Advances in Mathematical Behavioural Finance and Decision Analysis

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

Deadline for manuscript submissions: 28 February 2025 | Viewed by 788

Special Issue Editors


E-Mail Website
Guest Editor
Department of Mathematics and Phisics, University of Campania, ‘Luigi Vanvitelli’—Viale A. Lincoln, 5-81100 Caserta, Italy
Interests: financial mathematics; decision theory; intertemporal choice; financial psychology; behavioural finance; neurofinance; financial literacy

E-Mail Website
Guest Editor
Department of Economics and Business, Universidad de Almería, La Cañada de San Urbano, s/n, 04120 Almería, Spain
Interests: investment; financial analysis; portfolio; financial economics; capital markets
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Medical, Oral and Biotechnological Sciences, University G. d'Annunzio Chieti, Pescara Via dei Vestini, 31–66100 Chieti, Italy
Interests: biostatistics; machine learning; statistical learning; epidemiology; data analysis; clustering; classification

Special Issue Information

Dear Colleagues,

Mathematical finance provides a fundamental framework for describing finance-related problems and phenomena. Through the application of a rigorous mathematical approach, mathematical finance addresses the definition of models aimed at understanding markets, asset valuation, and risk management to provide the decision-maker with a rational and structured framework for financial analysis. Cognitive psychology has shown that the difference between the theoretical models of mathematical finance and the actual behaviour of decision-makers is linked to the human nature of decision-making. This nature is characterised by emotions, biases, and cognitive limitations. Behavioural finance has developed as a separate approach from mathematical finance, but it contributes in a complementary way to the descriptions provided by mathematical models through a perspective based on the analysis of human psychology to understand the particularities and intricate mechanisms of financial decisions. From recent developments based on the combination of mathematical finance and behavioural finance, uncertainty emerges as an essential element that models should include alongside the well-known concept of risk: choices under uncertainty and choices under risk are indispensable foundations of new theoretical developments.

This Special Issue, entitled "Advances in Mathematical Behavioural Finance and Decision Analysis", will focus on delivering novel insights into mathematical and statistical methodologies for modelling behavioural patterns within decision analysis. Modern finance is currently characterised by the necessity of finding optimal solutions to business and investment decisions in the face of uncertainty and the context of the consequences of human behaviour. To describe financial phenomena, choices made under conditions of risk or uncertainty, and the decision-making processes involved in evaluating and selecting alternatives, authors can use various complex frameworks that incorporate multiple approaches.

This Special Issue aims to report the latest progress in the theory of modern finance in real-world settings and make relevant case studies. Original research articles and reviews are welcome that address one or more of the following problems: financial risk management, mathematical and statistical finance modelling, decision-making, optimisation, financial applications, financial computation and modelling, and behavioural finance. Topics of interest include, but are not limited to, the issues presented. We look forward to receiving your contributions.

Prof. Viviana Ventre
Prof. Salvador Cruz Rambaud
Dr. Annamaria Porreca
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

  • financial risk management
  • mathematical and statistical finance modelling
  • decision-making
  • optimisation
  • financial applications
  • financial computation and modelling
  • functional data analysis
  • behavioural finance

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.

Published Papers (1 paper)

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

Research

23 pages, 325 KiB  
Article
Housing Developers’ Heterogeneous Decision-Making under Negative Shock after the High-Growth Era: Evidence from the Chinese Real Estate Economy
by Dachen Sheng, Huijun Cheng and Minmin Yin
Mathematics 2024, 12(12), 1798; https://doi.org/10.3390/math12121798 - 8 Jun 2024
Viewed by 423
Abstract
This research uses difference-in-difference (DID) and other empirical methods to analyze firm-level real estate data to discover how heterogeneous firm characteristics affect managers’ decision-making about development expansion when a firm faces a temporary negative sales shock in the Chinese housing market. The manager’s [...] Read more.
This research uses difference-in-difference (DID) and other empirical methods to analyze firm-level real estate data to discover how heterogeneous firm characteristics affect managers’ decision-making about development expansion when a firm faces a temporary negative sales shock in the Chinese housing market. The manager’s decision is a utility maximization problem under uncertainty, determined by their risk aversion levels, which managers choose to optimize by considering other factors of interest, including career risk and personal wealth. Also, the advance payment rule encourages real estate developers to maintain high turnover, since new projects allow developers to collect cash first. The results show that state-owned enterprises (SOEs) are much more conservative than other types of developers. SOEs tend to focus on current developing projects. Firms with more concentrated management pursue expansion and seek to use new project sales to compensate for their slower growth. Larger developers with headquarters in large cities tend to slow their development speed when they observe negative signals, as they can quickly engage in new projects given these firms’ easy access to financial resources such as bank loans. This study makes a novel contribution to the literature since previous research has tended to focus on the macro market level rather than the firm level. The findings also have strong policy and regulation value. The results indicate that higher cashflow monitoring needs, especially to monitor family-owned developers, to prevent misuse and excessive project expansion. Full article
(This article belongs to the Special Issue Advances in Mathematical Behavioural Finance and Decision Analysis)
Back to TopTop