Implications For Risk Management Research Articles

Time-frequency connectedness and spillover among carbon, climate, and energy futures: Determinants and portfolio risk management implications

This study examines returns and volatility connectedness and spillover among carbon, climate, and energy futures using TPV-VAR frequency connectedness approach with daily frequency observations from December 15, 2020 to September 23, 2022. The study also evaluates factors that contribute to connectedness and explores hedging benefits from using carbon and climate futures with bivariate and multivariate portfolio strategies. This study reveals higher levels of total return and volatility connectedness and spillover effects across carbon, climate, and energy futures markets. There are persistent high spillovers in the short term, but spillovers are lower in the long run. These spillover effects are time-varying and change with economic, geopolitical, financial market events. For return and volatility spillover, carbon, climate, natural gas, gasoil and coal futures serve as net informational and risk recipients while Brent crude oil, heating oil and gasoline futures serve as informational and risk transmitters. This transmission mechanism remains consistent in the short term. However, in the long term, crude oil futures became a net receiver, while climate change futures changed to a risk transmitter. The findings indicate that transmission mechanism changed during the Russia-Ukraine war, whereby carbon, Brent crude oil, heating oil, gasoline and gas oil futures played different roles in the return and volatility spillover network. We find that geopolitical risk, equity market volatility, global financial stress, and clean energy innovations are determinants of return and volatility connectedness. Understanding the interrelations among carbon, climate and energy markets can guide policy making to improve the effectiveness of climate actions. The findings also underline the hedging and portfolio diversification implications of carbon and climate futures for energy commodities market.

The influence of COVID-19 Mortality Rate Formats on Emotional Reactions, Risk perception, and self-protective Behavioral Intentions

We investigated whether different Mortality Rate Formats used to express the same objective probability affected people’s Emotional reactions, Risk perception, and protective behavioral intentions. A sample from the Italian population (N = 604) was exposed to six different formats (i.e. Absolute value; Raw ratio; 1 in X; Verbal; Percentage; Probability) to report the mortality rate of COVID-19 in a between-subject design. In line with expectations, the Probability format led to lower emotional reactions compared to all the other formats. Moreover, results from a path analysis revealed that emotional reactions predicted risk perception. The Mortality Rate Formats also had an indirect effect on Behavioral Intentions to protect oneself, which was mediated by emotional reactions and risk perception. The effect sizes of these indirect effects ranged from small to medium. The direct effect of risk on intentions was found to differ among two dimensions of risk. Affective Risk led to higher Behavioral Intentions, while Deliberative Risk had the opposite effect. We discuss these results in line with the ongoing debate regarding the role played by risk scientists during the pandemic and offer practical implications for risk management during health crises like COVID-19.

The Impact of COVID-19 on Investors Behavior: Evidence from Risk-aversion, Herding Behavior, and Availability Bias

The unforeseen pandemic has significantly influenced the financial market, and has caused major disruptions in the global economy, leading to a sharp decline in stock prices and increased volatility in financial markets. Assessing the impact of the COVID-19 pandemic on the market is essential for both investors and policymakers. This study recognizes that irrationality exists during the pandemic in investors decision-making and find that the efficient market hypothesis does not always hold perfectly. According to the analysis, emotional and cognitive biases play significant roles in investors decision-making, especially under uncertainty. Using empirical data from the previous study, the existence of risk aversion, herding behavior, and availability bias during the pandemic is testified. The results suggest that the pandemic has led to an increase in risk aversion among investors, as well as a tendency towards herding behavior in the stock market but not the crypto market. Furthermore, evidence of availability bias is found, with investors placing greater weight on recent news and information related to the pandemic, and making decisions based on that information. These findings have important implications for investment strategy and risk management during a crisis.

The Dynamic Return and Volatility Spillovers among Size-Based Stock Portfolios in the Saudi Market and Their Portfolio Management Implications during Different Crises

This study contributes to the ongoing debate on the size effect and size-based investment styles by investigating the return and volatility spillovers and time-varying conditional correlations among Saudi large-, mid-, and small-cap indices. To this end, we utilize the weekly returns on the MSCI Saudi large-, mid-, and small-cap indices over a long sample period, spanning several crises. The econometric approach that we use is a VAR-asymmetric BEKK-GARCH model which accounts for structural breaks. On the basis of the VAR-asymmetric BEKK-GARCH model estimation results, we calculate portfolio weights and hedge ratios, and discuss their risk management implications. The empirical results confirm the presence of unilateral return spillovers running from mid- to small-cap stocks, while multilateral volatility spillovers are documented, albeit substantially weakened when accounting for structural breaks. The time-varying conditional correlations display clear spikes around crises, which translate to higher hedge ratios, increasing the cost of hedging during turbulent times. The optimal portfolio weights suggest that investors generally overweight large caps in their portfolios during uncertain times to minimize risk without lowering expected returns. The main takeaway from our results is that passively confining fund managers to a particular size category regardless of the prevailing market conditions may lead to suboptimal performance.

A study of temperature variability on admissions and deaths for cardiovascular diseases in Northwestern China

ObjectiveTo explore the effect of temperature variability (TV) on admissions and deaths for cardiovascular diseases (CVDs).MethodThe admissions data of CVDs were collected in 4 general hospitals in Jinchang City, Gansu Province from 2013 to 2016. The monitoring data of death for CVDs from 2013 to 2017 were collected through the Jinchang City Center for Disease Control and Prevention. Distributed lag nonlinear model (DLNM) was combined to analyze the effects of TV (daily temperature variability (DTV) and hourly temperature variability (HTV)) on the admissions and deaths for CVDs after adjusting confounding effects. Stratified analysis was conducted by age and gender. Then the attribution risk of TV was evaluated.ResultsThere was a broadly linear correlation between TV and the admissions and deaths for CVDs, but only the association between TV and outpatient and emergency room (O&ER) visits for CVDs have statistically significant. DTV and HTV have similar lag effect. Every 1 ℃ increase in DTV and HTV was associated with a 3.61% (95% CI: 1.19% ~ 6.08%), 3.03% (95% CI: 0.27% ~ 5.86%) increase in O&ER visits for CVDs, respectively. There were 22.75% and 14.15% O&ER visits for CVDs can attribute to DTV and HTV exposure during 2013–2016. Males and the elderly may be more sensitive to the changes of TV. Greater effect of TV was observed in non-heating season than in heating season.ConclusionTV was an independent risk factor for the increase of O&ER visits for CVDs, suggesting effective guidance such as strengthening the timely prevention for vulnerable groups before or after exposure, which has important implications for risk management of CVDs.

The impact of natural disaster shocks on business confidence level and Istanbul Stock Exchange: A wavelet coherence approach

The focus of this study is to examine the short‐ and long‐term causal effects of natural disaster shocks on the stock market and business confidence level in the time‐frequency domain by studying the co‐movements between earthquake data and the Istanbul Stock Index closing prices, using the Wavelet Coherence and Phase Difference analyses. The empirical findings reveal that the relationship between earthquake events and financial markets is not stable over time and across different time horizons. The linkage becomes stronger in the long term when the impact of the earthquake event coincides with a financial crisis reflecting a combined effect. This nexus is also strong during the years 2007–2011 reflecting a similar combined effect of both an earthquake event and the global financial crisis. Meanwhile, co‐movement between the earthquake and the financial market index implies a negative effect in the period 2011–2012, indicating short‐run effects of stock market shocks. Differentiating these short‐term and long‐term effects has implications for risk management and policymaking.

The role of higher moments in predicting China's oil futures volatility: Evidence from machine learning models

This paper expands the emerging literature on volatility forecasting for China's oil market by exploring the predictive ability of higher-order moments (skewness, kurtosis, hyperskewness, and hyperkurtosis) based on high-frequency data. Our investigation is originally based on the heterogeneous autoregressive (HAR) framework, but considering the possible multicollinearity and nonlinearity, it is extended to various machine learning (ML) models and combination forecasting models. The results reveal that higher-order moments, including the two highest moments, always significantly improve predictive performance for the COVID-19 crisis. We further examine the interpretability of ML models and each factor's contribution to the prediction, finding that odd and even moments contain short- and long-term prediction information, respectively. This paper also highlights the effectiveness of ML models for capturing trends in oil futures volatility with higher-order moments and the satisfactory performance of combination forecasting models. Finally, we investigate the predictability of asymmetric risk patterns and obtain identical results. Our study has important implications for financial risk management, asset pricing, and portfolio allocation.

Interplay between Lipid Profile and Weight-Related Outcomes in Healthy Overweight Adults: In-sights from Comprehensive Analyses

Background: The escalating prevalence of overweight and obesity has heightened concerns about cardiovascular health. The intricate interplay between lipid profile variables and weight-related outcomes plays a pivotal role in shaping cardiovascular risks among individuals with excess body weight. This study investigates the associations between lipid profile variables and weight-related indicators in a cohort of healthy, overweight adults, shedding light on potential implications for cardiovascular risk management. Methods: The prevalence of metabolic syndrome, risk factors, and related lifestyle in adult Myanmar citizens were examined in the Inter-University Consortium for Political and Social Research Study (ICPSR146521) using prospective data. The patient’s lipid profiles and demographic data were statistically analyzed using the statistical MedCalc tool. Statistical significance was determined using a 0.05 p-value. Results: Results demonstrate that while BMI is influenced by multiple factors beyond lipid profile variables, waist circumference exhibits moderate association with these variables. Notably, triglycerides significantly correlated with waist circumference, suggesting a potential role in visceral fat accumulation. Additionally, the study highlights the impact of high-density lipoprotein (HDL) cholesterol levels on body weight, indicating that higher HDL levels are associated with lower body weights among healthy overweight adults. Conclusion: This study provides comprehensive insights into the complex relationship between lipid profile variables and weight-related outcomes among healthy, overweight adults. These findings underscore the importance of weight management strategies for cardiovascular health and suggest potential avenues for targeted interventions. By understanding the interplay between lipid profiles and obesity, clinicians and public health professionals can develop more effective strategies to mitigate cardiovascular risks in this demographic

Advances in Monitoring and Understanding the Dynamics of Suspended-Sediment Transport in the River Drava, Slovenia: An Analysis More than a Decade-Long

Managing sediment transport in streams is crucial to the surface water resource development strategy and has several implications for flood risk and water management, hydropower use, and balancing river morphology. This paper summarises the movement and behaviour of suspended sediment within the Slovenian portion of the River Drava, covering a span of thirteen years from 2005 to 2018. An analysis of relevant data collected during this period is also presented. Suspended-sediment dynamics strongly depend on flow velocity, seasonal variations in sediment sources, and human interventions in the riverbed. The transportation of material in the River Drava results in the accumulation of sediments in reservoirs and riverbeds, consequently impeding the natural hydrological cycle by reducing the outflow into aquifers. The 2018 high-water event is analysed in terms of the dependence of concentration of suspended sediments on discharge, where counterclockwise hysteresis was observed, providing an essential clue to the origin of sediment. Sediments from the River Drava in Slovenia are managed with some conventional processes and are mainly deposited or reintegrated into rivers and aquatic ecosystems. Some additional sediment management strategies with long-term solutions for efficient and comprehensive water management, hydropower, and ecological problems are proposed.

Evaluating how well active fault mapping predicts earthquake surface-rupture locations

Abstract Earthquake surface-fault rupture location uncertainty is a key factor in fault displacement hazard analysis and informs hazard and risk mitigation strategies. Geologists often predict future rupture locations from fault mapping based on the geomorphology interpreted from remote-sensing data sets. However, surface processes can obscure fault location, fault traces may be mapped in error, and a future rupture may not break every fault trace. We assessed how well geomorphology-based fault mapping predicted surface ruptures for seven earthquakes: 1983 M 6.9 Borah Peak, 2004 M 6.0 Parkfield, 2010 M 7.2 El Mayor–Cucapah, 2011 M 6.7 Fukushima-Hamadori, 2014 M 6.0 South Napa, 2016 M 7.8 Kaikoura, and 2016 M 7 Kumamoto. We trained geoscience students to produce active fault maps using topography and imagery acquired before the earthquakes. A geologic professional completed a “control” map. Mappers used a new “geomorphic indicator ranking” approach to rank fault confidence based on geomorphologic landforms. We determined the accuracy of the mapped faults by comparing the fault maps to published rupture maps. We defined predicted ruptures as ruptures near a fault (50–200 m, depending on the fault confidence) that interacted with the landscape in a similar way to the fault. The mapped faults predicted between 12% to 68% of the principal rupture length for the studied earthquakes. The median separation distances between predicted ruptures and strong, distinct, or weak faults were 15–30 m. Our work highlights that mapping future fault ruptures is an underappreciated challenge of fault displacement hazard analysis—even for experts—with implications for risk management, engineering site assessments, and fault exclusion zones.

Changes in flood-associated rainfall losses under climate change

Climate change is expected to impact the severity and frequency of floods, which has implications for flood risk management. Design floods and derived flood frequency curves obtained using event-based rainfall-runoff models are widely used in industry to assess flood risks for planning and design purposes. For these approaches it is necessary to have (a) rainfall inputs, and (b) rainfall losses specified, the latter representing the amount of rainfall that is either intercepted, stored on the surface, or infiltrated into the soil and does not contribute to the flood hydrograph. There is extensive research on changes in flooding under climate change that focus on projections of rainfall. However, there is little research into projections of rainfall losses under climate change, despite the knowledge that their changes will modulate the flood response. Here, we present one of the first studies seeking to quantify how rainfall losses, as represented by estimates of initial and continuing losses used in event-based models, are projected to change under climate change.We identify dependencies between rainfall losses and antecedent soil moisture in around half (over 200) of the largely unregulated catchments (i.e. watersheds) in Australia analysed in this study and use these relationships to project rainfall losses under climate change. Near universal increases in both the mean and variance of both initial losses and continuing losses are projected in these catchments, suggesting that increased rainfall losses could offset the impact of increased rainfalls for frequently occurring floods and result in an increased variance in flood responses.

Ultra-low volume (ULV) adulticide treatment impacts age structure of Culex species (Diptera: Culicidae) in a West Nile virus hotspot.

West Nile virus (WNV) invaded the continental United States over 20 years ago and continues to cause yearly seasonal outbreaks of human and veterinary disease. In the suburbs of Chicago, Illinois, ultra-low volume (ULV) truck-mounted adulticide spraying frequently is performed to reduce populations of Culex restuans Theobald and Cx. pipiens L. mosquitoes (Diptera: Culicidae) in an effort to lower the risk of WNV transmission. The effectiveness of this control method has not been rigorously evaluated, and evidence for Culex population reduction after ULV adulticide spraying has been inconclusive. Therefore, we evaluated the results of 5 sequential weekly truck-mounted adulticide applications of Zenivex® E20 (etofenprox) in 2 paired sites located in Cook County, IL, during the summer of 2018. Mosquito population abundance, age structure, and WNV infection prevalence were monitored and compared between paired treatment and nearby control sites. Adulticide treatment did not result in consistent short-term or long-term reductions in target WNV vector Culex abundance. However, there was a significant increase in the proportion of nulliparous females in the treated sites compared to control sites and a decrease in Cx. pipiens WNV infection rates at one of the treated sites. This evidence that ULV adulticide spraying altered the age structure and WNV infection prevalence in a vector population has important implications for WNV transmission risk management. Our findings also underscore the importance of measuring these important indicators in addition to abundance metrics when evaluating the efficacy of control methods.

Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models

This paper investigates how geopolitical risks influence the prediction performance on the US stock market volatility with machine learning models. Further, it compares the predictive performance of individual and combination forecast methods. With SHAP algorithm, it could identify which factor has a great impact and fully extract the information of geopolitical risks in predicting. Empirical results show that military build-ups and escalation of war have great importance on predicting realized volatility among various geopolitical risks. The research further emphasizes the superior performance of machine learning and forecast combination methods, especially SVR method and trimmed mean combination. In addition, by allocating portfolio according to the machine learning-based volatility forecasts, particularly elastic net and random forest, a mean-variance investor can achieve sizeable financial benefits. Our paper provides substantial implications for political risk management and volatility forecasting.

Effects of climate change and grazing intensity on grassland productivity—A case study of Inner Mongolia, China

In the last 30 years, grassland productivity has declined seriously due to climate variations and unreasonable human activities. Therefore, to analyze the impact of different factors on grassland productivity, we selected three grassland stations of the Typical Steppe from west to east and collected 38 years of data. The Pearson Correlation and Fixed Effect Model were used to analyze the impact of precipitation, temperature, and grazing intensity on grassland productivity. The empirical results show that precipitation positively and significantly affected grassland productivity. The effects of climate change are more significant than human activities, but the impact of temperature is greater than precipitation. The synergy between precipitation and temperature was greater than between precipitation and temperature separately. In addition, the effects of climate change and human activities on grassland productivity have evident regional heterogeneity. The variation trend gradually increases from west to east in factors that affect grassland productivity. Therefore, we suggest some implications for grassland risk management, such as utilizing some financial products for climate risk and focusing on the synergy index to design financial products, such as design weather derivatives. Lastly, we should strengthen the research on the relationship between climate change and grassland productivity to provide a scientific basis for revealing the intrinsic relationship between climate, human activities, and grassland productivity.

RISK MANAGEMENT IN VIA FERRATA CLIFF CLIMBING TOURISM ACTIVITIES IN MOUNT MENDELEM, PEMALANG REGENCY

Today's tourism industry has experienced rapid changes due to the variety of tourists now wanting to obtain an authentic experience. In Indonesia itself, adventure tourism has become a prima donna since 2018 because it has brought 100,000 tourists from all over the world. This provides great economic value for the destination visited up to 67%. Via ferrata is one of the growing adventure tourism activities in Indonesia. Despite the high risk, this activity has a main market, which is the general public who want to experience rock climbing without having to have special abilities. In order to minimize these risks, it is necessary to have risk management so that the via ferrata can be made into extreme tourism but still safe for public tourists. The purpose of this research is to identify and find out the theoretical implications of risk management carried out via ferrata managers. Good risk management is applying industry management based on existing policies, standards, and procedures. The method used is qualitative descriptive with analysis using coding tools. Via ferrata does not yet have standard rules and SOPs. The new risk management is assessed based on the safety aspects of the safety equipment referring to the UIAA. All Mount Mendelem via ferrata operators do not have rock climbing certification and the existing SOP has not been written and the implementation is not suitable. Even so, in terms of security, the manager takes great care to create a tracking lane as an alternative to the down lane. So in this case the manager has applied the standards well but not yet for the policies and procedures used.

Leading indicators for the US housing market: New empirical evidence and thoughts about implications for risk managers and ESG investors

We argue that financial risk managers should focus more strongly on developing forward-looking early warning indicator systems for the North American real estate market. Based on time series data from the US housing market that focuses on the subprime crisis and the period directly after this event, we discuss possible information that such early warning indicator systems could be based on and analyze the presence of a lead-lag relationship between US housing starts and the Architectural Billings Index. We find evidence for such a relation using two different approaches, namely Granger causality tests and transfer entropy analyses. We then discuss the implications of our findings for financial risk managers as well as for ESG investors.

Crisis risk and risk management

AbstractWe assess the state of knowledge about crisis risk and its implications for risk management. Data that became available after the global financial crisis show that some types of crises are predictable when accounting for interactions between risks. However, other types of crises do not seem predictable. There is no evidence that the frequency of economic and financial crises is increasing. While data show that an economic crisis is more likely following a political crisis, there is no comparable evidence for climate events. Strategies that increase firm operational and financial flexibility reduce the adverse impact of crises on firms.

Assessing awareness and compliance with fish consumption advisories on the upper Hudson River: Implications for risk management of the Hudson River Superfund site

Polychlorinated biphenyls (PCBs) are a common environmental contaminant. The NYS Department of Health (DOH) issues fish consumption advisories to limit consumption of PCB-contaminated fish. Fish consumption advisories are utilized as institutional controls within the Hudson River Superfund site to limit exposure to PCBs. There is a “Do Not Eat” advisory for all species caught in the upper Hudson River, from Glens Falls, NY to Troy, NY. The section of the river below Bakers Falls also has a catch-and-release regulation issued by the NYS Department of Environmental Conservation. There is limited research on the effectiveness of these advisories in preventing consumption of contaminated fish in the context of Superfund site risk management. We surveyed individuals actively fishing on the upper Hudson River in the area with a “Do Not Eat” advisory, specifically between Hudson Falls and the Federal Dam in Troy, NY. The goal of the survey was to assess knowledge of the consumption guidelines, and if the guidelines are effectively preventing exposure to PCBs. A subset of individuals continue to consume fish caught from the upper Hudson River Superfund site. Awareness of advisories was inversely related to fish consumption from the Superfund site. Age, race, and possession of a fishing license were associated with overall awareness of fish consumption guidelines; age and possession of a license were associated with awareness of the “Do Not Eat” advisory. While institutional controls appear to have a beneficial impact, there is incomplete awareness and compliance with advisories and regulations aimed at preventing exposure to PCBs from fish consumption. Risk assessment and management strategies for contaminated fisheries should consider imperfect adherence to fish consumption guidelines.

Impact of credit risk management on the financial stability of Vietnamese commercial banks

The research was conducted to understand the impact of credit risk management on the financial stability of 27 Vietnamese commercial banks. From the research results, the authors proposed some implications for credit risk management and solutions to promote financial stability for banks. The study used secondary data obtained from audited financial statements of banks in the period 2006 - 2020. Because the research model had intermediate variables, we used SEM to analyze and the data was processed by Stata. Research results show that non-performing loans and loan loss provisions had a direct effect on profitability and financial stability. Besides, there was an indirect relationship between credit risk management, profitability, and financial stability. The research proved whether the characteristics of Vietnam's banking system and the obtained results are compatible with the theory and previous studies.

The Stability of Islamic Cryptocurrencies and Copula-Based Dependence with Alternative Crypto and Fiat Currencies

Purpose — This study aims to examine Islamic cryptocurrencies and their dependency on foreign exchange markets in vine copula architecture (CD-Vine) and provide a framework for detecting complex dependence structures, risk management implications, and hedging effectiveness. Design/Methodology/Approach — This study used gold-backed cryptocurrencies and three fiat currencies. The vine copula approach was preferred because it applies several distributions and estimates complex dependencies. Hedging effectiveness was measured by constructing simulation-based portfolios optimised with DCC-t-Copula. Benford’s law and realized variance were used to determine the stability of Islamic cryptocurrencies. Findings — According to C-Vine and D-Vine copula models, paper money has a weak tail dependence with gold-backed cryptocurrencies. Only OneGram coin, whose volatility matched the risk of Bitcoin, showed zero irregularities in volume trading. The findings were robust to different estimations based on Minimum Spanning Tree and Dendrogram. Originality/Value — This is the first study to examine Islamic cryptocurrencies’ stability and the significance of hedging effectiveness on gold-backed cryptocurrencies under a copula-based approach. Research Limitations — The study did not apply time-varying vine copula. Practical Implications — The risk management perspective shows insignificant hedge effectiveness in the portfolio of fiat and gold-backed cryptocurrencies.