Special Issue "Application of Mathematical Analysis and Models to Financial Economics"

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

Deadline for manuscript submissions: 20 December 2020.

Special Issue Editor

Prof. Francisco Jareño
Website
Guest Editor
Department of Economics and Finance, University of Castilla-La Mancha, 02071 Albacete, Spain
Interests: term structure of interest rates; term structure of volatilities; risk management

Special Issue Information

Dear Colleagues,

In recent years, new mathematical developments have been applied in the context of financial economics. Thus, a relevant challenge is to provide a bridge between, on the one hand, new mathematical tools and, on the other hand, economics and finance issues. So, the main objective of this Special Issue of Mathematics named “Application of Mathematical Analysis and Models to Financial Economics” is the use of new mathematical approaches to economics and finance. Papers may focus on the mathematical part of the valuation of stocks, bonds and financial derivatives. The use of some factor models to manage potential financial risks and other applications in asset pricing theory and interest-rate modeling are also of interest.

We aim to provide a collection of new mathematical applications on economics and finance issues, such as interest rates, volatility modelling, factor models, risk management, derivatives, portfolio management and uncertainty in a quantitative finance context.

Prof. Francisco Jareño
Guest Editor

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

  • Derivatives
  • Factor models
  • Financial mathematics
  • Interest rates
  • Portfolio management
  • Quantitative finance
  • Risk management
  • Uncertainty
  • Volatility modelling

Published Papers (5 papers)

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Research

Open AccessFeature PaperArticle
A New Wavelet Tool to Quantify Non-Periodicity of Non-Stationary Economic Time Series
Mathematics 2020, 8(5), 844; https://doi.org/10.3390/math8050844 - 23 May 2020
Abstract
We introduce a new wavelet tool, the windowed scale index, to study the degree of non-periodicity of time series. The windowed scale index is based on some recently defined tools, such as the windowed scalogram and the scale index. This novel measure is [...] Read more.
We introduce a new wavelet tool, the windowed scale index, to study the degree of non-periodicity of time series. The windowed scale index is based on some recently defined tools, such as the windowed scalogram and the scale index. This novel measure is appropriate for non-stationary time series whose characteristics change over time and, therefore, it can be applied to a wide variety of disciplines. Furthermore, we revise the concept of the scale index and pose a theoretical problem: it is known that if the scale index of a function is not zero then it is non-periodic, but if the scale index of a function is zero, then it is not proved that it has to be periodic. This problem is solved for the particular case of the Haar wavelet, reinforcing the interpretation of the windowed scale index as a useful tool to quantify non-periodicity. In addition, the applicability of this wavelet-based measure is illustrated through several examples, including an economic application which compares the non-periodicity of two major commodities in the world economy, such as crude oil and gold. Finally, we discuss the relationship between non-periodicity and unpredictability, comparing the windowed scale index with the sample entropy. Full article
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Open AccessArticle
Nonlinear Autoregressive Distributed Lag Approach: An Application on the Connectedness between Bitcoin Returns and the Other Ten Most Relevant Cryptocurrency Returns
Mathematics 2020, 8(5), 810; https://doi.org/10.3390/math8050810 - 17 May 2020
Abstract
This article examines the connectedness between Bitcoin returns and returns of ten additional cryptocurrencies for several frequencies—daily, weekly, and monthly—over the period January 2015–March 2020 using a nonlinear autoregressive distributed lag (NARDL) approach. We find important and positive interdependencies among cryptocurrencies and significant [...] Read more.
This article examines the connectedness between Bitcoin returns and returns of ten additional cryptocurrencies for several frequencies—daily, weekly, and monthly—over the period January 2015–March 2020 using a nonlinear autoregressive distributed lag (NARDL) approach. We find important and positive interdependencies among cryptocurrencies and significant long-run relationships among most of them. In addition, non-Bitcoin cryptocurrency returns seem to react in the same way to positive and negative changes in Bitcoin returns, obtaining strong evidence of asymmetry in the short run. Finally, our results show high persistence in the impact of both positive and negative changes in Bitcoin returns on most of the other cryptocurrency returns. Thus, our model explains about 50% of the other cryptocurrency returns with changes in Bitcoin returns. Full article
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Open AccessArticle
Risk Management for Bonds with Embedded Options
Mathematics 2020, 8(5), 790; https://doi.org/10.3390/math8050790 - 13 May 2020
Abstract
This paper examines the behavior of the interest rate risk management measures for bonds with embedded options and studies factors it depends on. The contingent option exercise implies that both the pricing and the risk management of bonds requires modelling future interest rates. [...] Read more.
This paper examines the behavior of the interest rate risk management measures for bonds with embedded options and studies factors it depends on. The contingent option exercise implies that both the pricing and the risk management of bonds requires modelling future interest rates. We use the Ho and Lee (HL) and Black, Derman, and Toy (BDT) consistent interest rate models. In addition, specific interest rate measures that consider the contingent cash-flow structure of these coupon-bearing bonds must be computed. In our empirical analysis, we obtained evidence that effective duration and effective convexity depend primarily on the level of the forward interest rate and volatility. In addition, the higher the interest rate change and the lower the volatility, the greater the differences in pricing of these bonds when using the HL or BDT models. Full article
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Open AccessArticle
A Liquidity Shortfall Analysis Framework for the European Banking Sector
Mathematics 2020, 8(5), 787; https://doi.org/10.3390/math8050787 - 13 May 2020
Abstract
This paper presents an analytical framework for the identification of vulnerabilities arising from the liquidity and funding profile of banks. It is composed of two pillars—estimation of liquidity needs and the counterbalancing capacity of the total liquid assets—that determine a liquidity surplus or [...] Read more.
This paper presents an analytical framework for the identification of vulnerabilities arising from the liquidity and funding profile of banks. It is composed of two pillars—estimation of liquidity needs and the counterbalancing capacity of the total liquid assets—that determine a liquidity surplus or shortfall and the drivers for a range of plausible scenarios. Granular bank-level data on the structure of liabilities, maturation profile, liquid assets quality composition, and asset encumbrance are used for that purpose, also taking into account associated commonality effects. A new liquidity metric is introduced—the distance to liquidity stress indicator (DLSI)—which measures the required stress factor for banks to become illiquid. The novelty of the approach (i.e., taking into account asset encumbrance to determine counterbalancing capacity) provides empirical evidence that asset encumbrance has a significant impact on a bank’s liquidity position, leading to the non-linear behavior of liquidity shortfalls, even in the case of linear stress factors. Full article
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Open AccessArticle
Volatility Timing: Pricing Barrier Options on DAX XETRA Index
Mathematics 2020, 8(5), 722; https://doi.org/10.3390/math8050722 - 04 May 2020
Abstract
This paper analyses the impact of different volatility structures on a range of traditional option pricing models for the valuation of call down and out style barrier options. The construction of a Risk-Neutral Probability Term Structure (RNPTS) is one of the main contributions [...] Read more.
This paper analyses the impact of different volatility structures on a range of traditional option pricing models for the valuation of call down and out style barrier options. The construction of a Risk-Neutral Probability Term Structure (RNPTS) is one of the main contributions of this research, which changes in parallel with regard to the Volatility Term Structure (VTS) in the main and traditional methods of option pricing. As a complementary study, we propose the valuation of options by assuming a constant or historical volatility. The study implements the GARCH (1,1) model with regard to the continuously compound returns of the DAX XETRA Index traded at daily frequency. Current methodology allows for obtaining accuracy forecasts of the realized market barrier option premiums. The paper highlights not only the importance of selecting the right model for option pricing, but also fitting the most accurate volatility structure. Full article
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