Special Issue "Quantitative Methods for Economics and Finance"

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

Deadline for manuscript submissions: 30 September 2020.

Special Issue Editors

Prof. J.E. Trinidad-Segovia
Website
Guest Editor
Department of Economy and Company, University of Almería, Spain
Interests: long memory; portfolio theory; fractal dimension
Prof. Dr. Miguel Ángel Sánchez-Granero
Website
Guest Editor
Departamento de Matemáticas, Universidad de Almería, 04120 Almería, Spain
Interests: fractal structures, fractal dimension, Hurst exponent, finance, asymmetric topology

Special Issue Information

Dear Colleagues,

Since the mid-twentieth century, it has been clear that the more classical mathematical models were not enough to explain the complexity of the financial and economic series. Since then, the effort to develop new tools and mathematical models for their application to economics and finance has been remarkable. However, it is still necessary to continue developing new tools, as well as continue studying the latest tools developed for the study of the financial and economic series. These tools can come from techniques and models taken from physics or from new branches of mathematics such as fractals, dynamical systems, or new statistical techniques such as big data.

The purpose of this Special Issue is to gather a collection of articles reflecting the latest developments in different fields of economics and finance where mathematics plays an important role.

Prof. J.E. Trinidad-Segovia
Prof. Miguel Ángel Sánchez-Granero
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

  • Financial series
  • Portfolio theory
  • Factor models
  • Volatility modeling
  • Quantitative methods
  • Long memory
  • Computational finance
  • Statistical arbitrage

Published Papers (6 papers)

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

Research

Open AccessArticle
Market Volatility of the Three Most Powerful Military Countries during Their Intervention in the Syrian War
Mathematics 2020, 8(5), 834; https://doi.org/10.3390/math8050834 - 21 May 2020
Abstract
This paper analyzes the volatility dynamics in the financial markets of the (three) most powerful countries from a military perspective, namely, the U.S., Russia, and China, during the period 2015–2018 that corresponds to their intervention in the Syrian war. As far as we [...] Read more.
This paper analyzes the volatility dynamics in the financial markets of the (three) most powerful countries from a military perspective, namely, the U.S., Russia, and China, during the period 2015–2018 that corresponds to their intervention in the Syrian war. As far as we know, there is no literature studying this topic during such an important distress period, which has had very serious economic, social, and humanitarian consequences. The Generalized Autoregressive Conditional Heteroscedasticity (GARCH (1, 1)) model yielded the best volatility results for the in-sample period. The weighted historical simulation produced an accurate value at risk (VaR) for a period of one month at the three considered confidence levels. For the out-of-sample period, the Monte Carlo simulation method, based on student t-copula and peaks-over-threshold (POT) extreme value theory (EVT) under the Gaussian kernel and the generalized Pareto (GP) distribution, overstated the risk for the three countries. The comparison of the POT-EVT VaR of the three countries to a portfolio of stock indices pertaining to non-military countries, namely Finland, Sweden, and Ecuador, for the same out-of-sample period, revealed that the intervention in the Syrian war may be one of the pertinent reasons that significantly affected the volatility of the stock markets of the three most powerful military countries. This paper is of great interest for policy makers, central bank leaders, participants involved in these markets, and all practitioners given the economic and financial consequences derived from such dynamics. Full article
(This article belongs to the Special Issue Quantitative Methods for Economics and Finance)
Show Figures

Figure 1

Open AccessArticle
An Extension of the Concept of Derivative: Its Application to Intertemporal Choice
Mathematics 2020, 8(5), 696; https://doi.org/10.3390/math8050696 - 02 May 2020
Abstract
The framework of this paper is the concept of derivative from the point of view of abstract algebra and differential calculus. The objective of this paper is to introduce a novel concept of derivative which arises in certain economic problems, specifically in intertemporal [...] Read more.
The framework of this paper is the concept of derivative from the point of view of abstract algebra and differential calculus. The objective of this paper is to introduce a novel concept of derivative which arises in certain economic problems, specifically in intertemporal choice when trying to characterize moderately and strongly decreasing impatience. To do this, we have employed the usual tools and magnitudes of financial mathematics with an algebraic nomenclature. The main contribution of this paper is twofold. On the one hand, we have proposed a novel framework and a different approach to the concept of relative derivation which satisfies the so-called generalized Leibniz’s rule. On the other hand, in spite of the fact that this peculiar approach can be applied to other disciplines, we have presented the mathematical characterization of the two main types of decreasing impatience in the ambit of behavioral finance, based on a previous characterization involving the proportional increasing of the variable “time”. Finally, this paper points out other patterns of variation which could be applied in economics and other scientific disciplines. Full article
(This article belongs to the Special Issue Quantitative Methods for Economics and Finance)
Show Figures

Figure 1

Open AccessArticle
The VIF and MSE in Raise Regression
Mathematics 2020, 8(4), 605; https://doi.org/10.3390/math8040605 - 16 Apr 2020
Abstract
The raise regression has been proposed as an alternative to ordinary least squares estimation when a model presents collinearity. In order to analyze whether the problem has been mitigated, it is necessary to develop measures to detect collinearity after the application of the [...] Read more.
The raise regression has been proposed as an alternative to ordinary least squares estimation when a model presents collinearity. In order to analyze whether the problem has been mitigated, it is necessary to develop measures to detect collinearity after the application of the raise regression. This paper extends the concept of the variance inflation factor to be applied in a raise regression. The relevance of this extension is that it can be applied to determine the raising factor which allows an optimal application of this technique. The mean square error is also calculated since the raise regression provides a biased estimator. The results are illustrated by two empirical examples where the application of the raise estimator is compared to the application of the ridge and Lasso estimators that are commonly applied to estimate models with multicollinearity as an alternative to ordinary least squares. Full article
(This article belongs to the Special Issue Quantitative Methods for Economics and Finance)
Show Figures

Figure 1

Open AccessArticle
Discounted and Expected Utility from the Probability and Time Trade-Off Model
Mathematics 2020, 8(4), 601; https://doi.org/10.3390/math8040601 - 15 Apr 2020
Abstract
This paper shows the interaction between probabilistic and delayed rewards. In decision- making processes, the Expected Utility (EU) model has been employed to assess risky choices whereas the Discounted Utility (DU) model has been applied to intertemporal choices. Despite both models being different, [...] Read more.
This paper shows the interaction between probabilistic and delayed rewards. In decision- making processes, the Expected Utility (EU) model has been employed to assess risky choices whereas the Discounted Utility (DU) model has been applied to intertemporal choices. Despite both models being different, they are based on the same theoretical principle: the rewards are assessed by taking into account the sum of their utilities and some similar anomalies have been revealed in both models. The aim of this paper is to characterize and consider particular cases of the Time Trade-Off (PPT) model and show that they correspond to the EU and DU models. Additionally, we will try to build a PTT model starting from a discounted and an expected utility model able to overcome the limitations pointed out by Baucells and Heukamp. Full article
(This article belongs to the Special Issue Quantitative Methods for Economics and Finance)
Show Figures

Figure 1

Open AccessArticle
Some Notes on the Formation of a Pair in Pairs Trading
Mathematics 2020, 8(3), 348; https://doi.org/10.3390/math8030348 - 05 Mar 2020
Abstract
The main goal of the paper is to introduce different models to calculate the amount of money that must be allocated to each stock in a statistical arbitrage technique known as pairs trading. The traditional allocation strategy is based on an equal weight [...] Read more.
The main goal of the paper is to introduce different models to calculate the amount of money that must be allocated to each stock in a statistical arbitrage technique known as pairs trading. The traditional allocation strategy is based on an equal weight methodology. However, we will show how, with an optimal allocation, the performance of pairs trading increases significantly. Four methodologies are proposed to set up the optimal allocation. These methodologies are based on distance, correlation, cointegration and Hurst exponent (mean reversion). It is showed that the new methodologies provide an improvement in the obtained results with respect to an equal weighted strategy. Full article
(This article belongs to the Special Issue Quantitative Methods for Economics and Finance)
Show Figures

Figure 1

Open AccessArticle
Exploring the Link between Academic Dishonesty and Economic Delinquency: A Partial Least Squares Path Modeling Approach
Mathematics 2019, 7(12), 1241; https://doi.org/10.3390/math7121241 - 15 Dec 2019
Cited by 1
Abstract
This paper advances the study of the relationship between the attitude towards academic dishonesty and other types of dishonest and even fraudulent behavior, such as tax evasion and piracy. It proposes a model in which the attitudes towards two types of cheating and [...] Read more.
This paper advances the study of the relationship between the attitude towards academic dishonesty and other types of dishonest and even fraudulent behavior, such as tax evasion and piracy. It proposes a model in which the attitudes towards two types of cheating and fraud are systematically analyzed in connection with a complex set of latent construct determinants and control variables. It attempts to predict the tolerance towards tax evasion and social insurance fraud and piracy, using academic cheating as the main predictor. The proposed model surveys 504 student respondents, uses a partial least squares—path modeling analysis, and employs two subsets of latent constructs to account for context and disposition. The relationship between the outcome variable and the subset of predictors that account for context is mediated by yet another latent construct—Preoccupation about Money—that has been shown to strongly influence people’s attitude towards a whole range of social and economic behaviors. The results show academic dishonesty is a statistically significant predictor of an entire range of unethical and fraudulent behavior acceptance, and confirm the role played by both contextual and dispositional variables; moreover, they show that dispositional and contextual variables tend to be segregated according to how they impact the outcome. They also show that money priming does not act as a mediator, in spite of its stand-alone impact on the outcome variables. The most important result, however, is that the effect size of the main predictor is large. The contribution of this paper is two-fold: it advances a line of research previously sidestepped, and it proposes a comprehensive and robust model with a view to establish a hierarchy of significance and effect size in predicting deviance and fraud. Most of all, this research highlights the central role played by academic dishonesty in predicting the acceptance of any type of dishonest behavior, be it in the workplace, at home, or when discharging one’s responsibilities as a citizen. The results presented here give important clues as to where to start intervening in order to discourage the acceptance of deviance and fraud. Educators, university professors, and academic administrators should be at the forefront of targeted campaigns and policies aimed at fighting and reducing academic dishonesty. Full article
(This article belongs to the Special Issue Quantitative Methods for Economics and Finance)
Show Figures

Figure 1

Back to TopTop