Risks

33 pages, 2096 KiB

Open AccessArticle

Funding Illiquidity Implied by S&P 500 Derivatives

by Benjamin Golez, Jens Jackwerth and Anna Slavutskaya

Risks 2024, 12(9), 149; https://doi.org/10.3390/risks12090149 - 18 Sep 2024

Viewed by 616

Based on the typical positions of S&P 500 option market makers, we derive a funding illiquidity measure from quoted prices of S&P 500 derivatives. Our measure significantly affects the returns of leveraged managed portfolios; hedge funds with negative exposure to changes in funding [...] Read more.

Based on the typical positions of S&P 500 option market makers, we derive a funding illiquidity measure from quoted prices of S&P 500 derivatives. Our measure significantly affects the returns of leveraged managed portfolios; hedge funds with negative exposure to changes in funding illiquidity earn high returns in normal times and low returns in crisis periods when funding liquidity deteriorates. The results are not driven by existing measures of funding illiquidity, market illiquidity, and proxies for tail risk. Our funding illiquidity measure also affects leveraged closed-end mutual funds and, to an extent, asset classes where leveraged investors are marginal investors. Full article

(This article belongs to the Special Issue Financial Derivatives and Their Applications)

► Show Figures

Figure 1

12 pages, 761 KiB

Open AccessArticle

Automated Machine Learning and Asset Pricing

by Jerome V. Healy, Andros Gregoriou and Robert Hudson

Risks 2024, 12(9), 148; https://doi.org/10.3390/risks12090148 - 14 Sep 2024

Viewed by 1158

Abstract

We evaluate whether machine learning methods can better model excess portfolio returns compared to the standard regression-based strategies generally used in the finance and econometric literature. We examine 17 benchmark factor model specifications based on Expected Utility Theory and theory drawn from behavioural [...] Read more.

We evaluate whether machine learning methods can better model excess portfolio returns compared to the standard regression-based strategies generally used in the finance and econometric literature. We examine 17 benchmark factor model specifications based on Expected Utility Theory and theory drawn from behavioural finance. We assess whether machine learning can identify features of the data-generating process undetected by standard methods and rank the best-performing algorithms. Our tests use 95 years of CRSP data, from 1926 to 2021, encompassing the price history of the broad US stock market. Our findings suggest that machine learning methods provide more accurate models of stock returns based on risk factors than standard regression-based methods of estimation. They also indicate that certain risk factors and combinations of risk factors may be more attractive when more appropriate account is taken of the non-linear properties of the underlying assets. Full article

(This article belongs to the Special Issue Portfolio Selection and Asset Pricing)

► Show Figures

Figure 1

13 pages, 1025 KiB

Open AccessArticle

Dynamics of Foreign Exchange Futures Trading Volumes in Thailand

by Woradee Jongadsayakul

Risks 2024, 12(9), 147; https://doi.org/10.3390/risks12090147 - 14 Sep 2024

Viewed by 615

Abstract

Following the introduction of EUR/USD futures and USD/JPY futures on 31 October 2022, Thailand Futures Exchange first entered the top 11 list of derivatives exchanges based on foreign exchange derivative volumes in 2022. This paper investigates the dynamics of foreign exchange futures trading [...] Read more.

Following the introduction of EUR/USD futures and USD/JPY futures on 31 October 2022, Thailand Futures Exchange first entered the top 11 list of derivatives exchanges based on foreign exchange derivative volumes in 2022. This paper investigates the dynamics of foreign exchange futures trading volumes in Thailand through the VAR(2) model. Trading volumes of EUR/USD futures, USD/JPY futures, and USD/THB futures are considered over the sample period from 31 October 2022 to 12 January 2024. The empirical results provide no evidence that the trading volume of EUR/USD futures is dependent on the past trading volumes of USD/JPY futures and USD/THB futures. The Granger causality test results show the existence of bidirectional causality between the trading volumes of USD/JPY futures and USD/THB futures. The results of the impulse response function are consistent with the sign results of the VAR(2) model, showing that the USD/JPY futures trading volume has a negative impact on the USD/THB futures trading volume, and vice versa. The analysis of variance decomposition shows that the variability of the USD/JPY futures trading volume and USD/THB futures trading volume, apart from its own shock, is explained by other FX futures trading volume shocks. Therefore, traders should pay more attention to new FX futures trading activity due to its negative impact on the USD/THB futures trading volume and its contribution to the variance in the USD/THB futures trading volume. Understanding the futures trading volume relationship also helps Thailand Futures Exchange develop new products and services that can foster market liquidity and stability. Full article

(This article belongs to the Special Issue Financial Derivatives: Market Risk, Pricing, and Hedging)

► Show Figures

Figure 1

23 pages, 802 KiB

Open AccessArticle

What Drives Banks to Provide Green Loans? Corporate Governance and Ownership Structure Perspectives of Vietnamese Listed Banks

by Ariful Hoque, Duong Thuy Le and Thi Le

Risks 2024, 12(9), 146; https://doi.org/10.3390/risks12090146 - 13 Sep 2024

Viewed by 1371

Abstract

This study delves into the influence of banks’ governance and ownership structures on green lending. To examine this, we utilized the two-step system GMM and PCSE methods on the panel data of Vietnamese commercial banks spanning from 2010 to 2023. The findings suggest [...] Read more.

This study delves into the influence of banks’ governance and ownership structures on green lending. To examine this, we utilized the two-step system GMM and PCSE methods on the panel data of Vietnamese commercial banks spanning from 2010 to 2023. The findings suggest that board characteristics, precisely board size, board independence, and gender diversity, play a significant role in encouraging banks to provide green credit. The study highlights the importance of ownership structure in green lending. Banks with a high percentage of government ownership tend to fund more green projects, while foreign counterparts are reluctant to fund green finance. A mechanism test is also conducted to point out that banks’ disclosure of their green loan commitments is an influential channel whereby corporate governance and ownership structure impact green loans. Additionally, this research finds that the issuance of the Green Loan Principles in 2018 can facilitate banks’ governance of sustainable lending. Full article

► Show Figures

Figure 1

24 pages, 486 KiB

Open AccessArticle

Spotlight on Corporate Fraud: How Is Takaful Insurance Stability Affected by Its Disclosure?

by Wael Hemrit and Ines Belgacem

Risks 2024, 12(9), 145; https://doi.org/10.3390/risks12090145 - 12 Sep 2024

Viewed by 978

Abstract

This study examines the influence of fraud disclosure (FR_DISC) in annual reports on the financial stability of Takaful insurance (TKI) in Saudi Arabia over the period of 2014 to 2022. Moreover, the current study aims to explore the mediating impact of Shariah board [...] Read more.

This study examines the influence of fraud disclosure (FR_DISC) in annual reports on the financial stability of Takaful insurance (TKI) in Saudi Arabia over the period of 2014 to 2022. Moreover, the current study aims to explore the mediating impact of Shariah board size in shaping this relationship using agency theory and examines whether the different Islamic governance attributes could affect this stability differently. Using the dynamic generalized method of moments (GMM) approach to address the possibility of endogeneity, it was found that FR_DISC is significantly negatively related to the financial stability of a sample TKI. We also provide evidence that the larger the size of a Shariah board, the less FR_DISC affects TKI stability. Furthermore, significant negative influence of ownership concentration and the proportion of non-executives’ independent board members on the stability of insurance companies was also observed. Overall, our analysis reveals several significant challenges if accounting and whistleblowing are to contribute to financial stability. Full article

22 pages, 510 KiB

Open AccessArticle

Corporate Governance and Capital Structure Decisions: Moderating Role of inside Ownership

by Suman Paul Chowdhury, Riyashad Ahmed, Nitai Chandra Debnath, Nafisa Ali and Roni Bhowmik

Risks 2024, 12(9), 144; https://doi.org/10.3390/risks12090144 - 10 Sep 2024

Viewed by 887

Abstract

This study empirically investigates the association between board attributes and capital structure decisions of non-financial listed firms in Bangladesh. This study also investigates how this association is shaped and moderated by the level of insider ownership. The current study takes 3096 firm-year observations [...] Read more.

This study empirically investigates the association between board attributes and capital structure decisions of non-financial listed firms in Bangladesh. This study also investigates how this association is shaped and moderated by the level of insider ownership. The current study takes 3096 firm-year observations of firms that are listed on the Dhaka Stock Exchange from 2004 to 2023. Multiple regression analysis on panel data was used, and pooled OLS was selected by resolving stationary issues. Moreover, this study used lagged variables and a GMM estimator to address endogeneity. The results show that both board size and board independence are more positively correlated with a firm’s leverage under conditions of a high level of inside ownership. On the other hand, without the moderating effect of inside ownership, gender diversity on the board does not have any significant impact on a firm’s leverage, and it turns into a positive association due to the moderating effect of inside ownership. This result is consistent with the existing theory and previous findings. After the introduction of corporate governance guidelines, the inside owners’ effect on board size and board independence became substantial, indicating that corporate governance guidelines with the moderating role of inside ownership play a significant role in capital structure decisions in Bangladeshi listed firms. Full article

(This article belongs to the Special Issue Corporate Finance and Intellectual Capital Management)

22 pages, 2113 KiB

Open AccessFeature PaperReview

Trends and Risks in Mergers and Acquisitions: A Review

by Manuel García-Nieto, Vicente Bueno-Rodríguez, Juan Manuel Ramón-Jerónimo and Raquel Flórez-López

Risks 2024, 12(9), 143; https://doi.org/10.3390/risks12090143 - 9 Sep 2024

Viewed by 4597

Abstract

This study examines risk factors in mergers and acquisitions (M&As) identified in the recent literature, addressing the following question: “What risk factors associated with M&A transactions are discussed in the recent academic literature?” A semi-systematic literature review was conducted using a comprehensive search [...] Read more.

This study examines risk factors in mergers and acquisitions (M&As) identified in the recent literature, addressing the following question: “What risk factors associated with M&A transactions are discussed in the recent academic literature?” A semi-systematic literature review was conducted using a comprehensive search strategy with targeted keywords related to M&A risks. Papers from 2020 to 2024 were selected based on quality and relevance, with detailed review of abstracts and titles. Co-occurrence analysis using VOSviewer software (version 1.6.20) was applied to categorize key themes. The review of 118 papers identified four main risk categories: information asymmetry; performance and corporate reputation; litigation and investor protection; and geopolitical factors. Findings reveal complex interdependencies among these risks, highlighting the need for a holistic approach to risk management. Corporate social responsibility (CSR) is crucial for mitigating risks, improving transparency, and enhancing reputation. This study offers recommendations for better financial disclosures, robust environmental, social and governance strategies, and the integration of digital finance technologies as blockchain in M&A activity. Future research should include longitudinal studies on M&A risk dynamics, case studies on corporate governance, advanced valuation methods, and comparative analyses across regions and industries, focusing on emerging technologies like AI and blockchain. Full article

► Show Figures

Figure 1

13 pages, 826 KiB

Open AccessArticle

The Role of Sex in the Assessment of Return and Downside Risk in Decumulation Financial Planning

by Amaia Jone Betzuen Álvarez and Amancio Betzuen Zalbidegoitia

Risks 2024, 12(9), 142; https://doi.org/10.3390/risks12090142 - 6 Sep 2024

Viewed by 863

Abstract

This paper aims to assess the return and downside risk of a decumulation portfolio established at the retirement age of a senior, with a determined lifetime horizon differentiated by the sex of the citizen. To measure the portfolio’s return and downside risk, two [...] Read more.

This paper aims to assess the return and downside risk of a decumulation portfolio established at the retirement age of a senior, with a determined lifetime horizon differentiated by the sex of the citizen. To measure the portfolio’s return and downside risk, two ratios conditioned by seniors’ risk attitude towards portfolio failure are employed: the downside Sortino ratio and the downside risk–return ratio. Unlike other research in the field, this manuscript provides three portfolio compositions catering to different senior investment profiles: aggressive, moderate, and conservative. Additionally, it offers a decumulation horizon conditioned by the sex-specific life expectancy of the individual, instead of offering different scenarios for conducting a sensitivity analysis. Lastly, this study was conducted across three socioeconomically distinct countries: the US, Spain, and Japan. The results clearly demonstrate that both sex and nationality significantly influence the selection of the optimal decumulation portfolio composition aimed at exhausting funds by the senior’s demise. Full article

► Show Figures

Figure 1

28 pages, 4809 KiB

Open AccessArticle

Insurance Analytics with Clustering Techniques

by Charlotte Jamotton, Donatien Hainaut and Thomas Hames

Risks 2024, 12(9), 141; https://doi.org/10.3390/risks12090141 - 5 Sep 2024

Viewed by 756

Abstract

The K-means algorithm and its variants are well-known clustering techniques. In actuarial applications, these partitioning methods can identify clusters of policies with similar attributes. The resulting partitions provide an actuarial framework for creating maps of dominant risks and unsupervised pricing grids. This research [...] Read more.

The K-means algorithm and its variants are well-known clustering techniques. In actuarial applications, these partitioning methods can identify clusters of policies with similar attributes. The resulting partitions provide an actuarial framework for creating maps of dominant risks and unsupervised pricing grids. This research article aims to adapt well-established clustering methods to complex insurance datasets containing both categorical and numerical variables. To achieve this, we propose a novel approach based on Burt distance. We begin by reviewing the K-means algorithm to establish the foundation for our Burt distance-based framework. Next, we extend the scope of application of the mini-batch and fuzzy K-means variants to heterogeneous insurance data. Additionally, we adapt spectral clustering, a technique based on graph theory that accommodates non-convex cluster shapes. To mitigate the computational complexity associated with spectral clustering’s

O (n^{3})

runtime, we introduce a data reduction method for large-scale datasets using our Burt distance-based approach. Full article

► Show Figures

Figure 1

25 pages, 968 KiB

Open AccessArticle

A Financial Stability Model for Iraqi Companies

by Narjis Abdlkareem Ibrahim, Mahdi Salehi, Hussen Amran Naji Al-Refiay and Mahmoud Lari Dashtbayaz

Risks 2024, 12(9), 140; https://doi.org/10.3390/risks12090140 - 4 Sep 2024

Viewed by 846

Abstract

The current study aims to develop a financial stability model in Iraq; after reviewing the relevant literature and sources related to financial stability and considering Iraq’s social, economic, political, and cultural conditions, a conceptual model and a research questionnaire have been developed. Based [...] Read more.

The current study aims to develop a financial stability model in Iraq; after reviewing the relevant literature and sources related to financial stability and considering Iraq’s social, economic, political, and cultural conditions, a conceptual model and a research questionnaire have been developed. Based on the developed conceptual model, macro variables at the level of the economy, micro variables at the level of companies, the environmental variables of companies, and corporate governance have been selected as model dimensions. Each dimension has several components, including several indicators; 39 indicators were measured through questions in 2024. The research questionnaire was subjected to the opinion of 21 experts with sufficient experimental and academic records on this subject, and by using the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods, the results were analyzed, and the final model was extracted. In this model, the scientific method used to analyze the results determines the weight of each dimension, component, and indicator. The results of this research show that the dimensions of corporate governance, the variables of the company environment, micro variables at the company level, and macro variables at the economic level with coefficients of 0.345, 0.251, 0.236, and 0.168, respectively, have the most significant impact on the ranking of the company’s financial stability. So far, research has yet to be conducted to present the financial stability model of Iraqi companies. Therefore, the present research is one of the first studies in this respect, which presents a model both qualitatively (by designing a questionnaire and conceptual model) and quantitatively (through a mathematical model) to measure financial stability that can help the development of science and knowledge in this field. Full article

(This article belongs to the Special Issue Financial Analysis, Corporate Finance and Risk Management)

► Show Figures

Figure 1

20 pages, 4025 KiB

Open AccessArticle

A Novel Hybrid Deep Learning Method for Accurate Exchange Rate Prediction

by Farhat Iqbal, Dimitrios Koutmos, Eman A. Ahmed and Lulwah M. Al-Essa

Risks 2024, 12(9), 139; https://doi.org/10.3390/risks12090139 - 30 Aug 2024

Viewed by 808

Abstract

The global foreign exchange (FX) market represents a critical and sizeable component of our financial system. It is a market where firms and investors engage in both speculative trading and hedging. Over the years, there has been a growing interest in FX modeling [...] Read more.

The global foreign exchange (FX) market represents a critical and sizeable component of our financial system. It is a market where firms and investors engage in both speculative trading and hedging. Over the years, there has been a growing interest in FX modeling and prediction. Recently, machine learning (ML) and deep learning (DL) techniques have shown promising results in enhancing predictive accuracy. Motivated by the growing size of the FX market, as well as advancements in ML, we propose a novel forecasting framework, the MVO-BiGRU model, which integrates variational mode decomposition (VMD), data augmentation, Optuna-optimized hyperparameters, and bidirectional GRU algorithms for monthly FX rate forecasting. The data augmentation in the Prevention module significantly increases the variety of data combinations, effectively reducing overfitting issues, while the Optuna optimization ensures optimal model configuration for enhanced performance. Our study’s contributions include the development of the MVO-BiGRU model, as well as the insights gained from its application in FX markets. Our findings demonstrate that the MVO-BiGRU model can successfully avoid overfitting and achieve the highest accuracy in out-of-sample forecasting, while outperforming benchmark models across multiple assessment criteria. These findings offer valuable insights for implementing ML and DL models on low-frequency time series data, where artificial data augmentation can be challenging. Full article

(This article belongs to the Special Issue Risks Journal: A Decade of Advancing Knowledge and Shaping the Future)

► Show Figures

Figure 1

16 pages, 391 KiB

Open AccessArticle

The Spatial Analysis of the Role of Green Finance in Carbon Emission Reduction

by Menghan Xiao, Xiaojing Guo, Gonghang Chen, Xiangfeng Ji and Wenqing Sun

Risks 2024, 12(9), 138; https://doi.org/10.3390/risks12090138 - 29 Aug 2024

Viewed by 835

Abstract

Under the “dual carbon” goal, the core issue at present is to improve the environment while ensuring economic development. As a result, green finance, that is a tool that integrates finance and environmental protection, has shown increasingly significant carbon reduction effects. With the [...] Read more.

Under the “dual carbon” goal, the core issue at present is to improve the environment while ensuring economic development. As a result, green finance, that is a tool that integrates finance and environmental protection, has shown increasingly significant carbon reduction effects. With the panel data of 30 provinces in China from 2012 to 2021 being the research object, this study employs a spatial Durbin model to examine the impact of green finance on carbon emissions and further discusses its mechanism effects. The empirical results indicate the following: firstly, the development of green finance effectively suppresses carbon emissions; secondly, by decomposing the spatial effect of green finance on carbon emissions, it is found that green finance also reduces carbon emissions in neighboring regions due to the spillover effects; finally, green finance can suppress carbon emissions through technological innovation and industrial structure upgrading. Therefore, it is imperative to actively engage in practical work related to green finance, to establish a sound system for green finance, and simultaneously, to enhance cooperation among regions in terms of green finance, in order to fully leverage its role in suppressing carbon emissions. Full article

(This article belongs to the Special Issue Nexus between Green Finance and Green Total Factor Productivity: Principles, Techniques, and Noval Opportunities)

33 pages, 5094 KiB

Open AccessArticle

Claim Prediction and Premium Pricing for Telematics Auto Insurance Data Using Poisson Regression with Lasso Regularisation

by Farha Usman, Jennifer S. K. Chan, Udi E. Makov, Yang Wang and Alice X. D. Dong

Risks 2024, 12(9), 137; https://doi.org/10.3390/risks12090137 - 28 Aug 2024

Viewed by 876

Abstract

We leverage telematics data on driving behavior variables to assess driver risk and predict future insurance claims in a case study utilising a representative telematics sample. In the study, we aim to categorise drivers according to their driving habits and establish premiums that [...] Read more.

We leverage telematics data on driving behavior variables to assess driver risk and predict future insurance claims in a case study utilising a representative telematics sample. In the study, we aim to categorise drivers according to their driving habits and establish premiums that accurately reflect their driving risk. To accomplish our goal, we employ the two-stage Poisson model, the Poisson mixture model, and the Zero-Inflated Poisson model to analyse the telematics data. These models are further enhanced by incorporating regularisation techniques such as lasso, adaptive lasso, elastic net, and adaptive elastic net. Our empirical findings demonstrate that the Poisson mixture model with the adaptive lasso regularisation outperforms other models. Based on predicted claim frequencies and drivers’ risk groups, we introduce a novel usage-based experience rating premium pricing method. This method enables more frequent premium updates based on recent driving behaviour, providing instant rewards and incentivising responsible driving practices. Consequently, it helps to alleviate cross-subsidization among risky drivers and improves the accuracy of loss reserving for auto insurance companies. Full article

► Show Figures

Figure 1

23 pages, 516 KiB

Open AccessFeature PaperArticle

Dynamic Asset Pricing in a Unified Bachelier–Black–Scholes–Merton Model

by W. Brent Lindquist, Svetlozar T. Rachev, Jagdish Gnawali and Frank J. Fabozzi

Risks 2024, 12(9), 136; https://doi.org/10.3390/risks12090136 - 27 Aug 2024

Viewed by 589

Abstract

We present a unified, market-complete model that integrates both Bachelier and Black–Scholes–Merton frameworks for asset pricing. The model allows for the study, within a unified framework, of asset pricing in a natural world that experiences the possibility of negative security prices or riskless [...] Read more.

We present a unified, market-complete model that integrates both Bachelier and Black–Scholes–Merton frameworks for asset pricing. The model allows for the study, within a unified framework, of asset pricing in a natural world that experiences the possibility of negative security prices or riskless rates. Unlike the classical Black–Scholes–Merton, we show that option pricing in the unified model differs depending on whether the replicating, self-financing portfolio uses riskless bonds or a single riskless bank account. We derive option price formulas and extend our analysis to the term structure of interest rates by deriving the pricing of zero-coupon bonds, forward contracts, and futures contracts. We identify a necessary condition for the unified model to support a perpetual derivative. Discrete binomial pricing under the unified model is also developed. In every scenario analyzed, we show that the unified model simplifies to the standard Black–Scholes–Merton pricing under specific limits and provides pricing in the Bachelier model limit. We note that the Bachelier limit within the unified model allows for positive riskless rates. The unified model prompts us to speculate on the possibility of a mixed multiplicative and additive deflator model for risk-neutral option pricing. Full article

(This article belongs to the Special Issue Financial Derivatives: Market Risk, Pricing, and Hedging)

22 pages, 1518 KiB

Open AccessArticle

Using the Fuzzy Version of the Pearl’s Algorithm for Environmental Risk Assessment Tasks

by Oleg Uzhga-Rebrov

Risks 2024, 12(9), 135; https://doi.org/10.3390/risks12090135 - 26 Aug 2024

Viewed by 653

Abstract

In risk assessment, numerous subfactors influence the probabilities of the main factors. These main factors reflect adverse outcomes, which are essential in risk assessment. A Bayesian network can model the entire set of subfactors and their interconnections. To assess the probabilities of all [...] Read more.

In risk assessment, numerous subfactors influence the probabilities of the main factors. These main factors reflect adverse outcomes, which are essential in risk assessment. A Bayesian network can model the entire set of subfactors and their interconnections. To assess the probabilities of all possible states of the main factors (adverse consequences), complete information about the probabilities of all relevant subfactor states in the network nodes must be utilized. This is a typical task of probabilistic inference. The algorithm proposed by J. Pearl is widely used for point estimates of relevant probabilities. However, in many practical problems, including environmental risk assessment, it is not possible to assign crisp probabilities for relevant events due to the lack of sufficient statistical data. In such situations, expert assignment of probabilities is widely used. Uncertainty in expert assessments can be successfully modeled using triangular fuzzy numbers. That is why this article proposes a fuzzy version of this algorithm, which can solve the problem of probabilistic inference on a Bayesian network when the initial probability values are given as triangular fuzzy numbers. Full article

► Show Figures

Figure 1

26 pages, 964 KiB

Open AccessArticle

Financial Risk Management in Healthcare in the Provision of High-Tech Medical Assistance for Sustainable Development: Evidence from Russia

by Abdula M. Chililov

Risks 2024, 12(9), 134; https://doi.org/10.3390/risks12090134 - 26 Aug 2024

Viewed by 849

Abstract

The research determines the level of financial risk in the Russian healthcare system and identifies prospects for improving the current Russian practice of financial risk management in healthcare when providing high-tech medical care for sustainable development (using Russia as an example). The author [...] Read more.

The research determines the level of financial risk in the Russian healthcare system and identifies prospects for improving the current Russian practice of financial risk management in healthcare when providing high-tech medical care for sustainable development (using Russia as an example). The author summarizes the advanced experience of the top 20 largest healthcare organizations in Russia by revenue in 2022. Based on this experience, the author developed an SEM model of the financial risks in healthcare during the provision of high-tech medical care in Russia from a sustainable development perspective. The theoretical significance of the developed model lies in uncovering the previously unknown causal relationships between the implementation of the ICT, sustainable development support, and financial risks in healthcare. The model reveals a new market dimension of financial risks for healthcare organizations in Russia. The main conclusion is that implementing the ICT and support for sustainable development helps to reduce the financial risks in healthcare. The identified potential for reducing financial risks in providing high-tech medical care in Russia until 2026 is practically significant. This prospect can be practically applied as a roadmap for the digital modernization and sustainable development of healthcare until 2026, enhancing the state healthcare policy in Russia. The established systemic relationship between ICT implementation, sustainable development support, and financial risks in healthcare is of managerial importance because it will increase the predictability of the financial risks in the market dimension of healthcare in Russia. The newly developed approach to risk management in healthcare during the provision of high-tech medical care in Russia has expanded the instrumental framework of risk management for healthcare organizations in Russia and revealed further opportunities for improving its efficiency. Full article

(This article belongs to the Special Issue Managing Financial Risks Based on Corporate Social Responsibility for Sustainable Development II)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Risks, Volume 12, Issue 9 (September 2024) – 16 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI