Risks

23 pages, 2121 KiB

Open AccessFeature PaperArticle

Evaluating Transition Rules for Enhancing Fairness in Bonus–Malus Systems: An Application to the Saudi Arabian Auto Insurance Market

by Asrar Alyafie, Corina Constantinescu and Jorge Yslas

Risks 2025, 13(1), 18; https://doi.org/10.3390/risks13010018 - 20 Jan 2025

Viewed by 462

Abstract

A Bonus–Malus System (BMS) is a ratemaking mechanism used in insurance to adjust premiums based on a policyholder’s claim history, with the goal of segmenting risk profiles more accurately. A BMS typically comprises three key components: the number of BMS levels, the transition [...] Read more.

A Bonus–Malus System (BMS) is a ratemaking mechanism used in insurance to adjust premiums based on a policyholder’s claim history, with the goal of segmenting risk profiles more accurately. A BMS typically comprises three key components: the number of BMS levels, the transition rules dictating the movements of policyholders within the system, and the relativities used to determine premium adjustments. This paper explores the impact of modifications to these three elements on risk classification, assessed through the mean squared error. The model parameters are calibrated with real-world data from the Saudi auto insurance market. We begin the analysis by focusing on transition rules based solely on claim frequency, a framework in which most implemented BMSs work, including the current Saudi BMS. We then consider transition rules that depend on frequency and severity, in which higher penalties are given for large claim sizes. The results show that increasing the number of levels typically improves risk segmentation but requires balancing practical implementation constraints and that the adequate selection of the penalties is critical to enhancing fairness. Moreover, the study reveals that incorporating a severity-based penalty enhances risk differentiation, especially when there is a dependence between the claim frequency and severity. Full article

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26 pages, 5146 KiB

Open AccessArticle

Automated Bitcoin Trading dApp Using Price Prediction from a Deep Learning Model

by Zhi Zhan Lua, Chee Kiat Seow, Raymond Ching Bon Chan, Yiyu Cai and Qi Cao

Risks 2025, 13(1), 17; https://doi.org/10.3390/risks13010017 - 17 Jan 2025

Viewed by 633

Abstract

Distributed ledger technology (DLT) and cryptocurrency have revolutionized the financial landscape and relevant applications, particularly in investment opportunities. Despite its growth, the market’s volatility and technical complexities hinder widespread adoption. This study proposes a cryptocurrency trading system powered by advanced machine learning (ML) [...] Read more.

Distributed ledger technology (DLT) and cryptocurrency have revolutionized the financial landscape and relevant applications, particularly in investment opportunities. Despite its growth, the market’s volatility and technical complexities hinder widespread adoption. This study proposes a cryptocurrency trading system powered by advanced machine learning (ML) models to address these challenges. By leveraging random forest (RF), long short-term memory (LSTM), and bi-directional LSTM (Bi-LSTM) models, the cryptocurrency trading system is equipped with strong predictive capacity and is able to optimize trading strategies for Bitcoin. The up-to-date price prediction information obtained by the machine learning model is incorporated by custom oracle contracts and is transmitted to portfolio smart contracts. The integration of smart contracts and on-chain oracles ensures transparency and security, allowing real-time verification of portfolio management. The deployed cryptocurrency trading system performs these actions automatically without human intervention, which greatly reduces barriers to entry for ordinary users and investors. The results demonstrate the feasibility of creating a cryptocurrency trading system, with the LSTM model achieving a return on investment (ROI) of 488.74% for portfolio management during the duration of 9 December 2022 to 23 May 2024. The ROI obtained by the LSTM model is higher than the performance of Bitcoin at 234.68% and that of other benchmarking models with RF and Bi-LSTM over the same timeframe. This approach offers significant cost savings, transparent portfolio management, and a trust-free platform for investors, paving the way for broader cryptocurrency adoption. Future work will focus on enhancing prediction accuracy and achieving greater decentralization. Full article

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21 pages, 477 KiB

Open AccessFeature PaperArticle

Optimal Design of Multi-Asset Options

by Alejandro Balbás, Beatriz Balbás and Raquel Balbás

Risks 2025, 13(1), 16; https://doi.org/10.3390/risks13010016 - 16 Jan 2025

Viewed by 393

Abstract

The combination of stochastic derivative pricing models and downside risk measures often leads to the paradox (risk, return) = (−infinity, +infinity) in a portfolio choice problem. The construction of a portfolio of derivatives with high expected returns and very negative downside risk (henceforth [...] Read more.

The combination of stochastic derivative pricing models and downside risk measures often leads to the paradox (risk, return) = (−infinity, +infinity) in a portfolio choice problem. The construction of a portfolio of derivatives with high expected returns and very negative downside risk (henceforth “golden strategy”) has only been studied if all the involved derivatives have the same underlying asset. This paper also considers multi-asset derivatives, gives practical methods to build multi-asset golden strategies for both the expected shortfall and the expectile risk measure, and shows that the use of multi-asset options makes the performance of the obtained golden strategy more efficient. Practical rules are given under the Black–Scholes–Merton multi-dimensional pricing model. Full article

23 pages, 589 KiB

Open AccessArticle

Unravelling the Link Between Financialisation and Economic Growth: Evidence from Croatia

by Agim Mamuti, Fatbardha Kadiu, Idaver Sherifi, Inna Romānova and Simon Grima

Risks 2025, 13(1), 15; https://doi.org/10.3390/risks13010015 - 16 Jan 2025

Viewed by 372

Abstract

This study investigates the relationship between financialisation and economic growth in Croatia, focusing on the period from 1995 to 2021. Using time series econometric models, including the Augmented Dickey–Fuller test for stationarity, Johansen’s cointegration test for long-term relationships, and the Granger causality test [...] Read more.

This study investigates the relationship between financialisation and economic growth in Croatia, focusing on the period from 1995 to 2021. Using time series econometric models, including the Augmented Dickey–Fuller test for stationarity, Johansen’s cointegration test for long-term relationships, and the Granger causality test within the Vector Error Correction Model (VECM) framework, the research reveals a sustained long-term equilibrium relationship between financialisation and economic growth in Croatia. However, the Granger causality test does not indicate a definitive causal direction between these variables. While the study is limited to the Croatian context and the specified period, its findings have significant implications for policymakers in Croatia and similar emerging markets. These results suggest that while financialisation can enhance economic growth through better resource allocation and increased investment, it may also pose risks such as financial instability. Such measures aim to mitigate the risks associated with financialisation while promoting sustainable economic growth. To address these challenges, we recommend the implementation of robust regulatory frameworks, financial literacy initiatives, and economic diversification strategies. Such measures aim to mitigate the risks associated with financialisation while promoting sustainable economic growth. The study fills an important research gap on financialisation in emerging markets, particularly in Croatia, providing empirical evidence on the long-term relationship between financialisation and economic growth and highlighting the need for context-specific policy interventions. Full article

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34 pages, 1327 KiB

Open AccessArticle

Determinants of South African Asset Market Co-Movement: Evidence from Investor Sentiment and Changing Market Conditions

by Fabian Moodley, Sune Ferreira-Schenk and Kago Matlhaku

Risks 2025, 13(1), 14; https://doi.org/10.3390/risks13010014 - 16 Jan 2025

Viewed by 396

Abstract

The co-movement of multi-asset markets in emerging markets has become an important determinant for investors seeking diversified portfolios and enhanced portfolio returns. Despite this, studies have failed to examine the determinants of the co-movement of multi-asset markets such as investor sentiment and changing [...] Read more.

The co-movement of multi-asset markets in emerging markets has become an important determinant for investors seeking diversified portfolios and enhanced portfolio returns. Despite this, studies have failed to examine the determinants of the co-movement of multi-asset markets such as investor sentiment and changing market conditions. Accordingly, this study investigates the effect of investor sentiment on the co-movement of South African multi-asset markets by introducing alternating market conditions. The Markov regime-switching autoregressive (MS-AR) model and Markov regime-switching vector autoregressive (MS-VAR) model impulse response function are used from 2007 March to January 2024. The findings indicate that investor sentiment has a time-varying and regime-specific effect on the co-movement of South African multi-asset markets. In a bull market condition, investor sentiment positively affects the equity–bond and equity–gold co-movement. In the bear market condition, investor sentiment has a negative and significant effect on the equity–bond, equity–property, bond–gold, and bond–property co-movement. Similarly, in a bull regime, the co-movement of South African multi-asset markets positively responds to sentiment shocks, although this is only observed in the short term. However, in the bear market regime, the co-movement of South African multi-asset markets responds positively and negatively to sentiment shocks, despite this being observed in the long run. These observations provide interesting insights to policymakers, investors, and fund managers for portfolio diversification and risk management strategies. That being, the current policies are not robust enough to reduce asset market integration and reduce sentiment-induced markets. Consequently, policymakers must re-examine and amend current policies according to the findings of the study. In addition, portfolio rebalancing in line with the findings of this study is essential for portfolio diversification. Full article

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

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18 pages, 4380 KiB

Open AccessFeature PaperArticle

Gaussian Process Regression with a Hybrid Risk Measure for Dynamic Risk Management in the Electricity Market

by Abhinav Das and Stephan Schlüter

Risks 2025, 13(1), 13; https://doi.org/10.3390/risks13010013 - 16 Jan 2025

Viewed by 399

Abstract

In this work, we introduce an innovative approach to managing electricity costs within Germany’s evolving energy market, where dynamic tariffs are becoming increasingly normal. In line with recent German governmental policies, particularly the Energiewende (Energy Transition) and European Union directives on clean energy, [...] Read more.

In this work, we introduce an innovative approach to managing electricity costs within Germany’s evolving energy market, where dynamic tariffs are becoming increasingly normal. In line with recent German governmental policies, particularly the Energiewende (Energy Transition) and European Union directives on clean energy, this work introduces a risk management strategy based on a combination of the well-known risk measures of the Value at Risk (VaR) and Conditional Value at Risk (CVaR). The goal is to optimize electricity procurement by forecasting hourly prices over a certain horizon and allocating a fixed budget using the aforementioned measures to minimize the financial risk. To generate price predictions, a Gaussian process regression model is used. The aim of this hybrid approach is to design a model that is easily understandable but allows for a comprehensive evaluation of potential financial exposure. It enables consumers to adjust their consumption patterns or market traders to invest and allows more cost-effective and risk-aware decision-making. The potential of our approach is shown in a case study based on the German market. Moreover, by discussing the political and economical implications, we show how the implementation of our method can contribute to the realization of a sustainable, flexible, and efficient energy market, as outlined in Germany’s Renewable Energy Act. Full article

(This article belongs to the Special Issue Financial Derivatives and Hedging in Energy Markets)

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15 pages, 370 KiB

Open AccessFeature PaperArticle

Are Women More Risk Averse? A Sequel

by Christos I. Giannikos and Efstathia D. Korkou

Risks 2025, 13(1), 12; https://doi.org/10.3390/risks13010012 - 15 Jan 2025

Viewed by 424

Abstract

This paper reexamines the question of gender differences in financial relative risk aversion using updated methods and data. Specifically, the paper revisits the 1998 work “Are women more risk averse?” by Jianakoplos and Bernasek, suggests refinements in their model in relation to the [...] Read more.

This paper reexamines the question of gender differences in financial relative risk aversion using updated methods and data. Specifically, the paper revisits the 1998 work “Are women more risk averse?” by Jianakoplos and Bernasek, suggests refinements in their model in relation to the database used, namely the U.S. Federal Reserve Board’s Survey of Consumer Finances (SCF), and performs new tests on the latest SCF from 2022. The suggested refinements pertain first to an enhanced computation of wealth, which includes additional categories of assets such as 401(k)s or other thrift savings accounts, and second to the more subtle handling and consideration of specific demographic data of the SCF respondents. Unlike the original study, which also included married couples, the new study focuses exclusively on single-headed (never-married) households. This eliminates ambiguity about the actual financial decision maker in households, enabling a clearer assessment of individual gendered behavior. Following the refinements, the new tests reveal a continuing pattern of decreasing relative risk aversion; however, contrary to the 1998 findings, there is no significant gender difference in financial relative risk aversion in 2022. This study also documents that education levels strongly influence risk-taking: single women with higher education levels are more likely to hold risky assets, while for men, higher education correlates with less risk-taking. The paper concludes by informing policymakers and financial educators so as to further tailor their strategies for promoting gender equality in financial decision-making. Full article

22 pages, 482 KiB

Open AccessArticle

Board Gender Diversity and Risk Management in Corporate Financing: A Study on Debt Structure and Financial Decision-Making

by Davood Askarany, Soleil Jafari, Azam Pouryousof, Sona Habibi and Hassan Yazdifar

Risks 2025, 13(1), 11; https://doi.org/10.3390/risks13010011 - 13 Jan 2025

Viewed by 491

Abstract

Purpose: This study examines the role of board gender diversity in shaping corporate financial decisions, particularly in terms of debt structure and risk management. Focusing on the Tehran Stock Exchange, it explores how female representation on boards influences long-term and short-term leverage decisions, [...] Read more.

Purpose: This study examines the role of board gender diversity in shaping corporate financial decisions, particularly in terms of debt structure and risk management. Focusing on the Tehran Stock Exchange, it explores how female representation on boards influences long-term and short-term leverage decisions, focusing on the moderating effect of board compensation. Design/Methodology: Utilising a quantitative ex post facto design, the study analyses data from 114 companies listed on the Tehran Stock Exchange between 2017 and 2021. Multivariate regression techniques, including year- and industry-fixed effects, are employed to investigate the relationship between board gender diversity, debt structure, and risk-taking behaviour. Findings: The results reveal a significant negative relationship between female board representation and long-term debt, suggesting that companies with more female directors tend to adopt more conservative debt structures, thereby reducing risk. Additionally, the findings demonstrate that board compensation moderates this relationship by curbing managerial risk-taking, further improving financial decision-making. Originality/Value: This research provides novel insights into the intersection of board gender diversity and risk management in financial decision-making, particularly in the context of a developing economy like Iran. It also offers practical implications for firms seeking to optimise their debt structures while maintaining sound risk management practices. Full article

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

21 pages, 4282 KiB

Open AccessFeature PaperArticle

Using Futures Prices and Analysts’ Forecasts to Estimate Agricultural Commodity Risk Premiums

by Gonzalo Cortazar, Hector Ortega and José Antonio Pérez

Risks 2025, 13(1), 9; https://doi.org/10.3390/risks13010009 - 10 Jan 2025

Viewed by 490

Abstract

This paper presents a novel 5-factor model for agricultural commodity risk premiums, an approach not explored in previous research. The model is applied to the specific cases of corn, soybeans, and wheat. Calibration is achieved using a Kalman filter and maximum likelihood, with [...] Read more.

This paper presents a novel 5-factor model for agricultural commodity risk premiums, an approach not explored in previous research. The model is applied to the specific cases of corn, soybeans, and wheat. Calibration is achieved using a Kalman filter and maximum likelihood, with data from futures markets and analysts’ forecasts. Risk premiums are computed by comparing expected and futures prices. The model considers that risk premiums are not solely determined by contract maturity but also by the marketing crop years. These crop years, in turn, are influenced by the respective harvest periods, a crucial factor in the agricultural commodity market. Results show that risk premiums vary across commodities, with some exhibiting positive and others negative values. While maturity affects risk premiums’ size, sign, and shape, the crop year plays a critical role, especially in the case of wheat. As speculators in the financial markets demand a positive risk premium, its sign provides insights into whether they are buyers or sellers of futures for each crop year, maturity, and commodity. This research offers valuable insights into grain price behavior, highlighting their similarities and differences. These findings have significant practical implications for market participants seeking to refine their trading and risk management strategies and for future research on the industry structure for each crop. Moreover, this enhanced understanding of risk premiums can be directly applied in the finance and agricultural industries, improving decision-making processes. Full article

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

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24 pages, 431 KiB

Open AccessArticle

Corporate Social Responsibility, Efficiency, and Risk in US Banking

by Fathi Jouini, Mohamed Amine Chouchen and Ahlem Selma Messai

Risks 2025, 13(1), 10; https://doi.org/10.3390/risks13010010 - 10 Jan 2025

Viewed by 483

Abstract

Banks have faced increasing attention regarding their ability to balance Corporate Social Responsibility (CSR) initiatives, operational efficiency, and credit risk management, particularly in the wake of global financial challenges. This study examines the interplay between CSR, efficiency, and credit risk in 131 US [...] Read more.

Banks have faced increasing attention regarding their ability to balance Corporate Social Responsibility (CSR) initiatives, operational efficiency, and credit risk management, particularly in the wake of global financial challenges. This study examines the interplay between CSR, efficiency, and credit risk in 131 US banks from 2010 to 2018. Using the Choquet integral, two-step Data Envelopment Analysis, and a dynamic panel with the Generalized Method of Moments, the findings reveal a virtuous circle between CSR and credit risk, where CSR enhances credit risk profiles. Similarly, efficiency and risk exhibit mutual reinforcement. However, a vicious circle is identified between CSR and efficiency, indicating trade-offs between CSR objectives and operational efficiency. These insights guide policymakers and bank managers in optimizing this balance. Full article

23 pages, 423 KiB

Open AccessArticle

The Impact of Hyperbolic Discounting on Asset Accumulation for Later Life: A Study of Active Investors Aged 65 Years and over in Japan

by Honoka Nabeshima, Sumeet Lal, Haruka Izumi, Yuzuha Himeno, Mostafa Saidur Rahim Khan and Yoshihiko Kadoya

Risks 2025, 13(1), 8; https://doi.org/10.3390/risks13010008 - 5 Jan 2025

Viewed by 756

Abstract

Asset accumulation in later life is a pressing issue in Japan due to the growing gap between life expectancy (87.14 years for women, 81.09 years for men in 2023) and the retirement age (65 or less). This gap heightens financial insecurity, emphasizing the [...] Read more.

Asset accumulation in later life is a pressing issue in Japan due to the growing gap between life expectancy (87.14 years for women, 81.09 years for men in 2023) and the retirement age (65 or less). This gap heightens financial insecurity, emphasizing the need to meet asset goals by 65. Hyperbolic discounting, driven by present-biased preferences, often hinders this process, but empirical evidence for those aged 65 and older remains limited. Moreover, prior research has overlooked the varying impacts of hyperbolic discounting across different wealth levels. This study addresses these gaps by analyzing data from 6709 active Japanese investors aged over 65 (2023 wave) using probit regression. Wealth thresholds are categorized into four levels: JPY 20 million, JPY 30 million, JPY 50 million, and JPY 100 million. The results show that hyperbolic discounting significantly impairs asset accumulation at the JPY 100 million level but not at lower thresholds. This effect likely reflects the complex nature of hyperbolic discounting, which primarily affects long-term savings and investments. The findings underscore the importance of addressing hyperbolic discounting in later-life financial planning. Recommendations include implementing automatic savings plans, enhancing financial literacy, and incorporating behavioral insights into planning tools to support better asset accumulation outcomes. Full article

20 pages, 598 KiB

Open AccessArticle

Empirical Evidence of the Market Price of Risk for Delivery Periods

by Annika Kemper and Maren Diane Schmeck

Risks 2025, 13(1), 7; https://doi.org/10.3390/risks13010007 - 3 Jan 2025

Viewed by 491

Abstract

In this paper, we provide empirical evidence of the market price of risk for delivery periods (MPDP) of electricity swap contracts. The MPDP enables an accurate pricing of such contracts in the presence of the delivery period such that the typical approximations can [...] Read more.

In this paper, we provide empirical evidence of the market price of risk for delivery periods (MPDP) of electricity swap contracts. The MPDP enables an accurate pricing of such contracts in the presence of the delivery period such that the typical approximations can be avoided. In our empirical study, we focus on term-structure effects and identify the resulting MPDP. In presence of the Samuelson effect, we find the most pronounced MPDP close to maturity, while the MPDP disappears proportional to the Samuelson effect far away from maturity. Thus, our theory improves the pricing accuracy close to maturity. Full article

(This article belongs to the Special Issue Financial Derivatives and Hedging in Energy Markets)

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25 pages, 467 KiB

Open AccessArticle

Earnings Quality Drivers: Do Firm Attributes and Ownership Structure Matter in Emerging Stock Markets?

by Fahad Alrobai, Ahmed A. Alrashed and Maged M. Albaz

Risks 2025, 13(1), 6; https://doi.org/10.3390/risks13010006 - 3 Jan 2025

Viewed by 500

Abstract

This research aims to examine the drivers of earnings quality (EQ) in emerging stock markets. By testing the impact of firm attributes and ownership structures on the level of earnings quality. The research followed a mixed-method approach (qualitative and quantitative) and was conducted [...] Read more.

This research aims to examine the drivers of earnings quality (EQ) in emerging stock markets. By testing the impact of firm attributes and ownership structures on the level of earnings quality. The research followed a mixed-method approach (qualitative and quantitative) and was conducted based on a sample of 75 listed firms in Egypt as an emerging market from 2015 to 2022. The results of the research found that each firm attribute has a mixed impact on earning quality, such as firm size (positive on persistence and no impact on consistency) and ROA (U-shape on persistence and consistency). In addition, ownership structures uniquely and dynamically impact earnings, following positive, U-shape, and N-shape. This research sheds light on the drivers of the earnings quality (firm attributes and ownership structures) in the Egyptian-listed firms and helps policymakers implement appropriate corporate governance mechanisms. Our findings in Egypt can motivate future research to further investigate the most relevant factors that explain variations in earning persistence and consistency as a dimension of financial reporting quality in other emerging markets. Full article

22 pages, 470 KiB

Open AccessArticle

Dividend-Based Labor Remuneration and Tradable Shares in Worker Cooperatives

by Ermanno C. Tortia

Risks 2025, 13(1), 5; https://doi.org/10.3390/risks13010005 - 31 Dec 2024

Viewed by 618

Abstract

This paper analyzes the possibility of creating worker cooperatives in which members are paid not through wages but through dividends calculated on the organization’s residual income, as stipulated by the economic theory of the labor-managed firm. It is shown how dividends paid to [...] Read more.

This paper analyzes the possibility of creating worker cooperatives in which members are paid not through wages but through dividends calculated on the organization’s residual income, as stipulated by the economic theory of the labor-managed firm. It is shown how dividends paid to members can be linked to the value of their financial participation in the capital of the cooperative. In the presence of a financial market, cooperative shares would be issued and allocated to both members and non-member outside investors, thus addressing the problem of the under-capitalization of worker cooperatives. It is hypothesized that the strong financial incentives of this type of capital structure, together with involvement in the democratic governance of the cooperative, peer pressure, and other horizontal monitoring mechanisms, would support members’ intrinsic motivation to work and help overcome the problem of free-riding in the labor process. Flexible economic and financial structure in the absence of fixed wages would promote job stability, as already observed in existing worker cooperatives. Full article

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

27 pages, 905 KiB

Open AccessArticle

Optimal Benefit Distribution of a Tontine-like Annuity Fund with Age-Structured Models

by Fan Zhang, Ping Chen and Xueyuan Wu

Risks 2025, 13(1), 4; https://doi.org/10.3390/risks13010004 - 30 Dec 2024

Viewed by 486

Abstract

This paper introduces a tontine-like annuity fund designed to provide lifelong income to its participants. Initially, each member contributes a lump-sum payment into a trust fund as a joining premium. Participants then receive benefits over time, based on their survival. As members pass [...] Read more.

This paper introduces a tontine-like annuity fund designed to provide lifelong income to its participants. Initially, each member contributes a lump-sum payment into a trust fund as a joining premium. Participants then receive benefits over time, based on their survival. As members pass away, their share of payouts is redistributed among the survivors, resulting in increased payouts for those remaining. Differing from traditional tontines, which assume a uniform mortality risk, this fund accommodates participants of various ages and allows new members to join during its operation. To accommodate these features, the authors utilize age-structured models (ASMs) to determine fair premiums for new entrants and to analyze the dynamics of benefit distribution. The core objective of this paper is to develop a pension model using ASMs, recognizing its significant potential for adaptation and expansion. The primary mathematical approach employed is the Maximum Principle from optimal control theory, which helps in deriving explicit solutions for the optimal subsidy strategy. Through numerical examples and detailed illustrations, the paper demonstrates that participants who remain in the cohort longer receive greater subsidies. Additionally, the study finds that adverse shocks lead to a smaller population and thus fewer subsidies. Conversely, starting with a larger initial cohort population tends to increase the overall population, resulting in more subsidies. However, higher costs associated with subsidies lead to their reduction. Our analysis reveals the complex interplay of factors influencing the sustainability and effectiveness of the proposed annuity model. Full article

(This article belongs to the Special Issue Applied Financial and Actuarial Risk Analytics)

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17 pages, 1923 KiB

Open AccessFeature PaperArticle

Characterization and Prediction of the Ghana Stock Exchange Composite Index Utilizing Bayesian Stochastic Volatility Models

by Osei K. Tweneboah, Kwesi A. Ohene-Obeng and Maria C. Mariani

Risks 2025, 13(1), 3; https://doi.org/10.3390/risks13010003 - 30 Dec 2024

Viewed by 664

Abstract

This study delves into the dynamics of the Ghana Stock Exchange Composite Index (GSE-CI) over the period from 2011 to 2022, a symbolic emerging market index that presents unique challenges and opportunities for financial analysis. We characterize the GSE-CI using advanced analytical tools [...] Read more.

This study delves into the dynamics of the Ghana Stock Exchange Composite Index (GSE-CI) over the period from 2011 to 2022, a symbolic emerging market index that presents unique challenges and opportunities for financial analysis. We characterize the GSE-CI using advanced analytical tools such as the Hurst exponent and R/S analysis to uncover its fractal properties and complex dynamics. The paper then advances to predictive modeling, employing an innovative approach with four variations of Stochastic Volatility (SV) models: SV with linear regressors, SV with Student’s t errors, SV with leverage effects, and a hybrid model combining Student’s t errors with leverage. Each model offers a unique perspective on forecasting the behavior of the GSE-CI, with the SV model incorporating Student’s t errors emerging as the most effective, as evidenced by the lowest Root Mean Square Error (RMSE) in our comparative evaluation. The integration of these models highlights their robustness in capturing the intricate volatility patterns of the GSE-CI, making a compelling case for their applicability to similar financial markets in other emerging economies. This research also paves the way for future investigations into other market indices and assets within and beyond the borders of emerging markets. Full article

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20 pages, 443 KiB

Open AccessFeature PaperArticle

Profitability Drivers in European Banks: Analyzing Internal and External Factors in the Post-2009 Financial Landscape

by Suzana Laporšek, Barbara Švagan, Mojca Stubelj and Igor Stubelj

Risks 2025, 13(1), 2; https://doi.org/10.3390/risks13010002 - 28 Dec 2024

Viewed by 565

Abstract

The paper examines the key determinants of European banks’ profitability by analyzing the return on assets (ROA), return on equity (ROE), net interest margin (NIM), and the risk-adjusted measures of profitability, RAROAA and RAROAE, across 34 European countries during the period from 2013 [...] Read more.

The paper examines the key determinants of European banks’ profitability by analyzing the return on assets (ROA), return on equity (ROE), net interest margin (NIM), and the risk-adjusted measures of profitability, RAROAA and RAROAE, across 34 European countries during the period from 2013 to 2018—a time characterized by economic recovery and significant regulatory reforms, including the implementation of Basel III standards. Using the Generalized Method of Moments (GMM) approach and data of 3076 European banks, the research addresses the complex interplay between internal (bank-specific) factors and external factors, including macroeconomic and industry-specific factors. The results show that profitability is positively associated with a higher capital adequacy, liquidity risk, and income diversification, but not for risk-adjusted profitability ratios. Credit risk, management efficiency, and excessive size have a negative effect on all studied profitability measures. Macroeconomic conditions, in particular, GDP growth and inflation, also have a significant impact on profitability. The findings offer valuable insights for policymakers, regulators, and financial institutions aiming to enhance profitability while maintaining the stability of the European banking sector. Full article

(This article belongs to the Special Issue Portfolio Theory, Financial Risk Analysis and Applications)

27 pages, 999 KiB

Open AccessArticle

Measuring the Impacts of Argentina’s Presidential Election Process in 2023 on the Stock Market Performance Using a Dynamic Event Study Methodology

by Eduardo Enrique Sandoval Álamos, Claudio René Molina Mac-Kay and Erwin Octavio Taipe Aquino

Risks 2025, 13(1), 1; https://doi.org/10.3390/risks13010001 - 27 Dec 2024

Viewed by 511

Abstract

This study measured the individual and conjoint effects of Argentina’s primaries and first- and second-voting presidential election results, as well as their post-election comparative effects, on the stock market performance of its most relevant economic sectors. Within four different estimation methods, the state-space [...] Read more.

This study measured the individual and conjoint effects of Argentina’s primaries and first- and second-voting presidential election results, as well as their post-election comparative effects, on the stock market performance of its most relevant economic sectors. Within four different estimation methods, the state-space specification outperformed the rest. The findings suggest that investors can under/overreact compared to post-election sectors performance, the public services sector being the exception. Therefore, those investors who anticipated the election results by liquidating positions in companies in the materials sector and investing more in companies in the energy and other industrial sectors achieved a superior performance. Full article

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Risks, Volume 13, Issue 1 (January 2025) – 18 articles

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