Quantitative Methods in Economics and Finance

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 30313

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Special Issue Editors

Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 010 26 Zilina, Slovakia
Interests: financial markets; financial econometrics; bankruptcy prediction; credit risk
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Special Issue Information

Dear Colleagues,

The beginnings of quantitative methods and mathematical modeling in economics and finance can be traced back to the early stages of the development of classical political economy and are associated with names such as William Petty (1623–1687), Francois Quesnay (1694–1774), Léon Walras (1834–1910), Leonard Euler (1707–1783), Vilfredo Pareto (1848–1923), and many others. After the First World War, we can see a massive expansion of quantitative methods, both theoretical and practical. The exception was neither economics nor finance. An important milestone in this development was the year 1931, when the Econometric Society was founded and started to issue the Econometrica journal on a regular base. This helped to establish a new scientific branch of Econometrics, which considers the mathematical description and statistical verification of economic relations as its main content and, in a broader sense, also the implementation of mathematical methods into economics. The importance of quantitative methods in economics is clearly evident by the number of Nobel Prizes awarded for economics, where mathematical economists form a significant majority of laureates. For the thematic focus of this Special Issue, allow us to mention the most important ones: Leonid Vitalievič Kantorovič, James Tobin, Franco Modigliani, Harry M. Markowitz, Merton Miller, William F. Sharpe, John Forbes Nash, John C. Harsanyi, Robert Merton, Myron Scholes, Robert F. Engle, Clive W. J. Granger, Robert J. Aumann, Leonid Hurwicz a Eugene Fama.

We invite both theoretical and empirical contributions, which will be an important contribution to the development of the subject issue. We would like to thank potential authors for their efforts and wish plenty of success in the theory and practice of quantitative methods and mathematical modeling in economics and finance.

Prof. Dr. Tomas Kliestik
Dr. Katarina Valaskova
Dr. Maria Kovacova
Guest Editors

Manuscript Submission Information

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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 1800 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

  • Risk analysis and modeling in economics and finance
  • Value at risk and conditional value at risk
  • CreditMertics and CorporateMetrics
  • Financial econometrics
  • Volatility models
  • Risk of corporate bankruptcy prediction
  • Structural credit risk modeling
  • Reduced-form credit risk modeling
  • Earnings management

Published Papers (8 papers)

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Research

21 pages, 2152 KiB  
Article
Use of Neural Networks to Accommodate Seasonal Fluctuations When Equalizing Time Series for the CZK/RMB Exchange Rate
Risks 2021, 9(1), 1; https://doi.org/10.3390/risks9010001 - 22 Dec 2020
Cited by 29 | Viewed by 3345
Abstract
The global nature of the Czech economy means that quantitative knowledge of the influence of the exchange rate provides useful information for all participants in the international economy. Systematic and academic research show that the issue of estimating the Czech crown/Chinese yuan exchange [...] Read more.
The global nature of the Czech economy means that quantitative knowledge of the influence of the exchange rate provides useful information for all participants in the international economy. Systematic and academic research show that the issue of estimating the Czech crown/Chinese yuan exchange rate, with consideration for seasonal fluctuations, has yet to be dealt with in detail. The aim of this contribution is to present a methodology based on neural networks that takes into consideration seasonal fluctuations when equalizing time series by using the Czech crown and Chinese yuan as examples. The analysis was conducted using daily information on the Czech crown/Chinese yuan exchange rate over a period of more than nine years. This is the equivalent of 3303 data inputs. Statistica software, version 12 by Dell Inc. was used to process the input data and, subsequently, to generate multi-layer perceptron networks and radial basis function neural networks. Two versions of neural structures were produced for regression purposes, the second of which used seasonal fluctuations as a categorical variable–year, month, day of the month and week—when the value was measured. All the generated and retained networks had the ability to equalize the analyzed time series, although the second variant demonstrated higher efficiency. The results indicate that additional variables help the equalized time series to retain order and precision. Of further interest is the finding that multi-layer perceptron networks are more efficient than radial basis function neural networks. Full article
(This article belongs to the Special Issue Quantitative Methods in Economics and Finance)
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14 pages, 344 KiB  
Article
Determining Economic Security of a Business Based on Valuation of Intangible Assets according to the International Valuation Standards (IVS)
Risks 2020, 8(4), 110; https://doi.org/10.3390/risks8040110 - 20 Oct 2020
Cited by 6 | Viewed by 3011
Abstract
This work considered the economic security of an enterprise with regard to the valuation of intangible assets according to the International Valuation Standards (IVS). This study is essential due to a growing number of companies with intangible assets (trademarks, patents, know-how, etc.) as [...] Read more.
This work considered the economic security of an enterprise with regard to the valuation of intangible assets according to the International Valuation Standards (IVS). This study is essential due to a growing number of companies with intangible assets (trademarks, patents, know-how, etc.) as their main value. This study included analysis of the impact created by the value of intangible assets and intellectual property on company capitalization and economic security plus a regression model. An algorithm was developed to determine the economic security of a business based on the valuation of intangible assets according to the IVS. The suggested algorithm can allow a company to manage its intangible assets effectively using the IVS, which, in turn, will provide the required level of economic security for further development and achievement of strategic goals by the business entity. Full article
(This article belongs to the Special Issue Quantitative Methods in Economics and Finance)
19 pages, 841 KiB  
Article
A Note on Simulation Pricing of π-Options
Risks 2020, 8(3), 90; https://doi.org/10.3390/risks8030090 - 28 Aug 2020
Viewed by 2280
Abstract
In this work, we adapt a Monte Carlo algorithm introduced by Broadie and Glasserman in 1997 to price a π-option. This method is based on the simulated price tree that comes from discretization and replication of possible trajectories of the underlying asset’s [...] Read more.
In this work, we adapt a Monte Carlo algorithm introduced by Broadie and Glasserman in 1997 to price a π-option. This method is based on the simulated price tree that comes from discretization and replication of possible trajectories of the underlying asset’s price. As a result, this algorithm produces the lower and the upper bounds that converge to the true price with the increasing depth of the tree. Under specific parametrization, this π-option is related to relative maximum drawdown and can be used in the real market environment to protect a portfolio against volatile and unexpected price drops. We also provide some numerical analysis. Full article
(This article belongs to the Special Issue Quantitative Methods in Economics and Finance)
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16 pages, 1149 KiB  
Article
Modelling Australian Dollar Volatility at Multiple Horizons with High-Frequency Data
Risks 2020, 8(3), 89; https://doi.org/10.3390/risks8030089 - 26 Aug 2020
Cited by 1 | Viewed by 2754
Abstract
Long-range dependency of the volatility of exchange-rate time series plays a crucial role in the evaluation of exchange-rate risks, in particular for the commodity currencies. The Australian dollar is currently holding the fifth rank in the global top 10 most frequently traded currencies. [...] Read more.
Long-range dependency of the volatility of exchange-rate time series plays a crucial role in the evaluation of exchange-rate risks, in particular for the commodity currencies. The Australian dollar is currently holding the fifth rank in the global top 10 most frequently traded currencies. The popularity of the Aussie dollar among currency traders belongs to the so-called three G’s—Geology, Geography and Government policy. The Australian economy is largely driven by commodities. The strength of the Australian dollar is counter-cyclical relative to other currencies and ties proximately to the geographical, commercial linkage with Asia and the commodity cycle. As such, we consider that the Australian dollar presents strong characteristics of the commodity currency. In this study, we provide an examination of the Australian dollar–US dollar rates. For the period from 18:05, 7th August 2019 to 9:25, 16th September 2019 with a total of 8481 observations, a wavelet-based approach that allows for modelling long-memory characteristics of this currency pair at different trading horizons is used in our analysis. Findings from our analysis indicate that long-range dependence in volatility is observed and it is persistent across horizons. However, this long-range dependence in volatility is most prominent at the horizon longer than daily. Policy implications have emerged based on the findings of this paper in relation to the important determinant of volatility dynamics, which can be incorporated in optimal trading strategies and policy implications. Full article
(This article belongs to the Special Issue Quantitative Methods in Economics and Finance)
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20 pages, 475 KiB  
Article
A Raroc Valuation Scheme for Loans and Its Application in Loan Origination
Risks 2020, 8(2), 63; https://doi.org/10.3390/risks8020063 - 10 Jun 2020
Cited by 2 | Viewed by 5225
Abstract
In this article, a risk-adjusted return on capital (RAROC) valuation scheme for loans is derived. The critical assumption throughout the article is that no market information on a borrower’s credit quality like bond or CDS (Credit Default Swap) spreads is available. Therefore, market-based [...] Read more.
In this article, a risk-adjusted return on capital (RAROC) valuation scheme for loans is derived. The critical assumption throughout the article is that no market information on a borrower’s credit quality like bond or CDS (Credit Default Swap) spreads is available. Therefore, market-based approaches are not applicable, and an alternative combining market and statistical information is needed. The valuation scheme aims to derive the individual cost components of a loan which facilitates the allocation to a bank’s operational units. After its introduction, a theoretical analysis of the scheme linking the level of interest rates and borrower default probabilities shows that a bank should only originate a loan, when the interest rate a borrower is willing to accept is inside the profitability range for this client. This range depends on a bank’s internal profitability target and is always a finite interval only or could even be empty if a borrower’s credit quality is too low. Aside from analyzing the theoretical properties of the scheme, we show how it can be directly applied in the daily loan origination process of a bank. Full article
(This article belongs to the Special Issue Quantitative Methods in Economics and Finance)
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20 pages, 2027 KiB  
Article
Heads and Tails of Earnings Management: Quantitative Analysis in Emerging Countries
Risks 2020, 8(2), 57; https://doi.org/10.3390/risks8020057 - 01 Jun 2020
Cited by 14 | Viewed by 3838
Abstract
Earnings management is a globally used tool for long-term profitable enterprises and for the apparatus of reduction of bankruptcy risk in developed countries. This phenomenon belongs to the integral and fundamental part of their business finance. However, this has still been lax in [...] Read more.
Earnings management is a globally used tool for long-term profitable enterprises and for the apparatus of reduction of bankruptcy risk in developed countries. This phenomenon belongs to the integral and fundamental part of their business finance. However, this has still been lax in emerging countries. The models of detections of the existence of earnings management are based on discretionary accrual. The goal of this article is to detect the existence of earnings management in emerging countries by times series analysis. This econometric investigation uses the observations of earnings before interest and taxes of 1089 Slovak enterprises and 1421 Bulgarian enterprises in financial modelling. Our findings confirm the significant existence of earnings management in both analyzed countries, based on a quantitative analysis of unit root and stationarity. The managerial activities are purposeful, which is proven by the existence of no stationarity in the time series and a clear occurrence of the unit root. In addition, the results highlight the year 2014 as a significant milestone of change in the development of earnings management in both countries, based on homogeneity analyses. These facts identify significant parallels between Slovak and Bulgarian economics and business finance. Full article
(This article belongs to the Special Issue Quantitative Methods in Economics and Finance)
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23 pages, 2544 KiB  
Article
Application of Diffusion Models in the Analysis of Financial Markets: Evidence on Exchange Traded Funds in Europe
Risks 2020, 8(1), 18; https://doi.org/10.3390/risks8010018 - 14 Feb 2020
Cited by 3 | Viewed by 4408
Abstract
Exchange traded funds (ETFs) are financial innovations that may be considered as a part of the index financial instruments category, together with stock index derivatives. The aim of this paper is to explore the trajectories and formulates predictions regarding the spread of ETFs [...] Read more.
Exchange traded funds (ETFs) are financial innovations that may be considered as a part of the index financial instruments category, together with stock index derivatives. The aim of this paper is to explore the trajectories and formulates predictions regarding the spread of ETFs on the financial markets in six European countries. It demonstrates ETFs’ development trajectories with regard to stock index futures and options that may be considered as their substitutes, e.g., in risk management. In this paper, we use mathematical models of the diffusion of innovation that allow unveiling the evolutionary patterns of turnover of ETFs; the time span of the analysis is 2004–2015, i.e., the period of dynamic changes on the European ETF markets. Such an approach has so far rarely been applied in this field of research. Our findings indicate that the development of ETF markets has been strongest in Italy and France and weaker in the other countries, especially Poland and Hungary. The results highlight significant differences among European countries and prove that diffusion has not taken place in all the cases; there are also considerable differences in the predicted development paths. Full article
(This article belongs to the Special Issue Quantitative Methods in Economics and Finance)
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11 pages, 309 KiB  
Article
Omnichannel Banking Economy
Risks 2019, 7(4), 115; https://doi.org/10.3390/risks7040115 - 07 Nov 2019
Cited by 6 | Viewed by 4345
Abstract
In modern market conditions, customers who purchase banking products require a high level of service. In particular, they require continuous real-time service with the ability to instantly “switch” between service channels. The article analyzed the economic component of the omnichannel sales management system [...] Read more.
In modern market conditions, customers who purchase banking products require a high level of service. In particular, they require continuous real-time service with the ability to instantly “switch” between service channels. The article analyzed the economic component of the omnichannel sales management system in banking. The existing barriers to introducing omnichannels to the practice of banking management have been identified. The features of the calculation of individual elements of the cost of sales at various stages of the life cycle of sales (sales funnel) are considered. An economic–mathematical model for managing the cost and profitability of sales by selecting the optimal omnichannel chains was proposed. The omnichannel model of interaction with customers enables banks to simultaneously achieve several key goals of increasing their own business efficiency: increase sales while reducing their cost and improving the quality of customer service. The model can be used not only in banking, but also in other forms of retail business where it is possible to collect detailed statistics and build a factor analysis of conversion through a sales funnel. Full article
(This article belongs to the Special Issue Quantitative Methods in Economics and Finance)
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