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Coherent Diversification Measures in Portfolio Theory: An Axiomatic Foundation
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Pricing European Currency Options with High-Frequency Data
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A Combined Neural Network Approach for the Prediction of Admission Rates Related to Respiratory Diseases
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Construction of an SDE Model from Intraday Copper Futures Prices
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The Dynamic Connectedness between Risk and Return in the Fintech Market of India: Evidence Using the GARCH-M Approach
Journal Description
Risks
Risks
is an international, scholarly, peer-reviewed, open access journal for research and studies on insurance and financial risk management. Risks is published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High visibility: indexed within Scopus, ESCI (Web of Science), EconLit, EconBiz, RePEc, and other databases.
- Journal Rank: CiteScore - Q2 (Economics, Econometrics and Finance (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 22.2 days after submission; acceptance to publication is undertaken in 7.6 days (median values for papers published in this journal in the second half of 2022).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers for a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done
Latest Articles
Dependent Metaverse Risk Forecasts with Heteroskedastic Models and Ensemble Learning
Risks 2023, 11(2), 32; https://doi.org/10.3390/risks11020032 - 01 Feb 2023
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Metaverses have been evolving following the popularity of blockchain technology. They build their own cryptocurrencies for transactions inside their platforms. These new cryptocurrencies are, however, still highly speculative, volatile, and risky, motivating us to manage their risk. In this paper, we aimed to
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Metaverses have been evolving following the popularity of blockchain technology. They build their own cryptocurrencies for transactions inside their platforms. These new cryptocurrencies are, however, still highly speculative, volatile, and risky, motivating us to manage their risk. In this paper, we aimed to forecast the risk of Decentraland’s MANA and Theta Network’s THETA. More specifically, we constructed an aggregate of these metaverse cryptocurrencies as well as their combination with Bitcoin. To measure their risk, we proposed a modified aggregate risk measure (AggM) defined as a convex combination of aggregate value-at-risk (AggVaR) and aggregate expected shortfall (AggES). To capture their dependence, we employed copulas that link their marginal models: heteroskedastic and ensemble learning-based models. Our empirical study showed that the latter outperformed the former when forecasting volatility and aggregate risk measures. In particular, the AggM forecast was more accurate and more valid than the AggVaR and AggES forecasts. These risk measures confirmed that an aggregate of the two metaverse cryptocurrencies exhibited the highest risk with evidence of lower tail dependence. These results are, thus, helpful for cryptocurrency investors, portfolio risk managers, and policy-makers to formulate appropriate cryptocurrency investment strategies, portfolio allocation, and decision-making, particularly during extremely negative shocks.
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Open AccessArticle
Designing Stress Tests for UK Fast-Growing Firms and Fintech
Risks 2023, 11(2), 31; https://doi.org/10.3390/risks11020031 - 31 Jan 2023
Abstract
This paper captures advances in prudential regulation and supervision for challenger banks and fintech in the UK. It presents a critical analysis of the prudential supervisory approaches towards fintech. The focus is placed on fast-growing firms (FGFs), building on the review performed by
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This paper captures advances in prudential regulation and supervision for challenger banks and fintech in the UK. It presents a critical analysis of the prudential supervisory approaches towards fintech. The focus is placed on fast-growing firms (FGFs), building on the review performed by the Prudential Regulation Authority (PRA) of the Bank of England (BoE) in 2019. Specifically, it comprises a critical examination of the underlying regulatory framework in relation to the robustness of stress testing practices, as part of the review of FGF risk management practices and the weakness identified in the Internal Capital Adequacy Assessment Process (ICAAP). The economic analysis of law comprises the underlying methodology, using economic theory to analyse regulation and its effectiveness regarding fintech regulation and supervision. Recommendations for enhancements towards supervisory practices about the prudential governance and management of FGFs and fintech are included, with advances to the underlying regulatory framework in the UK. Overall, this critical legal research examines the supervisory practices of FGFs and fintech in the UK, under the lens of prudential regulation and risk management approaches, focusing on the design, development and implementation of the stress testing tool and scenario practices.
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(This article belongs to the Special Issue The Risk Landscape in the Digital Transformation of Finance and Insurance)
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Open AccessArticle
The SEV-SV Model—Applications in Portfolio Optimization
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Risks 2023, 11(2), 30; https://doi.org/10.3390/risks11020030 - 28 Jan 2023
Abstract
This paper introduces and studies a new family of diffusion models for stock prices with applications in portfolio optimization. The diffusion model combines (stochastic) elasticity of volatility (EV) and stochastic volatility (SV) to create the SEV-SV model. In particular, we focus on the
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This paper introduces and studies a new family of diffusion models for stock prices with applications in portfolio optimization. The diffusion model combines (stochastic) elasticity of volatility (EV) and stochastic volatility (SV) to create the SEV-SV model. In particular, we focus on the SEV component, which is driven by an Ornstein–Uhlenbeck process via two separate functional choices, while the SV component features the state-of-the-art 4/2 model. We study an investment problem within expected utility theory (EUT) for incomplete markets, producing closed-form representations for the optimal strategy, value function, and optimal wealth process for two different cases of prices of risk on the stock. We find that when EV reverts to a GBM model, the volatility and speed of reversion of the EV have a strong impact on optimal allocations, and more aggressive (bull markets) or cautious (bear markets) strategies are hence recommended. For a model when EV reverts away from GBM, only the mean reverting level of the EV plays a role. Moreover, the presence of SV leads mainly to more conservative investment decisions for short horizons. Overall, the SEV plays a more significant role than SV in the optimal allocation.
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(This article belongs to the Special Issue Stochastic Modelling in Financial Mathematics II)
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Open AccessArticle
Analysing Quantiles in Models of Forward Term Rates
Risks 2023, 11(2), 29; https://doi.org/10.3390/risks11020029 - 28 Jan 2023
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The class of forward-LIBOR market models can, under certain volatility structures, produce unrealistically high long-dated forward rates, particularly for maturities and tenors beyond the liquid market calibration instruments. This paper presents a diagnostic tool for analysing the quantiles of distributions for forward term
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The class of forward-LIBOR market models can, under certain volatility structures, produce unrealistically high long-dated forward rates, particularly for maturities and tenors beyond the liquid market calibration instruments. This paper presents a diagnostic tool for analysing the quantiles of distributions for forward term rates in a displaced lognormal forward-LIBOR model (DLFM). In particular, we provide a quantile approximation that can be used to assess whether the modelled term rates remain within realistic bounds with a high probability. Applying this diagnostic tool (verified using Quasi-Monte Carlo (QMC) simulations), we show that realised forward term rates for long time horizons may be kept within realistic limits by appropriately damping the tail of the DLFM volatility function.
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Open AccessArticle
Effect of Family Control on Earnings Management: The Role of Leverage
Risks 2023, 11(2), 28; https://doi.org/10.3390/risks11020028 - 25 Jan 2023
Abstract
This study aims to examine whether family control has a positive effect on earnings management of manufacturing companies and whether leverage weakens the positive effect of family control on earnings management. This study uses panel data for the 2015–2019 observation year. The research
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This study aims to examine whether family control has a positive effect on earnings management of manufacturing companies and whether leverage weakens the positive effect of family control on earnings management. This study uses panel data for the 2015–2019 observation year. The research population consists of companies listed on the Indonesian capital market. Sample selection was performed with a purposive sampling approach using certain criteria, namely: the company was not delisted during the observation period; the company has complete research data; and that the company is included in the criteria for family companies. The sample of the study consists of 84 companies with a total of 419 observations. We use panel data regression to prove our hypotheses. The findings of our research show that family control has a positive effect on earnings management and leverage weakens the positive effect of family control on earnings management. Additional tests confirm the main test. The implications of our research are expected to be input for determining regulations and policies related to restrictions on majority shareholders to protect minority shareholders.
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(This article belongs to the Special Issue Accounting, Financial Reporting, and Disclosure)
Open AccessArticle
Evaluating the Effectiveness of Modern Forecasting Models in Predicting Commodity Futures Prices in Volatile Economic Times
Risks 2023, 11(2), 27; https://doi.org/10.3390/risks11020027 - 22 Jan 2023
Abstract
The paper seeks to answer the question of how price forecasting can contribute to which techniques gives the most accurate results in the futures commodity market. A total of two families of models (decision trees, artificial intelligence) were used to produce estimates for
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The paper seeks to answer the question of how price forecasting can contribute to which techniques gives the most accurate results in the futures commodity market. A total of two families of models (decision trees, artificial intelligence) were used to produce estimates for 2018 and 2022 for 21- and 125-day periods. The main findings of the study are that in a calm economic environment, the estimation accuracy is higher (1.5% vs. 4%), and that the AI-based estimation methods provide the most accurate estimates for both time horizons. These models provide the most accurate forecasts over short and medium time periods. Incorporating these forecasts into the ERM can significantly help to hedge purchase prices. Artificial intelligence-based models are becoming increasingly widely available, and can achieve significantly better accuracy than other approximations.
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(This article belongs to the Special Issue New Advance of Risk Management Models)
Open AccessArticle
Perceived Risks of Autonomous Vehicles
Risks 2023, 11(2), 26; https://doi.org/10.3390/risks11020026 - 21 Jan 2023
Abstract
Whilst self-driving cars are not vehicles of the future, but technology that is already available, their acceptance and implementation is heavily limited. People consider them as technology that has a lot of risk—be it technological, IT related, or even ethical. The aim of
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Whilst self-driving cars are not vehicles of the future, but technology that is already available, their acceptance and implementation is heavily limited. People consider them as technology that has a lot of risk—be it technological, IT related, or even ethical. The aim of the present paper is to enrich the existing body of literature of risk perception—and in line with this technology adaption—regarding autonomous vehicles and how they are influenced by demographic and exogenous cultural variables. Whilst the effect of cultural variables on risk perception has already been explored by several researchers, the present paper shall be considered an expansion of those works, striving to address a particular segment of risk perception—the specifics of cultural influence on risk perception regarding autonomous vehicles. Whilst risk perception is of a multifaceted nature, the current paper does not aim to provide a comprehensive understanding of the complex phenomenon under scrutiny, but intends to highlight the potentiality of cultural influences besides the often-explored individual variables when it comes to risk perception and the consequent decisions and indicates that the cultural dimensions of Geert Hofstede use to create a better understanding of perceived risks related to self-driving cars.
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(This article belongs to the Special Issue New Advance of Risk Management Models)
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Open AccessEditorial
Acknowledgment to the Reviewers of Risks in 2022
Risks 2023, 11(2), 25; https://doi.org/10.3390/risks11020025 - 18 Jan 2023
Abstract
High-quality academic publishing is built on rigorous peer review [...]
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Open AccessOpinion
A Generalized Model for Pricing Financial Derivatives Consistent with Efficient Markets Hypothesis—A Refinement of the Black-Scholes Model
Risks 2023, 11(2), 24; https://doi.org/10.3390/risks11020024 - 17 Jan 2023
Abstract
This research article provides criticism and arguments why the canonical framework for derivatives pricing is incomplete and why the delta-hedging approach is not appropriate. An argument is put forward, based on the efficient market hypothesis, why a proper risk-adjusted discount rate should enter
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This research article provides criticism and arguments why the canonical framework for derivatives pricing is incomplete and why the delta-hedging approach is not appropriate. An argument is put forward, based on the efficient market hypothesis, why a proper risk-adjusted discount rate should enter into the Black-Scholes model instead of the risk-free rate. The resulting pricing equation for derivatives and, in particular, the formula for European call options is then shown to depend explicitly on the drift of the underlying asset, which is following a geometric Brownian motion. It is conjectured that with the generalized model, the predicted results by the model could be closer to real data. The adjusted pricing model could partly also explain the mystery of volatility smile. The present model also provides answers to many finance professionals and academics who have been intrigued by the risk-neutral features of the original Black-Scholes pricing framework. The model provides generally different fair values for financial derivatives compared to the Black-Scholes model. In particular, the present model predicts that the original Black-Scholes model tends to undervalue for example European call options.
Full article
(This article belongs to the Special Issue Frontiers in Quantitative Finance and Risk Management)
Open AccessArticle
Size-Threshold Effect in the Capital Structure–Firm Performance Nexus in the MENA Region: A Dynamic Panel Threshold Regression Model
Risks 2023, 11(2), 23; https://doi.org/10.3390/risks11020023 - 17 Jan 2023
Abstract
This paper investigates the nonlinear relationship between capital structure and firm performance in the MENA region using a sample of 499 listed firms over the 2007–2020 period, or 6986 firm-year observations. Specifically, we examine the size-threshold effect in the capital structure–firm performance nexus.
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This paper investigates the nonlinear relationship between capital structure and firm performance in the MENA region using a sample of 499 listed firms over the 2007–2020 period, or 6986 firm-year observations. Specifically, we examine the size-threshold effect in the capital structure–firm performance nexus. To do so, this study applies a dynamic panel threshold regression model (DPTR). The findings show that there is a nonlinear relationship between debt and firm performance (Tobin’s Q, ROA, and ROE). Specifically, the threshold values of firm size for the three models are estimated at 9.126 (about $1 million), 15.48 (about $5 million), and 16.816 (about $20 million), respectively, between the low- and the high-sized regimes. In the lower regime, the firm’s value (Q) increases when debt increases; however, in the higher regime, this value decreases when debt increases. Furthermore, in the lower regime, the performances (ROA and ROE) of small firms decrease when debt increases; however, in the upper regime, when debt increases, the performances of large firms increase. The results are several robustness tests. These results support the predictions of signal, pecking order, and trade-off theories. Managers of large (small) MENA firms should increase (decrease) the use of debt to improve performance.
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(This article belongs to the Special Issue Accounting, Financial Reporting, and Disclosure)
Open AccessArticle
The Effects of Direct Democracy on Stock Market Risk and Returns: An Event Study from Switzerland
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Risks 2023, 11(2), 22; https://doi.org/10.3390/risks11020022 - 17 Jan 2023
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The aim of this study was to determine whether referendums affect stock price risks and returns, using an event study approach. Daily end period data for the Swiss stock market index, the STOXX European market index, and the Swiss/US exchange rate running from
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The aim of this study was to determine whether referendums affect stock price risks and returns, using an event study approach. Daily end period data for the Swiss stock market index, the STOXX European market index, and the Swiss/US exchange rate running from the beginning of 2004 to June 2021, along with the EGARCH model, were applied to determine the effects on both the market’s return and volatility. The results suggest that the day after the referendum, there was little evidence of a positive effect on stock returns. However, using a longer window of three days before and after the referendum, there was evidence of a positive effect from the referendum on the market’s returns and a negative effect on its volatility. Analysing the effects of referendums on both asset returns and risks allows for a more comprehensive assessment of how they impact on the economy, with these results supporting previous studies that found a positive effect on economic returns, and also showing they can reduce risks.
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Open AccessArticle
Valuation of Equity-Linked Death Benefits on Two Lives with Dependence
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Risks 2023, 11(1), 21; https://doi.org/10.3390/risks11010021 - 12 Jan 2023
Abstract
The purpose of this paper is to investigate equity-linked death benefits for joint alive and last survivor individuals. Utilizing Farlie–Gumbel–Morgenstern (FGM) type dependency modeling framework, we first analyze the joint distribution of the couple (joint alive and last survival density) when marginal distributions
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The purpose of this paper is to investigate equity-linked death benefits for joint alive and last survivor individuals. Utilizing Farlie–Gumbel–Morgenstern (FGM) type dependency modeling framework, we first analyze the joint distribution of the couple (joint alive and last survival density) when marginal distributions follow mixed exponentials and weighted exponentials distributions. Then, we derive the price of the guaranteed minimum death benefit (GMDB) product. In addition, we provide closed analytical expressions of the price of some financial contingent claim contracts (classical and exotic options). Furthermore, we present some numerical results to support our theoretical results. We show in our numerical example that it is important to model the dependency between two lives (couple) since the price changes as the copula parameter changes.
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(This article belongs to the Special Issue New Advance of Risk Management Models)
Open AccessArticle
Adversarial Artificial Intelligence in Insurance: From an Example to Some Potential Remedies
Risks 2023, 11(1), 20; https://doi.org/10.3390/risks11010020 - 11 Jan 2023
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Artificial intelligence (AI) is a tool that financial intermediaries and insurance companies use or are willing to use in almost all their activities. AI can have a positive impact on almost all aspects of the insurance value chain: pricing, underwriting, marketing, claims management,
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Artificial intelligence (AI) is a tool that financial intermediaries and insurance companies use or are willing to use in almost all their activities. AI can have a positive impact on almost all aspects of the insurance value chain: pricing, underwriting, marketing, claims management, and after-sales services. While it is very important and useful, AI is not free of risks, including those related to its robustness against so-called adversarial attacks, which are conducted by external entities to misguide and defraud the AI algorithms. The paper is designed to review adversarial AI and to discuss its implications for the insurance sector. We give a taxonomy of adversarial attacks and present an original, fully fledged example of claims falsification in health insurance, as well as some remedies which are consistent with the current regulatory framework.
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Open AccessArticle
FAANG Stocks, Gold, and Islamic Equity: Implications for Portfolio Management during COVID-19
Risks 2023, 11(1), 19; https://doi.org/10.3390/risks11010019 - 11 Jan 2023
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During the COVID-19 pandemic, technology stocks, such as FAANG stocks (Facebook, Amazon, Apple, Netflix, and Google), attracted the attention of global investors due to the vast use of technology in daily business. However, technology stocks are generally considered risky stocks; hence, efficient risk
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During the COVID-19 pandemic, technology stocks, such as FAANG stocks (Facebook, Amazon, Apple, Netflix, and Google), attracted the attention of global investors due to the vast use of technology in daily business. However, technology stocks are generally considered risky stocks; hence, efficient risk management is required to construct an optimal portfolio. In this study, we investigate the volatility spillovers and dynamic conditional correlations among the daily returns of FAANG company stocks, gold, and sharia-compliant equity to construct the optimal portfolio weights and hedge ratios during the COVID-19 pandemic period by utilizing a multivariate GARCH framework. The dynamic conditional correlations reveal that both gold and sharia-compliant equities exhibit lower correlations with FAANG stocks during the COVID-19 pandemic, implying opportunities for portfolio diversification. The findings indicate that gold and shariah-compliant equity are good candidates to hedge FAANG stocks. These findings are highly relevant for international investors, asset managers, hedgers, and portfolio managers.
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Open AccessFeature PaperArticle
Dependence Modelling of Lifetimes in Egyptian Families
Risks 2023, 11(1), 18; https://doi.org/10.3390/risks11010018 - 11 Jan 2023
Abstract
In this study, we analyse a large sample of Egyptian social pension data which covers, by law, the policyholder’s spouse, children, parents and siblings. This data set uniquely enables the study and comparison of pairwise dependence between multiple familial relationships beyond the well-known
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In this study, we analyse a large sample of Egyptian social pension data which covers, by law, the policyholder’s spouse, children, parents and siblings. This data set uniquely enables the study and comparison of pairwise dependence between multiple familial relationships beyond the well-known husband and wife case. Applying Bayesian Markov Chain Monte Carlo (MCMC) estimation techniques with the two-step inference functions for margins (IFM) method, we model dependence between lifetimes in spousal, parent–child and child–parent relationships, using copulas to capture the strength of association. Dependence is observed to be strongest in child–parent relationships and, in comparison to the high-income countries of data sets previously studied, of lesser significance in the husband and wife case, often referred to as broken-heart syndrome. Given the traditional use of UK mortality tables in the modelling of mortality in Egypt, the findings of this paper will help to inform appropriate mortality assumptions specific to the unique structure of the Egyptian scheme.
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(This article belongs to the Special Issue Interplay between Financial and Actuarial Mathematics II)
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Open AccessArticle
Rational versus Irrational Behavior of Indonesian Cryptocurrency Owners in Making Investment Decision
Risks 2023, 11(1), 17; https://doi.org/10.3390/risks11010017 - 11 Jan 2023
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The purpose of this study is to investigate the salient factors that influence Indonesian cryptocurrency owners in making their investment decision. This study employs intergroup bias, subjective norms, overborrowing, and spending control to explain cryptocurrency investment behavior. The questionnaire was collected from 309
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The purpose of this study is to investigate the salient factors that influence Indonesian cryptocurrency owners in making their investment decision. This study employs intergroup bias, subjective norms, overborrowing, and spending control to explain cryptocurrency investment behavior. The questionnaire was collected from 309 respondents from the five largest internet user areas: Jakarta, Surabaya, Bandung, Semarang, and Medan. This study executes the research framework using binary logistic regression. The results reveal that intergroup bias and overborrowing are the most impulsive factors contributing to the cryptocurrency investment decisions over the past year. Furthermore, after November 2021, Indonesian crypto owners are more irrational in a bearish period since their investment decisions are driven by their desire to be accepted in the social group. Moreover, when they have overindebtedness, instead of solving their debt problems, they prefer to spend their money on cryptocurrency investments. The subjective norms’ influencers suggest that crypto owners not invest when the cryptocurrency price is sharply declining. The findings contribute to the dual-systems perspective and social contagion theories, enriching the empirical study regarding investment behavior.
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Open AccessArticle
Trade Credit Management and Profitability of Jordanian Manufacturing Firms
Risks 2023, 11(1), 16; https://doi.org/10.3390/risks11010016 - 10 Jan 2023
Abstract
The significant role of Small and Medium Enterprises (SMEs) in the growth of the economy has been well-documented in the past few decades. Studies in literature have focused on the reasons behind the trade credit offerings and acceptance of SMEs, but empirical findings
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The significant role of Small and Medium Enterprises (SMEs) in the growth of the economy has been well-documented in the past few decades. Studies in literature have focused on the reasons behind the trade credit offerings and acceptance of SMEs, but empirical findings revealing the positive relationship between trade credit itself and profitability is still limited. Thus, in this paper, the trade credit effect on the profitability of SMEs from the side of supply and demand is examined. The paper focused on 38 SMEs in Amman Stock Exchange (ASE) for the years from 2009 to 2021. The obtained findings showed a positive relationship between accounts payable and profitability, which indicates that SMEs should establish long-term relationships with their suppliers to maintain credit. However, no clear relationship was found between accounts receivable and profitability, represented by ROE and ROA. Furthermore, financial leverage and size were revealed to impact the profitability of SMEs.
Full article
Open AccessArticle
A Wavelet Analysis of the Dynamic Connectedness among Oil Prices, Green Bonds, and CO2 Emissions
Risks 2023, 11(1), 15; https://doi.org/10.3390/risks11010015 - 09 Jan 2023
Abstract
Wavelet power spectrum (WPS) and wavelet coherence analyses (WCA) are used to examine the co-movements among oil prices, green bonds, and CO2 emissions on daily data from January 2014 to October 2022. The WPS results show that oil returns exhibit significant volatility
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Wavelet power spectrum (WPS) and wavelet coherence analyses (WCA) are used to examine the co-movements among oil prices, green bonds, and CO2 emissions on daily data from January 2014 to October 2022. The WPS results show that oil returns exhibit significant volatility at low and medium frequencies, particularly in 2014, 2019–2020, and 2022. Also, the Green Bond Index presents significant volatility at the end of 2019–2020 and the beginning of 2022 at low, medium, and high frequencies. Additionally, CO2 futures’ returns present high volatility at low and medium frequencies, expressly in 2015–2016, 2018, the end of 2019–2020, and 2022. WCA’s empirical findings reveal (i) that oil returns have a negative impact on the Green Bond Index in the medium term. (ii) There is a strong interdependence between oil prices and CO2 futures’ returns, in short, medium, and long terms, as inferred from the time–frequency analysis. (iii) There also is evidence of strong short, medium, and long terms co-movements between the Green Bond Index and CO2 futures’ returns, with the Green Bond Index leading.
Full article
(This article belongs to the Special Issue Data Analysis and Financial Risk Management in Financial Markets)
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Open AccessArticle
Analysis of Yields and Their Determinants in the European Corporate Green Bond Market
Risks 2023, 11(1), 14; https://doi.org/10.3390/risks11010014 - 06 Jan 2023
Abstract
The green bond market helps to mobilize financial sources toward sustainable investments. Green bonds are similar to conventional bonds but are specifically designed to raise money to finance environmental projects. The feature of green bonds is the existence of greenium, or the lower
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The green bond market helps to mobilize financial sources toward sustainable investments. Green bonds are similar to conventional bonds but are specifically designed to raise money to finance environmental projects. The feature of green bonds is the existence of greenium, or the lower yield compared to “conventional” bonds of the same risk. The relevance of the paper is underpinned by the mixed evidence on the existence of ‘greenium’, especially in corporate green bond markets; there has been limited research on the topic and a narrow focus on global, US, or Chinese green bond markets. Instead, the greenium in European debt markets remains underexplored. The objective of this study is to investigate the existence of greenium and its key determinants in European corporate debt capital markets, including the local markets of the United Kingdom (UK), France, Netherlands, and Germany. The sample included 3851 corporate bonds, both green and conventional ones, between 2007 and 2021 from 33 European countries. Linear regression was applied for the analysis. The results show that the climate corporate bonds in Europe are priced at a discount to the same-risk conventional corporate bonds. The magnitude of greenium is around 3 bps. Determinants of greenium include the presence of an ESG rating and belonging to the utility and financial industry. The remaining drivers of bond yields in the European corporate debt market are the credit quality (expressed by the level of credit rating), the coupon size, the bond tenor, the market liquidity, and macroeconomic variables (growth of gross domestic product and consumer price index). For the local corporate debt markets, our results are controversial. In all markets under consideration except for the UK and the Netherlands, we did not find sustainable evidence of greenium. The results of the research lead to a better understanding of the green bond market for investors, researchers, regulators, and potential issuing companies.
Full article
(This article belongs to the Special Issue Risk Analysis and Management in the Digital and Innovation Economy)
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Open AccessArticle
Risk Measures in Simulation-Based Business Valuation: Classification of Risk Measures in Risk Axiom Systems and Application in Valuation Practice
Risks 2023, 11(1), 13; https://doi.org/10.3390/risks11010013 - 06 Jan 2023
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Simulation-based company valuations are based on an analysis of the risks in the company to be valued. This means that risk analysis is decisively important in a simulation-based business valuation. The link between risk measures, risk conception and risk axiom systems has not
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Simulation-based company valuations are based on an analysis of the risks in the company to be valued. This means that risk analysis is decisively important in a simulation-based business valuation. The link between risk measures, risk conception and risk axiom systems has not yet been sufficiently elaborated for simulation-based business valuations. The aim of this study was to determine which understanding of risk underlies simulation-based business valuations and how this can be implemented via suitable risk measures in simulation-based business valuations. The contribution of this study is providing guidance for the methodologically correct selection of appropriate risk measures. This will help with avoiding valuation errors. To this end, the findings were combined from risk axiom systems with the valuation equations of simulation-based business valuations. Only position-invariant risk measures are suitable for simulation-based business valuations.
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