Quantitative Finance and Risk Management Research

A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Engineering".

Deadline for manuscript submissions: closed (29 September 2023) | Viewed by 17160

Special Issue Editors


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Guest Editor
Department of Regional Development, Ionian University, 49100 Corfu, Greece
Interests: quantitative finance; risk management; asset pricing models; derivatives
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Business Administration, University of Patras, Patras, Greece
Interests: financial management; quantitative methods; applied economics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of Journal of Computation (ISSN 2079-3197) is devoted to Quantitative Finance and Risk Management Research, reflecting the imperative necessity to incorporate advanced quantitative and computational techniques in finance and risk management.

Our Special Issue welcomes papers dealing with original and innovative contributions in the following areas:

  • Asset pricing;
  • EMH and adaptive market hypothesis;
  • Financial markets;
  • Financial econometrics;
  • Risk management;
  • Financial regulation;
  • Artificial intelligence machine learning in financial trading;
  • Volatility modelling and risk management;
  • Nonlinear and stochastic optimization in finance;
  • Behavior finance;
  • Corporate finance;
  • Derivatives pricing and hedging;
  • Portfolio management;
  • Financial market regulation;
  • Spillover effects;
  • Price discovery and informational efficiency;
  • Asset pricing and macroeconomic fundamentals;
  • Financial market structure and microstructure;
  • Mutual funds and hedge funds;
  • Big data analysis.

Dr. Vasilios I. Sogiakas
Dr. Athanasios G. Tsagkanos
Guest Editors

Manuscript Submission Information

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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. Computation 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 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

  • quantitative finance
  • risk management research
  • credit risk
  • financial crisis

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Related Special Issue

Published Papers (7 papers)

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Research

20 pages, 357 KiB  
Article
Corporate Bankruptcy Prediction Models: A Comparative Study for the Construction Sector in Greece
by Kanellos Toudas, Stefanos Archontakis and Paraskevi Boufounou
Computation 2024, 12(1), 9; https://doi.org/10.3390/computation12010009 - 9 Jan 2024
Cited by 1 | Viewed by 2985
Abstract
This study focuses on testing the efficiency of alternative bankruptcy prediction models (Altman, Ohlson, Zmijewski) and on assessing the possible reasons that led to the confirmation or not of the prevailing model. Data from financial statements of listed (Greek) construction companies before the [...] Read more.
This study focuses on testing the efficiency of alternative bankruptcy prediction models (Altman, Ohlson, Zmijewski) and on assessing the possible reasons that led to the confirmation or not of the prevailing model. Data from financial statements of listed (Greek) construction companies before the economic crisis were utilized. The results showed that Altman’s main predictive model as well as the revised models have low overall predictability for all three years before bankruptcy. Full article
(This article belongs to the Special Issue Quantitative Finance and Risk Management Research)
21 pages, 4272 KiB  
Article
Exploring the Quotation Inertia in International Currency Markets
by Alexander Musaev, Andrey Makshanov and Dmitry Grigoriev
Computation 2023, 11(11), 209; https://doi.org/10.3390/computation11110209 - 24 Oct 2023
Viewed by 1552
Abstract
The authors suggest a methodology that involves conducting a preliminary analysis of inertia in financial time series. Inertia here means the manifestation of some kind of long-term memory. Such effects may take place in complex processes of a stochastic kind. If the decision [...] Read more.
The authors suggest a methodology that involves conducting a preliminary analysis of inertia in financial time series. Inertia here means the manifestation of some kind of long-term memory. Such effects may take place in complex processes of a stochastic kind. If the decision is negative, they do not recommend using predictive management strategies based on trend analysis. The study uses computational schemes to detect and confirm trends in financial market data. The effectiveness of these schemes is evaluated by analyzing the frequency of trend confirmation over different time intervals and with different levels of trend confirmation. Furthermore, the study highlights the limitations of using smoothed curves for trend analysis due to the lag in the dynamics of the curve, emphasizing the importance of considering real-time data in trend analysis for more accurate predictions. Full article
(This article belongs to the Special Issue Quantitative Finance and Risk Management Research)
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13 pages, 802 KiB  
Article
Spillover Effects of Green Finance on Attaining Sustainable Development: Spatial Durbin Model
by Aleksy Kwilinski, Oleksii Lyulyov and Tetyana Pimonenko
Computation 2023, 11(10), 199; https://doi.org/10.3390/computation11100199 - 5 Oct 2023
Cited by 48 | Viewed by 3831
Abstract
Attaining sustainable development goals is a complex process that involves a range of economic, social, and environmental factors. It requires investments in infrastructure, technology, and human capital. In this case, green finance is conducive to channel investments toward sustainable projects and initiatives by [...] Read more.
Attaining sustainable development goals is a complex process that involves a range of economic, social, and environmental factors. It requires investments in infrastructure, technology, and human capital. In this case, green finance is conducive to channel investments toward sustainable projects and initiatives by providing incentives for environmentally friendly practices and technologies and by encouraging companies and investors to adopt sustainable business models. This paper aims to check the spatial spillover effect of green finance on attaining sustainable development for European Union (EU) countries for 2008–2021. The study applies the spatial Durbin model to explore the research hypothesis. The findings confirm that green finance promotes the achievement of sustainable development goals. However, the impact of green finance on attaining sustainable development is heterogeneous depending on the EU region. In this case, the EU should intensify its green finance policy considering the regional features that significantly affect the achievement of sustainable development goals by reducing greenhouse gas emissions, improving energy efficiency, and promoting renewable energy. In addition, it is necessary to develop alternative financial sources involving green bonds that could be used to fund green projects on renewable energy projects, green building construction, etc. Full article
(This article belongs to the Special Issue Quantitative Finance and Risk Management Research)
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21 pages, 1192 KiB  
Article
Applications of Modified Bessel Polynomials to Solve a Nonlinear Chaotic Fractional-Order System in the Financial Market: Domain-Splitting Collocation Techniques
by Mohammad Izadi and Hari Mohan Srivastava
Computation 2023, 11(7), 130; https://doi.org/10.3390/computation11070130 - 3 Jul 2023
Cited by 4 | Viewed by 1408
Abstract
We propose two accurate and efficient spectral collocation techniques based on a (novel) domain-splitting strategy to handle a nonlinear fractional system consisting of three ODEs arising in financial modeling and with chaotic behavior. One of the major numerical difficulties in designing traditional spectral [...] Read more.
We propose two accurate and efficient spectral collocation techniques based on a (novel) domain-splitting strategy to handle a nonlinear fractional system consisting of three ODEs arising in financial modeling and with chaotic behavior. One of the major numerical difficulties in designing traditional spectral methods is in the handling of model problems on a long computational domain, which usually yields to loss of accuracy. One remedy is to split the underlying domain and apply the spectral method locally in each subdomain rather than on the global domain of interest. To treat the chaotic financial system numerically, we use the generalized version of modified Bessel polynomials (GMBPs) in the collocation matrix approaches along with the domain-splitting strategy. Whereas the first matrix collocation scheme is directly applied to the financial model problem, the second one is a combination of the quasilinearization method and the direct first numerical matrix method. In the former approach, we arrive at nonlinear algebraic matrix equations while the resulting systems are linear in the latter method and can be solved more efficiently. A convergence theorem related to GMBPs is proved and an upper bound for the error is derived. Several simulation outcomes are provided to show the utility and applicability of the presented matrix collocation procedures. Full article
(This article belongs to the Special Issue Quantitative Finance and Risk Management Research)
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34 pages, 6703 KiB  
Article
Informal Sector, ICT Dynamics, and the Sovereign Cost of Debt: A Machine Learning Approach
by Apostolos Kotzinos, Vasilios Canellidis and Dimitrios Psychoyios
Computation 2023, 11(5), 90; https://doi.org/10.3390/computation11050090 - 28 Apr 2023
Viewed by 2141
Abstract
We examine the main effects of ICT penetration and the shadow economy on sovereign credit ratings and the cost of debt, along with possible second-order effects between the two variables, on a dataset of 65 countries from 2001 to 2016. The paper presents [...] Read more.
We examine the main effects of ICT penetration and the shadow economy on sovereign credit ratings and the cost of debt, along with possible second-order effects between the two variables, on a dataset of 65 countries from 2001 to 2016. The paper presents a range of machine-learning approaches, including bagging, random forests, gradient-boosting machines, and recurrent neural networks. Furthermore, following recent trends in the emerging field of interpretable ML, based on model-agnostic methods such as feature importance and accumulated local effects, we attempt to explain which factors drive the predictions of the so-called ML black box models. We show that policies facilitating the penetration and use of ICT and aiming to curb the shadow economy may exert an asymmetric impact on sovereign ratings and the cost of debt depending on their present magnitudes, not only independently but also in interaction. Full article
(This article belongs to the Special Issue Quantitative Finance and Risk Management Research)
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20 pages, 1664 KiB  
Article
Pricing and Hedging Index Options under Mean-Variance Criteria in Incomplete Markets
by Pornnapat Yamphram, Phiraphat Sutthimat and Udomsak Rakwongwan
Computation 2023, 11(2), 30; https://doi.org/10.3390/computation11020030 - 7 Feb 2023
Cited by 1 | Viewed by 2292
Abstract
This paper studies the portfolio selection problem where tradable assets are a bank account, and standard put and call options are written on the S&P 500 index in incomplete markets in which there exist bid–ask spreads and finite liquidity. The problem is mathematically [...] Read more.
This paper studies the portfolio selection problem where tradable assets are a bank account, and standard put and call options are written on the S&P 500 index in incomplete markets in which there exist bid–ask spreads and finite liquidity. The problem is mathematically formulated as an optimization problem where the variance of the portfolio is perceived as a risk. The task is to find the portfolio which has a satisfactory return but has the minimum variance. The underlying is modeled by a variance gamma process which can explain the extreme price movement of the asset. We also study how the optimized portfolio changes subject to a user’s views of the future asset price. Moreover, the optimization model is extended for asset pricing and hedging. To illustrate the technique, we compute indifference prices for buying and selling six options namely a European call option, a quadratic option, a sine option, a butterfly spread option, a digital option, and a log option, and propose the hedging portfolios, which are the portfolios one needs to hold to minimize risk from selling or buying such options, for all the options. The sensitivity of the price from modeling parameters is also investigated. Our hedging strategies are decent with the symmetry property of the kernel density estimation of the portfolio payout. The payouts of the hedging portfolios are very close to those of the bought or sold options. The results shown in this study are just illustrations of the techniques. The approach can also be used for other derivatives products with known payoffs in other financial markets. Full article
(This article belongs to the Special Issue Quantitative Finance and Risk Management Research)
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8 pages, 1876 KiB  
Article
On Volatility Transmission between Gold and Silver Markets: Evidence from A Long-Term Historical Period
by Alexandros Koulis and Constantinos Kyriakopoulos
Computation 2023, 11(2), 25; https://doi.org/10.3390/computation11020025 - 3 Feb 2023
Cited by 6 | Viewed by 1816
Abstract
Several studies estimate the volatility spillover effects between gold and silver returns, but none of them used the implied volatility to evaluate the long-term relationship between these two metal markets. Our paper aims to fill this gap in the existing literature. This paper [...] Read more.
Several studies estimate the volatility spillover effects between gold and silver returns, but none of them used the implied volatility to evaluate the long-term relationship between these two metal markets. Our paper aims to fill this gap in the existing literature. This paper investigates the long-term volatility transmission between gold and silver; by using GARCH and VAR modelling, it finds that the volatility transmission from gold to silver is unidirectional. Volatility strategies using options can be designed to take advantage of this especially in times where the volatility transmission is not captured by the markets. Additionally, the results appear to be useful for gaining better portfolio diversification benefits. Investors, for instance, could use the results of this study for making proper investment decisions during the period of economic down-turns or inflation surges. Full article
(This article belongs to the Special Issue Quantitative Finance and Risk Management Research)
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