analyzing the present value of total profit for non-participating and participating insurance policies in order to determine the optimal profitability of non-participating and participating insurance policies based on applying the approach used in operations research to the field of finance. As such, a comprehensive insurance product evaluation model was developed using both mathematical models and numerical analysis to evaluate the demand for non-participating and participating life insurance policies in response to changes in interest rates. The findings indicate that non-participating life insurance policies offer greater solvency for insurance companies compared to participating policies. The study also highlights the significance of spontaneous and induced demand in determining the total profit of both types of policies. The study concludes that life insurance companies should focus on generating spontaneous consumer demand, reducing induced demand, and implementing the optimal pricing strategy to achieve maximum profits. Full article
(This article belongs to the Special Issue Advances in Computational Methods for Finance and Insurance)
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