Implications For Risk Management Research Articles

SOCIO-ECONOMIC SIGNIFICANCE OF INTERNAL AUDIT IMPROVEMENT IN THE REPUBLIC

Improving internal audit processes plays a crucial role in shaping socio-economic landscapes in various sectors. This improvement has significant implications for financial integrity, fraud prevention, compliance, governance, operational efficiency, risk management, investor confidence, job creation, public trust, innovation, growth and global competitiveness. By ensuring clarity, transparency and ethical practices, improved internal audits contribute to a sustainable and prosperous economy, while building trust among stakeholders and attracting investment.

Operational loss recoveries and the macroeconomic environment: Evidence from the U.S. banking sector

Using supervisory data from large U.S. bank holding companies (BHCs), we document that operational loss recovery rates decrease in macroeconomic downturns. This procyclical relationship varies by business lines and loss event types and is robust to alternative data aggregations, macroeconomic measurement horizons, subperiod partitions and estimation methodologies. Further analysis shows that resource constraints faced by BHC risk management functions is a plausible explanation for these patterns. Our findings offer new evidence on how economic shocks transmit to banking industry losses with implications for risk management and supervision.

Two-year Monitoring of Microbiological Water Quality in Small Water Supply Systems: Implications for Microbial Risk Management.

Small water supply systems (SWSSs) are often more vulnerable to waterborne disease outbreaks. In Japan, many SWSSs operate without regulation under the Waterworks Law, yet there is limited investigation into microbial contamination and the associated health risks. In this study, the microbiological water quality of four SWSSs that utilize mountain streams as water sources and do not install water treatment facilities were monitored for over 2 years. In investigated SWSSs, the mean heterotrophic plate counts were below 350 CFU/mL, and the total bacterial loads (16S rDNA concentration) ranged from 4.71 to 5.35 log10 copies/mL. The results also showed the consistent presence of fecal indicator bacteria (FIB), i.e., Escherichia coli and Clostridium perfringens, suggesting the potential of fecal pollution. E. coli was then utilized as an indicator to assess the health risk posed by E. coli O157:H7 and Campylobacter jejuni. The results indicated that the estimated mean annual risk of infection and disability-adjusted life years (DALYs) exceeded acceptable levels in all SWSSs for the two reference pathogens. To ensure microbial water safety, implementing appropriate water treatment facilities with an estimated mean required reduction of 5-6 log10 was necessary. This study highlighted the potential microbial contamination and health risk level in SWSSs that utilize mountain streams as water sources, even though the water sources were almost not affected by human activities. Furthermore, this study would also be helpful in supporting risk-based water management to ensure a safe water supply in SWSSs.

Flight-to-safety across time and market conditions

This paper examines the time-varying directional predictability from the implied volatility of risky assets, such as US stocks, to the implied volatility of less risky or safe haven assets, such as gold, cryptocurrency, foreign exchange rates, and US Treasury notes, which allows for making time and regime dependent inferences on the flight-to-safety phenomenon. The results show a positive directional predictability from the VIX to the implied volatility of gold, cryptocurrency, and foreign exchange rates in periods of high market uncertainty such as the COVID-19 outbreak and the war in Ukraine. The volatility of US Treasury notes has a different response dynamic to the VIX, switching to negative cross-correlations in some cases, given its tight link to inflationary pressure and economic policy uncertainty. The main results remain qualitatively unchanged after incorporating economic policy uncertainty and oil volatility. An additional analysis indicates that flight-to-safety is not exclusively triggered by the high volatility regime in US equities but happens at median levels too. Our findings have important implications for investors, risk managers, and policymakers regarding volatility predictability, hedging, and market stability.

Examining the Distributional Characteristics of Daily Returns of Nifty 50: Normality Assessment and Implications

This paper investigates the distributional characteristics of daily returns of the Nifty 50 index, a benchmark index comprising 50 large-cap stocks traded on the National Stock Exchange of India. Utilizing historical data spanning a specified time period, we conduct normality testing to assess the adequacy of the normal distribution assumption underlying many financial models. Our analysis provides insights into the departure from normality. As a result of departure from Normality, it may affect the tail behaviour, and volatility dynamics of Nifty 50 daily returns, offering implications for risk management, option pricing, portfolio management, and market efficiency. By synthesizing empirical findings with theoretical considerations, this research contributes to a deeper understanding of the statistical properties of Nifty 50 daily returns and informs practitioners in finance about the challenges associated with Modeling and analysing stock market data.

The Potential of Absorbing Aerosols to Enhance Extreme Precipitation

AbstractUnderstanding the impact of various climate forcing agents, such as aerosols, on extreme precipitation is socially and scientifically vital. While anthropogenic absorbing aerosols influence Earth's energy balance and atmospheric convection, their role in extreme events remains unclear. This paper uses convective‐resolving radiative‐convective‐equilibrium simulations, with fixed solar radiation, to investigate the influence of absorbing aerosols on extreme precipitation comprehensively. Our findings reveal an underappreciated mechanism through which absorbing aerosols can, under certain conditions, strongly intensify extreme precipitation. Notably, we demonstrate that a mechanism previously reported for much warmer (hothouse) climates, where intense rainfall alternates with multi‐day dry spells, can operate under current realistic conditions due to absorbing aerosol influence. This mechanism operates when an aerosol perturbation shifts the lower tropospheric radiative heating rate to positive values, generating a strong inhibition layer. Our work highlights an additional potential effect of absorbing aerosols, with implications for climate change mitigation and disaster risk management.

Factors Associated With High-Risk and Low-Risk Bone Stress Injury in Female Runners: Implications for Risk Factor Stratification and Management.

Bone stress injury (BSI) is a common overuse injury in active women. BSIs can be classified as high-risk (pelvis, sacrum, and femoral neck) or low-risk (tibia, fibula, and metatarsals). Risk factors for BSI include low energy availability, menstrual dysfunction, and poor bone health. Higher vertical load rates during running have been observed in women with a history of BSI. The purpose of this study was to characterize factors associated with BSI in a population of premenopausal women, comparing those with a history of high-risk or low-risk BSI with those with no history of BSI. It was hypothesized that women with a history of high-risk BSI would be more likely to exhibit lower bone mineral density (BMD) and related factors and less favorable bone microarchitecture compared with women with a history of low-risk BSI. In contrast, women with a history of low-risk BSI would have higher load rates. Cross-sectional study; Level of evidence, 3. Enrolled were 15 women with a history of high-risk BSI, 15 with a history of low-risk BSI, and 15 with no history of BSI. BMD for the whole body, hip, and spine was standardized using z scores on dual-energy x-ray absorptiometry. High-resolution peripheral quantitative computed tomography was used to quantify bone microarchitecture at the radius and distal tibia. Participants completed surveys characterizing factors that influence bone health-including sleep, menstrual history, and eating behaviors-utilizing the Eating Disorder Examination Questionnaire (EDE-Q). Each participant completed a biomechanical assessment using an instrumented treadmill to measure load rates before and after a run to exertion. Women with a history of high-risk BSI had lower spine z scores than those with low-risk BSI (-1.04 ± 0.76 vs -0.01 ± 1.15; P < .05). Women with a history of high-risk BSI, compared with low-risk BSI and no BSI, had the highest EDE-Q subscores for Shape Concern (1.46 ± 1.28 vs 0.76 ± 0.78 and 0.43 ± 0.43) and Eating Concern (0.55 ± 0.75 vs 0.16 ± 0.38 and 0.11 ± 0.21), as well as the greatest difference between minimum and maximum weight at current height (11.3 ± 5.4 vs 7.7 ± 2.9 and 7.6 ± 3.3 kg) (P < .05 for all). Women with a history of high-risk BSI were more likely than those with no history of BSI to sleep <7 hours on average per night during the week (80% vs 33.3%; P < .05). The mean and instantaneous vertical load rates were not different between groups. Women with a history of high-risk BSI were more likely to exhibit risk factors for poor bone health, including lower BMD, while load rates did not distinguish women with a history of BSI.

Risk dynamics in energy transition: Evaluating downside risks and interconnectedness in fossil fuel and renewable energy markets

Amidst rising concerns over climate change, the global shift from oil-powered vehicles to lithium-powered electric vehicles marks a critical pivot in the energy sector. This transition holds profound implications for the traditional dominance of oil in the energy market. This study aims to investigate the risk dynamics between the fossil fuel sector, represented by the crude oil, and the renewable energy sector, symbolized by lithium, focusing on the risk spillover and interconnectedness. The study employs a two-step approach that combines the conditional autoregressive value-at-risk (CAViaR) and time-varying parameters vector-autoregression (TVP-VAR). The study spans from January 2011 to August 2023, focusing on extreme market events like the COVID-19 pandemic and the Russia-Ukraine conflict. Findings reveal a strong tail-risk connectedness between the lithium stocks of the same country, and during extreme market events such as the COVID-19 pandemic and the Russia-Ukraine conflict, there is a strong transmission of tail risk across the lithium stocks of different countries. Moreover, a strong bidirectional tail-risk connectedness is observed between crude oil and lithium stocks. The study has important implications for portfolio managers, fund managers and investors with respect to portfolio optimization and asset allocation. Also, the findings have important implications for financial risk management with respect to energy transition from fossil fuels to renewable energy.

The impact of local government debt expansion on exports: A study based on Chinese enterprise-level data

This article establishes a multi-sector general equilibrium mathematical model, using Cobb-Douglas production and utility functions, analyzing the dynamic transmission mechanism within and between infrastructure sector, other non-trade sector and trade sector under the impact of local government debt. Besides, with data related to local government debt in China and data from Chinese industrial enterprises, it examines, from empirical perspective, the impact and transmission mechanisms of local government debt expansion on enterprise exports. The research findings indicate that, firstly, the expansion of local government debt has a significant negative impact on enterprise exports, with a stronger focus on the quantity of exports. Secondly, local government debt creates a crowding-out effect on export industries by promoting the expansion of non-trade sectors, leading to an impact on corporate exports. Finally, the financial constraint effect is an important transmission mechanism through which local government debt affects corporate exports. These conclusions have significant practical implications for risk management and control of local government debt, financial management and driving economic growth through exports.

Decomposing risk spillover effect in international stock market: A novel intertemporal network topology approach

This paper investigates the intertemporal risk effects in global stock markets using a novel network topology based on relative importance analysis. The rolling time window approach identifies dynamic and asymmetric risk spillovers. The results reveal complex and asymmetric intertemporal risk spillovers in international stock markets. Europe and America are the main risk transmitters. Countries in the forecast period, receive more risk from the international stock market. Major events that generate stock market turbulence will dramatically increase intertemporal risk spillovers. These findings have implications for risk management and the stability of the international stock market.

Gendered flood risk perception and mental health of urban households in Ghana: Insights from the Oforikrom municipality

It is important to understand gendered impacts of flood risks on mental health in developing countries. This study examines the gender-differentiated impacts of flood risk on the mental health of households in Ghana. Utilizing a mixed-methods approach, we collected data through questionnaire survey and in-depth interviews. Descriptive statistics and Student's t-test were used to analyze the data. The study revealed that both male and female headed households in the communities had experienced floods and associated impacts. However, flood risk perceptions of households were gender differentiated. The independent samples t-test result shows that the difference between male and female households' perceived mental health impacts of flooding are not significantly different. The impacts, include increased stress, anxiety, depression, and post-traumatic stress symptoms. Additionally, the results show divergent coping strategies, with male headed households preferring temporal relocation and female headed households seeking support from family and friends. Further distinctions emerged in adaptation strategies, as male headed households constructed floodwalls, while female headed households opted for desilting drainage systems. The findings have theoretical and practical implications for flood risk management in urban Ghana and other developing countries, especially in sub-Saharan Africa.

Tracking the spatial footprints of extreme storm surges around the coastline of the UK and Ireland

Storm surges are the most important driver of flooding in many coastal areas. Understanding the spatial extent of storm surge events has important financial and practical implications for flood risk management, reinsurance, infrastructure reliability and emergency response. In this paper, we apply a new tracking algorithm to a high-resolution surge hindcast (CODEC, 1980–2017) to characterize the spatial dependence and temporal evolution of extreme surge events along the coastline of the UK and Ireland. We quantify the severity of each spatial event based on its footprint extremity to select and rank the collection of events. Several surge footprint types are obtained based on the most impacted coastal stretch from each particular event, and these are linked to the driving storm tracks. Using the collection of the extreme surge events, we assess the spatial distribution and interannual variability of the duration, size, severity, and type. We find that the northeast coastline is most impacted by the longest and largest storm surge events, while the English Channel experiences the shortest and smallest storm surge events. The interannual variability indicates that the winter seasons of 1989-90 and 2013–14 were the most serious in terms of the number of events and their severity, based on the return period along the affected coastlines. The most extreme surge event and the highest number of events occurred in the winter season 1989–90, while the proportion of events with larger severities was higher during the winter season 2013–14. This new spatial analysis approach of surge extremes allows us to distinguish several categories of spatial footprints of events around the UK/Ireland coast and link these to distinct storm tracks. The spatial dependence structures detected can improve multivariate statistical methods which are crucial inputs to coastal flooding assessments.

Gold-backed cryptocurrencies: A hedging tool against categorical and regional financial stress

This study evaluates the potential of gold-backed cryptocurrencies, such as Tether Gold and PAX Gold, as a hedge and safe haven against global, regional, and categorical financial stresses. Hedge and safe haven properties of gold-backed cryptocurrencies are also compared with those of gold and Bitcoin. For the analyses, dynamic conditional correlation (DCC) and quantile coherency techniques are applied to daily data from February 2020 to March 2023. The results show that Tether Gold and PAX Gold are strong safe havens against the US and equity-valuation-related financial stress but weak safe havens against global financial stress. Tether Gold is a weak safe haven against credit-related financial stress as well. Tether Gold is a strong hedge against US financial stress but a weak hedge against aggregate financial stress of developed economies and that of emerging economies. In our sample, gold-backed cryptocurrencies usually outperform gold and Bitcoin as a hedge and safe haven against financial stresses. The Quantile coherency analysis shows that Tether Gold is a hedge against low to moderate financial stress and a safe haven against extreme financial stresses. These findings have important implications for investors, risk-managers and policy makers.

Drivers of S&amp;P 500’s Profitability: Implications for Investment Strategy and Risk Management

The financial markets, shaped by dynamic forces, including macroeconomic trends and technological advancements, are influenced by a multitude of factors impacting the S&amp;P 500 stock index, a pivotal indicator in the US equity markets. This paper highlights the significance of understanding the exogenous variables affecting the index’s profitability for academics, portfolio managers, and investment professionals. Amid the global ramifications of the S&amp;P 500, particularly in combating the eroding purchasing power caused by inflation, investing in stock indexes emerges as a means to safeguard wealth. The study employs various statistical techniques, emphasizing a methodical approach to uncover influential variables, and using static regression and autoregressive models for immediate and time-lagged effects. In conclusion, the findings have broad practical implications beyond investment strategy, extending to portfolio construction and risk management. Acknowledging inherent uncertainties in financial market forecasts, future research endeavors should target long-term trends, specific influences, and the impact of exchange rate fluctuations on index evolution. Collaboration across regulatory bodies, academia, and the financial industry is underscored, holding the potential for effective risk monitoring and bolstering overall economic and financial market stability. This research serves as a foundational step towards enhancing market understanding and facilitating more efficient investment decision-making approaches.

Informationally advantaged lenders and the credit derivative market: Evidence from Loan only Credit Default Swap (LCDX)

This paper explores the informational role of the Loan Only Credit Default Index (LCDX) on the pricing of syndicated loans. Despite an extensive body of research on credit indices and loan pricing, limited studies have comprehensively assessed the complex relationship between the LCDX and individual loan spreads. Contrary to indices like the CDX, which are largely linked to corporate bonds, the LCDX directly pertains to the syndicated secured loan market, offering valuable insights about the overall credit default market and the cost of credit risk insurance. Preliminary results reveal a pronounced positive correlation between the LCDX spread and the syndicated loan spread, particularly noticeable amongst borrowers with lower credit quality. The paper highlights the LCDX's pivotal role in conveying secondary credit market information, with critical implications for credit risk management and financial regulations.

Segmenting Bitcoin Transactions for Price Movement Prediction

Cryptocurrencies like Bitcoin have received substantial attention from financial exchanges. Unfortunately, arbitrage-based financial market price prediction models are ineffective for cryptocurrencies. In this paper, we utilize standard machine learning models and publicly available transaction data in blocks to predict the direction of Bitcoin price movement. We illustrate our methodology using data we merged from the Bitcoin blockchain and various online sources. This gave us the Bitcoin transaction history (block IDs, block timestamps, transaction IDs, senders’ addresses, receivers’ addresses, transaction amounts), as well as the market exchange price, for the period from 13 September 2011 to 5 May 2017. We show that segmenting publicly available transactions based on investor typology helps achieve higher prediction accuracy compared to the existing Bitcoin price movement prediction models in the literature. This transaction segmentation highlights the role of investor types in impacting financial markets. Managerially, the segmentation of financial transactions helps us understand the role of financial and cryptocurrency market participants in asset price movements. These findings provide further implications for risk management, financial regulation, and investment strategies in this new era of digital currencies.

Occurrence of heavy metals in sanitary napkins from seven countries: Implication for risk management of female hygiene products

Chemicals in sanitary napkins are easy to enter women's bodies, as these products are in contact with the skin of vagina and vulva directly, which has strong absorption capacity. However, available information regarding the occurrence of metals in sanitary napkins and their potential hazards, remains very limited. This study measured the concentrations of As, Co, Cu, Pb, Cd, Zn, Ni and Cr in sanitary napkins collected from seven countries. Moderate levels of Pb, Cd, Zn and Cr and lower levels of other metals were found, in comparison to the metal concentrations reported for other products previously. Metal concentrations differed by producer, price and fragrance. These metals were originated mainly from the introduction of raw materials and the use of chemical additives during the manufacturing process. Relative to other skin-contacted products, the sanitary napkin contributed more to women's total metal exposure, although the exposure was lower than that of dietary intake. The summed non-carcinogenic risks from six metals and the carcinogenic risks from Pb were acceptable. However, more research is required to investigate metals in sanitary napkins and the associated health risks to women, owing to the variability in the metal concentrations and the complexity of actual exposure.

Modeling high-frequency financial data using R and Stan: A bayesian autoregressive conditional duration approach

In econometrics, Autoregressive Conditional Duration (ACD) models use high-frequency economic or financial duration data, which mostly exhibit irregular time intervals. The ACD model is widely used to examine the duration of transaction volume and duration of price variations in stock markets. In this work, our goal is to devise testing that will aid in the identification of the best potential duration model among a set of four models using Bayesian approach. We test three models that rely on conditional mean duration (Weibull ACD, Log Weibull ACD, Generalized Gamma ACD) and one conditional median duration model (Birnbaum-Saunders ACD), and are being compared each other. The study was done in Rstan, a programming language for statistical inference, and the simulation uses the Hamiltonian Monte Carlo (HMC) algorithm of Markov Chain Monte Carlo (MCMC) to sample from the posterior distribution. Our findings show that Log Weibull ACD (second-generation model) as best among the four models followed by Birnbaum-Saunders ACD (third-generation model). The result offers methodological implications for algorithmic trading (algo-trading), high-frequency trading and risk management.

Board gender diversity, firm risk, and the intermediate mechanisms: A meta‐analysis

AbstractResearch questionThe primary focus of this meta‐analysis is to synthesize previously discordant findings on the relationship between board gender diversity (BGD) and different types of firm risk and to explore potential moderating and mediating mechanisms underlying these relationships.Research findingsWe statistically combine the results from 193 studies and find a negative association between BGD and firm risk. Further investigation indicates that different measures of risk lead to systematically different effect sizes. Our meta‐analysis structural equation modeling (MASEM) analysis reveals that BGD's impact on risk operates primarily through the monitoring rather than advising function of the board. Regarding the moderating role of national institutions, we find that several aspects of the national institutional context (e.g., investor protection, gender equality, and national culture) influence the relationship between BGD and different types of risk.Theoretical implicationsOverall, our results suggest that agency theory has more explanatory power than resource dependence theory for understanding the association between BGD and risk, and women's board representation is more likely to reduce downside risk than upside risk. Our moderating effect analysis also highlights interesting avenues for further research on the interplay of BGD and different risks in national environments with varying institutional attributes.Practitioner/policy implicationsOur meta‐analysis offers important practical implications for corporate risk management, suggesting that BGD significantly mitigates downside risks associated with poor corporate transparency without stifling board support for corporate decisions shaping future growth potential. In an era of rising board vulnerability to litigation for insufficient transparency, this study contributes evidence supporting trends toward greater gender diversity.

What do we know about COVID-19 media coverage and African stock markets? A time-varying connectedness analysis

ABSTRACT In this study, we explore the role of media coverage in the connectedness between African stock markets during the COVID-19 pandemic. Using the time-varying parameter autoregression connectedness metric and the Media Coverage Index (MCI), we analyse return and volatility connectedness between African stocks from January 2020 to October 2022. Our findings reveal that the MCI significantly drives risk transmission and financial market contagion from the global market to African markets. We document a peak in return (volatility) connectedness at 73% (55%) during the height of the pandemic in March 2020. The MCI transmits return shocks to all African stock markets except South Africa and Botswana, and volatility spillovers to all African markets. Our analysis suggests potential diversification attributes for stocks from Ghana, Mauritius, and Nigeria, which are strictly net receivers throughout the pandemic period. These findings have important implications for risk management, asset allocation, and market regulation decisions.