RisksPub Date : 2024-02-18DOI: 10.3390/risks12020040
Shengkun Xie, Yuanshun Li
{"title":"Analyzing Size of Loss Frequency Distribution Patterns: Uncovering the Impact of the COVID-19 Pandemic","authors":"Shengkun Xie, Yuanshun Li","doi":"10.3390/risks12020040","DOIUrl":"https://doi.org/10.3390/risks12020040","url":null,"abstract":"This study delves into a critical examination of the Size of Loss distribution patterns in the context of auto insurance during pre- and post-pandemics, emphasizing their profound influence on insurance pricing and regulatory frameworks. Through a comprehensive analysis of the historical Size of Loss data, insurers and regulators gain essential insights into the probabilities and magnitudes of insurance claims, informing the determination of precise insurance premiums and the management of case reserving. This approach aids in fostering fair competition, ensuring equitable premium rates, and preventing discriminatory pricing practices, thereby promoting a balanced insurance landscape. The research further investigates the impact of the COVID-19 pandemic on these Size of Loss patterns, given the substantial shifts in driving behaviours and risk landscapes. Also, the research contributes to the literature by addressing the need for more studies focusing on the implications of the COVID-19 pandemic on pre- and post-pandemic auto insurance loss patterns, thus offering a holistic perspective encompassing both insurance pricing and regulatory dimensions.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"254 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139902825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RisksPub Date : 2024-02-18DOI: 10.3390/risks12020039
Giuseppe Campolieti, Arash Fahim, Dan Pirjol, Harvey Stein, Tai-Ho Wang, Lingjiong Zhu
{"title":"In Memory of Peter Carr (1958–2022)","authors":"Giuseppe Campolieti, Arash Fahim, Dan Pirjol, Harvey Stein, Tai-Ho Wang, Lingjiong Zhu","doi":"10.3390/risks12020039","DOIUrl":"https://doi.org/10.3390/risks12020039","url":null,"abstract":"The editors of this special issue and several of the contributing authors have known Peter for a long time. We thought that the special issue will be enriched by adding a few personal notes and recollections about our interactions with Peter.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"6 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139902606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RisksPub Date : 2024-02-13DOI: 10.3390/risks12020037
Cong Nie, Xiaoming Liu, Serge B. Provost
{"title":"An Objective Measure of Distributional Estimability as Applied to the Phase-Type Aging Model","authors":"Cong Nie, Xiaoming Liu, Serge B. Provost","doi":"10.3390/risks12020037","DOIUrl":"https://doi.org/10.3390/risks12020037","url":null,"abstract":"The phase-type aging model (PTAM) is a class of Coxian-type Markovian models that can provide a quantitative description of the effects of various aging characteristics. Owing to the unique structure of the PTAM, parametric inference on the model is affected by a significant estimability issue, its profile likelihood functions being flat. While existing methods for assessing distributional non-estimability require the subjective specification of thresholds, this paper objectively quantifies estimability in the context of general statistical models. More specifically, this is achieved via a carefully designed cumulative distribution function sensitivity measure, under which the threshold is tailored to the empirical cumulative distribution function, thus becoming an experiment-based quantity. The proposed definition, which is validated to be innately sound, is then employed to determine and enhance the estimability of the PTAM.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"94 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139754129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RisksPub Date : 2024-02-13DOI: 10.3390/risks12020038
Dong-Hwa Lee, Joo-Ho Sung
{"title":"Dynamic Liability-Driven Investment under Sponsor’s Loss Aversion","authors":"Dong-Hwa Lee, Joo-Ho Sung","doi":"10.3390/risks12020038","DOIUrl":"https://doi.org/10.3390/risks12020038","url":null,"abstract":"This paper investigates a dynamic liability-driven investment policy for defined-benefit (DB) plans by incorporating the loss aversion of a sponsor, who is assumed to be more sensitive to underfunding than overfunding. Through the lens of prospect theory, we first set up a loss-aversion utility function for a sponsor whose utility depends on the funding ratio in each period, obtained from stochastic processes of pension assets and liabilities. We then construct a multi-horizon dynamic control optimization problem to find the optimal investment strategy that maximizes the expected utility of the plan sponsor. A genetic algorithm is employed to provide a numerical solution for our nonlinear dynamic optimization problem. Our results suggest that the overall paths of the optimal equity allocation decline as the age of a plan participant reaches retirement. We also find that the equity portion of the portfolio increases when a sponsor is less loss-averse or the contribution rate is lower.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"41 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139754070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RisksPub Date : 2024-02-08DOI: 10.3390/risks12020036
Ionuț Nica, Ștefan Ionescu, Camelia Delcea, Nora Chiriță
{"title":"Quantitative Modeling of Financial Contagion: Unraveling Market Dynamics and Bubble Detection Mechanisms","authors":"Ionuț Nica, Ștefan Ionescu, Camelia Delcea, Nora Chiriță","doi":"10.3390/risks12020036","DOIUrl":"https://doi.org/10.3390/risks12020036","url":null,"abstract":"This study explored the complex interplay and potential risk of financial contagion across major financial indices, focusing on the Bucharest Exchange Trading Investment Funds Index (BET-FI), along with global indices like the S&P 500, Nasdaq Composite (IXIC), and Dow Jones Industrial Average (DJIA). Our analysis covered an extensive period from 2012 to 2023, with a particular emphasis on Romania’s financial market. We employed Autoregressive Distributed Lag (ARDL) modeling to examine the interrelations among these indices, treating the BET-FI index as our primary variable. Our research also integrated Exponential Curve Fitting (EXCF) and Generalized Supremum Augmented Dickey–Fuller (GSADF) models to identify and scrutinize potential price bubbles in these indices. We analyzed moments of high volatility and deviations from typical market trends, influenced by diverse factors like government policies, presidential elections, tech sector performance, the COVID-19 pandemic, and geopolitical tensions, specifically the Russia–Ukraine conflict. The ARDL model revealed a stable long-term relationship among the variables, indicating their interconnectedness. Our study also highlights the significance of short-term market shifts leading to long-term equilibrium, as shown in the Error Correction Model (ECM). This suggests the existence of contagion effects, where small, short-term incidents can trigger long-term, domino-like impacts on the financial markets. Furthermore, our variance decomposition examined the evolving contributions of different factors over time, shedding light on their changing interactions and impact. The Cholesky factors demonstrated the interdependence between indices, essential for understanding financial contagion effects. Our research thus uncovered the nuanced dynamics of financial contagion, offering insights into market variations, the effectiveness of our models, and strategies for detecting financial bubbles. This study contributes valuable knowledge to the academic field and offers practical insights for investors in turbulent financial environments.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"29 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139754125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RisksPub Date : 2024-02-05DOI: 10.3390/risks12020033
Marcos Escobar-Anel, Yiyao Jiao
{"title":"Robust Portfolio Optimization with Environmental, Social, and Corporate Governance Preference","authors":"Marcos Escobar-Anel, Yiyao Jiao","doi":"10.3390/risks12020033","DOIUrl":"https://doi.org/10.3390/risks12020033","url":null,"abstract":"This study addresses the crucial but under-explored topic of ambiguity aversion, i.e., model misspecification, in the area of environmental, social, and corporate governance (ESG) within portfolio decisions. It considers a risk- and ambiguity-averse investor allocating resources to a risk-free asset, a market index, a green stock, and a brown stock. The study employs a robust control approach rooted in relative entropy to account for model misspecification and derive closed-form optimal investment strategies. The key contribution of this study includes demonstrating, using two sets of empirical data on asset returns and ESG ratings, the substantial influence of ambiguity on optimal trading strategies, particularly highlighting the differential effects of market, green, and brown ambiguities. As a by-product of our analytical solutions, the study contrasts ambiguity-averse investors with their non-ambiguity counterparts, revealing more cautious risk exposures with a reduction in short-selling positions for the former. Furthermore, three types of investors who employ popular suboptimal strategies are identified, together with two loss measures used to quantify their performance. The findings reveal that popular strategies, not accounting for ESG and misspecification in the model, could lead to significant financial costs, with the extent of loss varying depending on those two factors: investors’ ambiguity aversion profiles and ESG preferences.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"12 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139754272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RisksPub Date : 2024-02-04DOI: 10.3390/risks12020034
Sijie Yao, Hui Zou, Haipeng Xing
{"title":"L1 Regularization for High-Dimensional Multivariate GARCH Models","authors":"Sijie Yao, Hui Zou, Haipeng Xing","doi":"10.3390/risks12020034","DOIUrl":"https://doi.org/10.3390/risks12020034","url":null,"abstract":"The complexity of estimating multivariate GARCH models increases significantly with the increase in the number of asset series. To address this issue, we propose a general regularization framework for high-dimensional GARCH models with BEKK representations, and obtain a penalized quasi-maximum likelihood (PQML) estimator. Under some regularity conditions, we establish some theoretical properties, such as the sparsity and the consistency, of the PQML estimator for the BEKK representations. We then carry out simulation studies to show the performance of the proposed inference framework and the procedure for selecting tuning parameters. In addition, we apply the proposed framework to analyze volatility spillover and portfolio optimization problems, using daily prices of 18 U.S. stocks from January 2016 to January 2018, and show that the proposed framework outperforms some benchmark models.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"16 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139680199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RisksPub Date : 2024-02-03DOI: 10.3390/risks12020032
José Sequeira, Cláudia Pereira, Luís Gomes, Armindo Lima
{"title":"Features of the Association between Debt and Earnings Quality for Small and Medium-Sized Entities","authors":"José Sequeira, Cláudia Pereira, Luís Gomes, Armindo Lima","doi":"10.3390/risks12020032","DOIUrl":"https://doi.org/10.3390/risks12020032","url":null,"abstract":"The main source of financing is bank loans for Portuguese small and medium-sized entities (SMEs), which implies several constraints to obtaining additional funds. Relying on the argument of Positive Accounting Theory (PAT) that accounting choices are not neutral and on Agency Theory that information asymmetry prevails between insiders and outsiders, we analyzed the impacts of debt on earnings quality, focusing on its level, its increases, and its term of payment. We estimated econometric regressions using panel data with fixed effects over 2013–2019, using discretionary accruals as an inverse proxy of earnings quality. We found empirical evidence that the relationship between debt and earnings quality tends to vary in sign, as the quality of financial information deteriorates with debt, but as debt becomes high, firms tend to increase the quality of earnings. Furthermore, we found that short-term debt tends to decrease earnings quality more than long-term debt. This article aimed to contribute to the prior literature by collecting evidence that debt levels tend to be an incentive to increase earnings management and fill the gap by analyzing the influence of different debt features. This evidence is useful because earnings management may compromise both stakeholders’ confidence and the efficient allocation of capital.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"4 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139680335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RisksPub Date : 2024-02-03DOI: 10.3390/risks12020031
Hao Wang, Anthony Bellotti, Rong Qu, Ruibin Bai
{"title":"Discrete-Time Survival Models with Neural Networks for Age–Period–Cohort Analysis of Credit Risk","authors":"Hao Wang, Anthony Bellotti, Rong Qu, Ruibin Bai","doi":"10.3390/risks12020031","DOIUrl":"https://doi.org/10.3390/risks12020031","url":null,"abstract":"Survival models have become popular for credit risk estimation. Most current credit risk survival models use an underlying linear model. This is beneficial in terms of interpretability but is restrictive for real-life applications since it cannot discover hidden nonlinearities and interactions within the data. This study uses discrete-time survival models with embedded neural networks as estimators of time to default. This provides flexibility to express nonlinearities and interactions between variables and hence allows for models with better overall model fit. Additionally, the neural networks are used to estimate age–period–cohort (APC) models so that default risk can be decomposed into time components for loan age (maturity), origination (vintage), and environment (e.g., economic, operational, and social effects). These can be built as general models or as local APC models for specific customer segments. The local APC models reveal special conditions for different customer groups. The corresponding APC identification problem is solved by a combination of regularization and fitting the decomposed environment time risk component to macroeconomic data since the environmental risk is expected to have a strong relationship with macroeconomic conditions. Our approach is shown to be effective when tested on a large publicly available US mortgage dataset. This novel framework can be adapted by practitioners in the financial industry to improve modeling, estimation, and assessment of credit risk.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"3 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139754508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RisksPub Date : 2024-02-03DOI: 10.3390/risks12020030
Péter Szálteleki, Gabriella Bánhegyi, Zsuzsanna Bacsi
{"title":"The Impacts of CAP Subsidies on the Financial Risk and Resilience of Hungarian Farms, 2014–2021","authors":"Péter Szálteleki, Gabriella Bánhegyi, Zsuzsanna Bacsi","doi":"10.3390/risks12020030","DOIUrl":"https://doi.org/10.3390/risks12020030","url":null,"abstract":"The present paper empirically analyzes the efficiency of European Union (EU) subsidies for farms in the Southern Great Plain region of Hungary between 2014 and 2021. The aim of this analysis was to explore whether the subsidies increased the resilience of farms, enhancing their profitability, liquidity and solvency, and economic efficiency, measured by the usual financial indicators of farm performance. The analysis also evaluated the ability of farm businesses to create and retain jobs, i.e., to increase employment in the rural environment, focusing on differences between the subsidized and non-subsidized farms. The research analyzed all agricultural companies of the selected region. The methodology was a non-parametric statistical analysis (Kruskal–Wallis test, Dunnett’s T3 test) for identifying significant differences between subsidized and non-subsidized farms in the 8-year period. Results show that subsidies significantly improved the financial stability, resilience and efficiency of subsidized farms only in the micro size category, and the employment indicators deteriorated more in subsidized farms than in non-subsidized ones. Thus, the intended purpose of the subsidies was not entirely realized, and positive impacts were noticeable only in the micro enterprises. This might imply that subsidies contributed to the survival of non-viable enterprises instead of enhancing their competitiveness.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"39 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139677427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}