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Risks, Volume 11, Issue 6 (June 2023) – 15 articles

Cover Story (view full-size image): The purpose of the Bank for International Settlements regulatory agenda, as implemented by financial regulators globally, has been to make banks safer and reduce the likelihood of systemic events. Using an original model of bank profit maximisation under a regulatory constraint, we statistically examine how market risk exposure has interacted with financial performance and capital structure, to see if the Basel regulatory agenda concerning the quantity, quality and liquidity of capital has prompted changes in banking behaviour as measured by exposure to market risk. Breaking new ground, we empirically explore how the regulatory agenda has affected the largest banks. View this paper
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15 pages, 539 KiB  
Article
Uncovering Hidden Insights with Long-Memory Process Detection: An In-Depth Overview
by Hossein Hassani, Masoud Yarmohammadi and Leila Marvian Mashhad
Risks 2023, 11(6), 113; https://doi.org/10.3390/risks11060113 - 16 Jun 2023
Cited by 1 | Viewed by 991
Abstract
Long-memory models are frequently used in finance and other fields to capture long-range dependence in time series data. However, correctly identifying whether a process has long memory is crucial. This paper highlights a significant limitation in using the sample autocorrelation function (ACF) to [...] Read more.
Long-memory models are frequently used in finance and other fields to capture long-range dependence in time series data. However, correctly identifying whether a process has long memory is crucial. This paper highlights a significant limitation in using the sample autocorrelation function (ACF) to identify long-memory processes. While the ACF establishes the theoretical definition of a long-memory process, it is not possible to determine long memory by summing the sample ACFs. Hassani’s 12 theorem demonstrates that the sum of the sample ACF is always 12 for any stationary time series with any length, rendering any diagnostic or analysis procedures that include this sum open to criticism. The paper presents several cases where discrepancies between the empirical and theoretical use of a long-memory process are evident, based on real and simulated time series. It is critical to be aware of this limitation when developing models and forecasting. Accurately identifying long-memory processes is essential in producing reliable predictions and avoiding incorrect model specification. Full article
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22 pages, 1270 KiB  
Article
ESG Disclosure and Firm Performance: An Asset-Pricing Approach
by Vinay Khandelwal, Prashant Sharma and Varun Chotia
Risks 2023, 11(6), 112; https://doi.org/10.3390/risks11060112 - 12 Jun 2023
Cited by 2 | Viewed by 4125
Abstract
Disclosing information on environmental, social, and governance (ESG) parameters is voluntary for most firms across the world. Companies disclose their performance on ESG datapoints due to two main reasons—(i) to gain the trust of stakeholders through increased transparency and (ii) to comply with [...] Read more.
Disclosing information on environmental, social, and governance (ESG) parameters is voluntary for most firms across the world. Companies disclose their performance on ESG datapoints due to two main reasons—(i) to gain the trust of stakeholders through increased transparency and (ii) to comply with regulations imposed by governments and investment houses. Using a dataset of companies disclosing ESG parameters during 2014–2021 from the S&P BSE 500 index, this study investigates the role of ESG disclosure on firm performance. We divide the constituent securities into three factors—size, value, and disclosure to study the premiums generated by firms on each factor using single-, double-, and triple-sorting approaches. We utilize time series regressions along with GRS tests to empirically test the presence of factor premiums. We find the significant role of factors size, value, disclosure, and a dummy variable for the COVID-19 pandemic period to explain the portfolio returns. The study found a negative ESG disclosure premium stating that firms with high levels of disclosure earn less returns compared with the firms with less disclosures. The findings of this study contrast with multiple studies in the past that have found a positive disclosure premium. Our findings help reconcile the mixed evidence on the disclosure–returns relationship. Full article
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23 pages, 475 KiB  
Article
On the Stochastic Volatility in the Generalized Black-Scholes-Merton Model
by Roman V. Ivanov
Risks 2023, 11(6), 111; https://doi.org/10.3390/risks11060111 - 08 Jun 2023
Cited by 2 | Viewed by 1256
Abstract
This paper discusses the generalized Black-Scholes-Merton model, where the volatility coefficient, the drift coefficient of stocks, and the interest rate are time-dependent deterministic functions. Together with it, we make the assumption that the volatility, the drift, and the interest rate depend on a [...] Read more.
This paper discusses the generalized Black-Scholes-Merton model, where the volatility coefficient, the drift coefficient of stocks, and the interest rate are time-dependent deterministic functions. Together with it, we make the assumption that the volatility, the drift, and the interest rate depend on a gamma or inverse-gamma random variable. This model includes the models of skew Student’s t- and variance-gamma-distributed stock log-returns. The price of the European forward-start call option is derived from the considered models in closed form. The obtained formulas are compared with the Black-Scholes formula through examples. Full article
15 pages, 392 KiB  
Article
Investigating Causes of Model Instability: Properties of the Prediction Accuracy Index
by Ross Taplin
Risks 2023, 11(6), 110; https://doi.org/10.3390/risks11060110 - 07 Jun 2023
Cited by 1 | Viewed by 1172
Abstract
The Prediction Accuracy Index (PAI) monitors stability, defined as whether the predictive power of a model has deteriorated due to a change in the distribution of the explanatory variables since its development. This paper shows how the PAI is related to the Mahalanobis [...] Read more.
The Prediction Accuracy Index (PAI) monitors stability, defined as whether the predictive power of a model has deteriorated due to a change in the distribution of the explanatory variables since its development. This paper shows how the PAI is related to the Mahalanobis distance, an established statistic for examining high leverage observations in data. This relationship is used to explore properties of the PAI, including tools for how the PAI can be decomposed into effects due to (a) individual observations/cases, (b) individual variables, and (c) shifts in the mean of variables. Not only are these tools useful for practitioners to help determine why models fail stability, but they also have implications for auditors and regulators. In particular, reasons why models containing econometric variables may fail stability are explored and suggestions to improve model development are discussed. Full article
32 pages, 2302 KiB  
Article
Do Behavioral Biases Affect Investors’ Investment Decision Making? Evidence from the Pakistani Equity Market
by Zain UI Abideen, Zeeshan Ahmed, Huan Qiu and Yiwei Zhao
Risks 2023, 11(6), 109; https://doi.org/10.3390/risks11060109 - 06 Jun 2023
Cited by 5 | Viewed by 11118
Abstract
Using a unique sample constructed by 600 investors’ responses to a structured questionnaire, we investigate the impact of behavioral biases on the investors’ investment decision making in the Pakistani equity market, as well as the roles that market anomalies and financial literacy play [...] Read more.
Using a unique sample constructed by 600 investors’ responses to a structured questionnaire, we investigate the impact of behavioral biases on the investors’ investment decision making in the Pakistani equity market, as well as the roles that market anomalies and financial literacy play in the decision making process. We first document the empirical evidence to support that the behavioral biases and market anomalies are closely associated and that these two factors significantly influence the investors’ investment decision making. The additional analyses confirm the mediating roles of certain market anomalies in the association between the investors’ behavioral biases and their investment decision making. Furthermore, empirical evidence reveals that financial literacy moderates the association between behavioral biases and market anomalies, and eventually influences the investors’ investment decision making. Overall, although the results are inconclusive for the relationships between certain variables, our results highlight the importance of financial literacy in terms of optimal investment decision making of individuals and the stability of the overall stock market. Full article
(This article belongs to the Special Issue Frontiers in Quantitative Finance and Risk Management)
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28 pages, 564 KiB  
Article
The Explanatory Factors of Risk Disclosure in the Integrated Reports of Listed Entities in Brazil
by Fabio Albuquerque, Eveline Monteiro and Maria Albertina Barreiro Rodrigues
Risks 2023, 11(6), 108; https://doi.org/10.3390/risks11060108 - 05 Jun 2023
Viewed by 1426
Abstract
The gaps observed in entities’ traditional reports and accounts led to the emergence of the integrated report (IR), which includes several content elements, namely the component relating to risks and opportunities. Within this scope, the specific risks that may affect an organization’s capacity [...] Read more.
The gaps observed in entities’ traditional reports and accounts led to the emergence of the integrated report (IR), which includes several content elements, namely the component relating to risks and opportunities. Within this scope, the specific risks that may affect an organization’s capacity to create value are disclosed, among others, which is information of interest to the different stakeholders. This paper aims to identify the explanatory factors that influence the disclosure of risks in IRs. For this purpose, the IRs of entities listed on the Brazilian stock exchange for the year 2020 were assessed. The study was based on the explanatory theories of risk disclosure usually found in the literature, namely, the legitimacy, the agency, the signaling, and the upper echelon theories. Linear regression models were used with the disclosure rates of different types of risk as dependent variables. The size, profitability, indebtedness, independence, and gender diversity in the board of directors (BD), audit, and activity sector comprised the selected explanatory factors. Associations were found between some of the types of risks disclosed and the size of the entity, the existence of an audit, the independence of the BD, and the activity sector. The paper contributes to the literature about the explanatory factors of risk disclosure by exploring its analysis with different typologies and attributes, having the IR as a source of information, which is still little explored. The scientific contribution encompasses proposing a new risk analysis model in the IR. The innovative elements also comprise the classification of risks related to sustainable development (SD), including environmental, social, and governance (ESG) factors. Full article
16 pages, 899 KiB  
Article
A Guaranteed-Return Structured Product as an Investment Risk-Hedging Instrument in Pension Savings Plans
by Zvika Afik, Elroi Hadad and Rami Yosef
Risks 2023, 11(6), 107; https://doi.org/10.3390/risks11060107 - 05 Jun 2023
Viewed by 1248
Abstract
This study proposes a structured product (SP) for hedging defined contribution pension fund members against capital market risk. Using Monte Carlo simulations on three different guaranteed returns to test the investment strategy of the SP against a balanced investment portfolio, we measure their [...] Read more.
This study proposes a structured product (SP) for hedging defined contribution pension fund members against capital market risk. Using Monte Carlo simulations on three different guaranteed returns to test the investment strategy of the SP against a balanced investment portfolio, we measure their performance across a wide variety of capital market returns and risk scenarios. The results show that the SP guarantees a minimal return on the pension savings portfolio and offers a higher portfolio return at a lower investment risk, compared with the balanced investment portfolio. We conclude that the SP may become popular among pension fund members, potentially leading to improved risk management, greater competition, and investment strategy innovations for defined contribution pension schemes. Full article
(This article belongs to the Special Issue Frontiers in Quantitative Finance and Risk Management)
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23 pages, 3018 KiB  
Article
Big Data Analytics to Support Open Innovation Strategies in Banks
by Tasya Aspiranti, Qaisar Ali and Ima Amaliah
Risks 2023, 11(6), 106; https://doi.org/10.3390/risks11060106 - 05 Jun 2023
Viewed by 1761
Abstract
Today’s dynamic business environment has pushed service-oriented firms such as banks to collaborate with external partners through open innovation (OI) to address issues of service differentiation, optimize customer experience, and create effective open innovation strategies (OIS). However, the essential elements required to design [...] Read more.
Today’s dynamic business environment has pushed service-oriented firms such as banks to collaborate with external partners through open innovation (OI) to address issues of service differentiation, optimize customer experience, and create effective open innovation strategies (OIS). However, the essential elements required to design OIS and the methods to manage these strategies are missing. Therefore, this study aims to investigate the strategic resources essential to creating OIS and identify the tools to manage these resources. Following the fundamentals of the resource-based view (RBV), bank openness (BOP), selection of external partners (SEP), open innovation methods (OIM), formalizing collaboration processes (FCP), and banks’ internal practices (BIP) are identified as the strategic elements required for creating OIS, and the role of big data analytics (BDA) in these strategic resources is examined. The data were collected through a survey questionnaire from 425 bank executives employed at different digital banks located in Malaysia. To achieve our research objectives, a quantitative deductive research design was employed and the collected data were processed in WarPLS using the structural equation modeling (SEM) technique to test the research hypotheses of this study. The empirical results reveal that BDA has a significant positive impact on BOP, SEP, and FCP, whereas OIM and BIP have an insignificant positive impact. The findings of this study contribute to designing a robust digital strategy to enhance the banking sector’s contribution to the development of financial industries in developing countries by employing BDA as a major strategic policy tool of OIS Full article
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14 pages, 1424 KiB  
Article
Constant or Variable? A Performance Analysis among Portfolio Insurance Strategies
by Daniele Mancinelli and Immacolata Oliva
Risks 2023, 11(6), 105; https://doi.org/10.3390/risks11060105 - 02 Jun 2023
Viewed by 1129
Abstract
In this paper, we propose a comparison among three portfolio insurance strategies, namely the constant proportion portfolio insurance, the time-invariant portfolio protection, and the exponential proportion portfolio insurance, via an in-depth performance analysis. We aim to ascertain whether strategies characterized by variable parameters [...] Read more.
In this paper, we propose a comparison among three portfolio insurance strategies, namely the constant proportion portfolio insurance, the time-invariant portfolio protection, and the exponential proportion portfolio insurance, via an in-depth performance analysis. We aim to ascertain whether strategies characterized by variable parameters can outperform those with constant parameters by measuring potential returns, investment riskiness, downside protection capability, and ability to capture market upside. The results, achieved in a model-free framework by exploiting bootstrapping techniques, advise that no winning strategy exists overall, even when considering different volatility regimes, rebalancing frequencies, and protection levels. Full article
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23 pages, 2132 KiB  
Article
Regulation and De-Risking: Theoretical and Empirical Insights
by Lawrence Haar and Andros Gregoriou
Risks 2023, 11(6), 104; https://doi.org/10.3390/risks11060104 - 02 Jun 2023
Viewed by 1362
Abstract
The purpose of the Bank for International Settlements regulatory agenda, as implemented by financial regulators globally, has been to make banks safer and reduce the likelihood of systemic events. Using an original model of bank profit maximisation under a regulatory constraint, we statistically [...] Read more.
The purpose of the Bank for International Settlements regulatory agenda, as implemented by financial regulators globally, has been to make banks safer and reduce the likelihood of systemic events. Using an original model of bank profit maximisation under a regulatory constraint, we statistically examine how market risk exposure has interacted with financial performance and capital structure, to see if the Basel regulatory agenda concerning the quantity, quality and liquidity of capital, has prompted changes in banking behaviour as measured by exposure to market risk. Breaking new ground, we empirically explore how the regulatory agenda has affected the largest banks. We analyse if the regulatory agenda has succeeded in aligning the cost of capital with their exposure to market risk, measured by Value at Risk; or if regulations have induced changes to banking activities. We find rather than regulation inducing changes to the rate at which unchanged risk exposure is capitalised; it leads to changes in the nature of exposures. Risk has declined along with financial performance while the cost of capital is largely unchanged. A consequence of regulation may be to encourage the migration of riskier activities to organisations where it may be borne more cheaply. Full article
(This article belongs to the Special Issue Risks: Feature Papers 2023)
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24 pages, 563 KiB  
Article
On Valuation and Investments of Pension Plans in Discrete Incomplete Markets
by Michail Anthropelos and Evmorfia Blontzou
Risks 2023, 11(6), 103; https://doi.org/10.3390/risks11060103 - 01 Jun 2023
Viewed by 1076
Abstract
We study the valuation of a pension fund’s obligations in a discrete time and space incomplete market model. The market’s incompleteness stems from the non-replicability of the wage process that finances the pension plan through time. The contingent defined-benefit liability of the pension [...] Read more.
We study the valuation of a pension fund’s obligations in a discrete time and space incomplete market model. The market’s incompleteness stems from the non-replicability of the wage process that finances the pension plan through time. The contingent defined-benefit liability of the pension fund is a function of the wages, which can be seen as the payoff of a path-dependent derivative security. We apply the notion of the super-hedging value and propose its difference from the current pension’s fund capital as a measure of distance to liability hedging. The induced closed-form expressions of the values and the related investment strategies provide insightful comparative statistics. Furthermore, we use a utility-based optimization portfolio to point out that in cases of sufficient capital, the application of a subjective investment criterion may result in heavily different strategies than the super-hedging one. This means that the pension fund will be left with some liability risk, although it could have been fully hedged. Finally, we provide conditions under which the effect of a possible early exit leaves the super-hedging valuation unchanged. Full article
(This article belongs to the Special Issue Frontiers in Quantitative Finance and Risk Management)
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17 pages, 491 KiB  
Article
The Relationship between Capital Structure and Firm Performance: The Moderating Role of Agency Cost
by Amanj Mohamed Ahmed, Deni Pandu Nugraha and István Hágen
Risks 2023, 11(6), 102; https://doi.org/10.3390/risks11060102 - 01 Jun 2023
Cited by 6 | Viewed by 7240
Abstract
Since it first appeared, agency theory has argued that debt can decrease agency issues between agent and principal and enhance the value of firms. This paper explores the moderating effect of agency cost on the association between capital structure and firm performance. A [...] Read more.
Since it first appeared, agency theory has argued that debt can decrease agency issues between agent and principal and enhance the value of firms. This paper explores the moderating effect of agency cost on the association between capital structure and firm performance. A panel econometric method, namely a fixed-effect regression model, was used to evaluate the above description. This investigation uses secondary data collected from published annual reports of manufacturing firms listed on Tehran Stock Exchange (TSE) during 2011–2019. Empirical results show that capital structure is negatively related to firm performance. Agency cost also has a negative impact on corporate performance; however, in the case of ROA and EPS, the relationship is positive. Interestingly, the findings illustrate that increasing the level of debt can reduce agency costs and enhance firm performance. Moreover, robust correlations are revealing that agency cost significantly affects the relationship between capital structure and corporate performance. These findings provide proof to support the assumptions of agency theory, which explains the association between capital structure and performance of firms. This study provides new perspectives on the relationship between capital structure and firm performance by using data from listed manufacturing firms in Iran; hence, these new insights from a developing market improve the understanding of capital structure in Asian and Middle Eastern markets. Full article
22 pages, 4519 KiB  
Article
Context-Based and Adaptive Cybersecurity Risk Management Framework
by Henock Mulugeta Melaku
Risks 2023, 11(6), 101; https://doi.org/10.3390/risks11060101 - 31 May 2023
Cited by 4 | Viewed by 4316
Abstract
Currently, organizations are faced with a variety of cyber-threats and are possibly challenged by a wide range of cyber-attacks of varying frequency, complexity, and impact. However, they can do something to prevent, or at least mitigate, these cyber-attacks by first understanding and addressing [...] Read more.
Currently, organizations are faced with a variety of cyber-threats and are possibly challenged by a wide range of cyber-attacks of varying frequency, complexity, and impact. However, they can do something to prevent, or at least mitigate, these cyber-attacks by first understanding and addressing their common problems regarding cybersecurity culture, developing a cyber-risk management plan, and devising a more proactive and collaborative approach that is suitable according to their organization context. To this end, firstly various enterprise, Information Technology (IT), and cybersecurity risk management frameworks are thoroughly reviewed along with their advantages and limitations. Then, we propose a proactive cybersecurity risk management framework that is simple and dynamic, and that adapts according to the current threat and technology landscapes and organizational context. Finally, performance metrics to evaluate the framework are proposed. Full article
(This article belongs to the Special Issue Risks: Feature Papers 2023)
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16 pages, 1970 KiB  
Article
The Generalised Pareto Distribution Model Approach to Comparing Extreme Risk in the Exchange Rate Risk of BitCoin/US Dollar and South African Rand/US Dollar Returns
by Thabani Ndlovu and Delson Chikobvu
Risks 2023, 11(6), 100; https://doi.org/10.3390/risks11060100 - 31 May 2023
Viewed by 1118
Abstract
Cryptocurrencies are said to be very risky, and so are the currencies of emerging economies, including the South African rand. The steady rise in the movement of South Africans’ investments between the rand and BitCoin warrants an investigation as to which of the [...] Read more.
Cryptocurrencies are said to be very risky, and so are the currencies of emerging economies, including the South African rand. The steady rise in the movement of South Africans’ investments between the rand and BitCoin warrants an investigation as to which of the two currencies is riskier. In this paper, the Generalised Pareto Distribution (GPD) model is employed to estimate the Value at Risk (VaR) and the Expected Shortfall (ES) for the two exchange rates, BitCoin/US dollar (BitCoin) and the South African rand/US dollar (ZAR/USD). The estimated risk measures are used to compare the riskiness of the two exchange rates. The Maximum Likelihood Estimation (MLE) method is used to find the optimal parameters of the GPD model. The higher extreme value index estimate associated with the BTC/USD when compared with the ZAR/USD estimate, suggests that the BTC/USD is riskier than the ZAR/USD. The computed VaR estimates for losses of $0.07, $0.09, and $0.16 per dollar invested in the BTC/USD at 90%, 95%, and 99% compared to the ZAR/USD’s $0.02, $0.02, and $0.03 at the respective levels of significance, confirm that BitCoin is riskier than the rand. The ES (average losses) of $0.11, $0.13, and $0.21 per dollar invested in the BTC/USD at 90%, 95%, and 99% compared to the ZAR/USD’s $0.02, $0.02, and $0.03 at the respective levels of significance further confirm the higher risk associated with BitCoin. Model adequacy is confirmed using the Kupiec test procedure. These findings are helpful to risk managers when making adequate risk-based capital requirements more rational between the two currencies. The argument is for more capital requirements for BitCoin than for the South African rand. Full article
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20 pages, 886 KiB  
Article
Estimating Territory Risk Relativity Using Generalized Linear Mixed Models and Fuzzy C-Means Clustering
by Shengkun Xie and Chong Gan
Risks 2023, 11(6), 99; https://doi.org/10.3390/risks11060099 - 24 May 2023
Viewed by 1160
Abstract
Territory risk analysis has played an important role in auto insurance rate regulation. It aims to design rating territories from a set of basic rating units so that their respective risk relativities can be estimated to reflect the regional risk of insurance. In [...] Read more.
Territory risk analysis has played an important role in auto insurance rate regulation. It aims to design rating territories from a set of basic rating units so that their respective risk relativities can be estimated to reflect the regional risk of insurance. In this work, spatially constrained clustering is first applied to insurance loss data to form such regions, using the forward sortation area (FSA) as a basic rating unit. The groupings of FSA by spatially constrained clustering reduce the insurance rate heterogeneity caused by smaller risk exposures. Furthermore, the generalized linear mixed model (GLMM) is proposed to derive the risk relativities of clusters and each FSA. In addition, as an alternative approach, fuzzy C-Means clustering is proposed to derive the risk relativity of FSA, and the obtained results are compared to the ones from GLMM. The spatially constrained clustering and risk relativity estimation help to retrieve a set of territory risk benchmarks used in rate filings within the regulation process. It also provides guidance for auto insurance companies on rate making. Full article
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