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Risks
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Stochastic Modeling and Computational Statistics in Finance
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Stochastic Modeling and Computational Statistics in Finance

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

Deadline for manuscript submissions: 30 June 2025 | Viewed by 11931

Special Issue Editors

Dr. Judit Sági

E-Mail Website
Guest Editor
Department of Finance, Faculty of Finance and Accountancy, Budapest Business School, Buzogary str. 10-12, H-1149 Budapest, Hungary
Interests: banking; financial policy; corporate bankruptcy tests; FinTech
Dr. Nick Chandler

E-Mail Website
Co-Guest Editor
Department of Management, Faculty of Finance and Accountancy, Budapest Business School, Buzogány str. 10-12, 1149 Budapest, Hungary
Interests: organizational management; business ethics; strategic management and planning; business economics

Special Issue Information

Dear Colleagues,

The Guest Editor invites you to submit publications for a Special Issue on Stochastic Modeling and Computational Statistics in Finance. The existing economic literature is diverse in economic modelling; however, in this turbulent world with volatile market indicators there is a space for discussion about the measurement of equilibrium. This Special Issue will cover, inter alia, financial themes related to financial (money market, stock exchange and foreign exchange) markets; ESG-related financing; green, social and sustainable financing; asset-based financing; trade finance; commodity finance; project and structured financing; financing of service industries; financing of sovereign debts; as well as innovative financing solutions like FinTech or WealthTech.

Modelling and methodologies of interest for publication include, but are not limited to:

  • Stochastic modelling of monetary transmission mechanisms;
  • Modelling of independent and identically distributed time series or power law distributions, etc. for capital market instruments (i.e., stock indices, bonds, FX rates) or macroeconomic indicators (i.e., inflation, industrial production, GDP);
  • Parametric or non-parametric modelling of economic bubbles or other monetary anomalies;
  • Non-linear, exponential and asymmetric generalized autoregressive conditional heteroskedasticity (NGARCH, EGARCH, APARCH, GJRGARCH, TARCH and GARCH) models to predict the volatility of returns on financial assets;
  • Applying generalized autoregressive conditional heteroscedasticity (GARCH) models to measure market shock and autoregressive distributive lagged (ARDL) regression model to display COVID-19 measurements and stock indexes performance relationship;
  • Model-based and estimation-based approaches for equilibrium exchange rates over the short-, mid- and long-term horizons (PPP, UIP, CHEER, etc. models);
  • Understanding the role of shocks: structural vector autoregressions (SVARs) and dynamic stochastic general equilibrium (DSGE) approaches to the foreign exchange rate;
  • Predicting price behaviors with vector autoregression (VAR) model, ridge regression, etc.;
  • Modelling the financial accounts and the reserve assets within the balance of payments (e.g., with quantile regression);
  • Modelling FX rates within conventional and non-conventional monetary policy regimes.
  • Application of non-linear threshold autoregressive (TAR), smooth transition autoregressive (STAR) or Markov-switching (MS) models for regime change;
  • Analyzing co-movements among financial market indicators (i.e., FY rates or stock indices) with dynamic conditional correlation (DCC) or copulas;
  • Exploring risk contagion using graph theory and Markov chains;
  • Logit and probit models for sovereign or corporate bankruptcy prediction;
  • Modelling behavioral aspects of banking services, the occurrence of Fintech in commercial and investment banking.

Dr. Judit Sági
Dr. Nick Chandler
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. Risks 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

  • market volatility
  • equilibrium exchange rates
  • financial stability
  • cost of capital
  • financial innovations
  • regime change
  • ESG investments
  • ESG stock indexes
  • time series
  • cross-sectional data

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

22 pages, 12370 KiB  
Article
Inhomogeneous Financial Markets in a Low Interest Rate Environment—A Cluster Analysis of Eurozone Economies
by Tibor Tatay, Zsanett Orlovits and Zsuzsanna Novák
Risks 2022, 10(10), 192; https://doi.org/10.3390/risks10100192 - 5 Oct 2022
Viewed by 1734
Abstract
In the present paper, we investigate the financial homogeneity of the euro area economies by contrasting eurozone countries’ responses to monetary policy steps to the theoretical assumptions of the liquidity trap phenomenon. Our assumption is that the euro area economies are not completely [...] Read more.
In the present paper, we investigate the financial homogeneity of the euro area economies by contrasting eurozone countries’ responses to monetary policy steps to the theoretical assumptions of the liquidity trap phenomenon. Our assumption is that the euro area economies are not completely homogeneous. Hence, in a zero-interest rate environment, the asset holding decisions of economic agents exhibit detectable differences across countries. We verify our assumptions using Eurostat data. We use the financial asset stocks of the euro area countries to cluster the countries concerned. Previous literature has not examined changes in the ratio of financial assets to GDP, nor differences in structural changes in the total stock of financial assets under the zero lower bound. The paper uses k-centers cluster analysis based on Euclidean distance for detecting changes in the portfolio holdings of eurozone economic actors owing to economic crises and monetary policy responses. The results confirm that euro area financial markets are fragmented. There are significant differences across asset markets of different Eurozone countries, both during and after the crisis. Despite some similarities in the portfolio rearrangement across countries, the ECB’s monetary policy does not have a uniform impact on euro area financial markets, and notable differences prevail in the financial asset structures of the economies concerned. Full article
(This article belongs to the Special Issue Stochastic Modeling and Computational Statistics in Finance)
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32 pages, 844 KiB  
Article
Optimal Liquidation, Acquisition and Market Making Problems in HFT under Hawkes Models for LOB
by Ana Roldan Contreras and Anatoliy Swishchuk
Risks 2022, 10(8), 160; https://doi.org/10.3390/risks10080160 - 9 Aug 2022
Cited by 3 | Viewed by 2530
Abstract
The present paper is focused on the solution of optimal control problems such as optimal acquisition, optimal liquidation, and market making in relation to the high-frequency trading market. We have modeled optimal control problems with the price approximated by the diffusion process for [...] Read more.
The present paper is focused on the solution of optimal control problems such as optimal acquisition, optimal liquidation, and market making in relation to the high-frequency trading market. We have modeled optimal control problems with the price approximated by the diffusion process for the general compound Hawkes process (GCHP), using results from the work of Swishchuk and Huffman. These problems have been solvedusing a price process incorporating the unique characteristics of the GCHP. The GCHP was designed to reflect important characteristics of the behaviour of real-world price processes such as the dependence on the previous process and jumping features. In these models, the agent maximizes their own utility or value function by solving the Hamilton–Jacobi–Bellman (HJB) equation and designing a strategy for asset trading. The optimal solutions are expressed in terms of parameters describing the arrival rates and the midprice process from the price process, modeled as a GCHP, allowing such characteristics to influence the optimization process, aiming towards the attainment of a more general solution. Implementations of the obtained results were carried out using real LOBster data. Full article
(This article belongs to the Special Issue Stochastic Modeling and Computational Statistics in Finance)
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14 pages, 980 KiB  
Article
Did the Islamic Stock Index Provide Shelter for Investors during the COVID-19 Crisis? Evidence from an Emerging Stock Market
by Kashif Ali, Muhammad Ashfaque, Adil Saleem, Judit Bárczi and Judit Sági
Risks 2022, 10(6), 109; https://doi.org/10.3390/risks10060109 - 24 May 2022
Cited by 10 | Viewed by 2676
Abstract
The economic and financial chaos caused by COVID-19 has been a discussion topic since the beginning of 2020. This study intends to provide a parallel comparison of volatility change and external shock persistence of the Islamic and conventional stock indexes of the Pakistan [...] Read more.
The economic and financial chaos caused by COVID-19 has been a discussion topic since the beginning of 2020. This study intends to provide a parallel comparison of volatility change and external shock persistence of the Islamic and conventional stock indexes of the Pakistan Stock Exchange. The daily stock index was extracted from Eikon Thomson Reuters for the conventional and Islamic stock index from Jan 2018 to April 2021, which was further divided in three periods, i.e., full, pre-, and post-pandemic period. The data have been analyzed using generalized autoregressive conditional heteroscedasticity (GARCH). An optimally parameterized GARCH (1,1) model is used to measure volatility change for both the pre- to post-pandemic periods. The results suggest that the magnitude of risk in a conventional index is significantly higher than that of the Islamic stock index for the period of study. However, the level of COVID shock persistence is longer in the KSE (conventional) index compared to the KMI (Islamic) index. Full article
(This article belongs to the Special Issue Stochastic Modeling and Computational Statistics in Finance)
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13 pages, 569 KiB  
Article
Exchange Rate Crisis among Inflation Targeting Countries in Sub-Saharan Africa
by Senanu Kwasi Klutse, Judit Sági and Gábor Dávid Kiss
Risks 2022, 10(5), 94; https://doi.org/10.3390/risks10050094 - 4 May 2022
Cited by 1 | Viewed by 3731
Abstract
The exchange market pressure index has proven to be a major indicator in identifying exchange rate crises in economies; however, due to the complexities surrounding developing economies, the efficacy of the index has been called to question. Specifically, the selection of an appropriate [...] Read more.
The exchange market pressure index has proven to be a major indicator in identifying exchange rate crises in economies; however, due to the complexities surrounding developing economies, the efficacy of the index has been called to question. Specifically, the selection of an appropriate index and the problem of selecting the appropriate threshold for identifying exchange market pressure. To investigate this issue, this study identifies exchange rate crisis episodes in South Africa and Ghana using ridge regression, a discrete threshold regression, and Dynamic Ordinary Least Square (DOLS) models. The results are robust in resolving the problems with an exchange market pressure index. They also point to uneven implementation of the inflation targeting policy framework in the studied countries. Full article
(This article belongs to the Special Issue Stochastic Modeling and Computational Statistics in Finance)
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