Risk Measures Research Articles

Risk of cancer in relatives of patients with myelodysplastic neoplasia and acute leukemias

BackgroundThe risk of cancer among relatives of patients with either myelodysplastic neoplasia (MDS), acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) has not been thoroughly examined. MethodsWe linked the Danish Civil Registration System with the Danish Cancer Registry, the Danish National Acute Leukemia Registry, and the Danish Myelodysplastic Syndrome Database to estimate the relative risk of cancer among relatives of patients with MDS/AML/ALL. We used standardized incidence ratios (SIRs), i.e., the ratio of observed to expected number of cancers among the relatives as a measure of relative risk. ResultsWe identified 13010 first-degree (FDR) and 22051 second‐degree (SDR) relatives of 8386 patients with MDS/ALL/AML. Disregarding basal cell carcinoma (BCC), the relative risk for cancer overall was increased in both FDR (SIR=1.3; 95% confidence interval (CI) 1.1–1.4) and SDR (SIR=1.5; 95% CI 1.2–1.8). SIRs among FDRs were statistically significantly increased for malignant melanoma, BCC and for the combined groups of cancers of the male genital organs, urinary tract, and MDS/AML/ALL. Among SDRs, SIRs were statistically significantly increased for malignant melanoma, BCC, and cancers in the digestive organs and peritoneum. ConclusionsWe observed an increased risk of cancer among FDR and SDR of patients with MDS/AML/ALL.

Analysing Risk & Return Profiles: A Comparative Study of the Indonesian Stock Market against International Benchmarks

The Indonesian stock market, also known as IDX, has emerged as a prominent player in the financial landscape of Southeast Asia. It has attracted the interest of investors who regard it as a potential source of massive returns. Nevertheless, empirical research has consistently demonstrated that developing nations’ stock markets tend to exhibit a notable degree of volatility. This volatility is well recognised for its propensity to amplify risk levels for domestic investors, potentially leading to a decrease in the demand for stock market investments. The observed phenomenon in Indonesia reveals a very low degree of stock market engagement when compared to benchmark nations. This suggests that the high volatility in the market may be a contributing factor. Understanding the risk-return characteristics of the IDX in comparison to recognised benchmark indexes is crucial for making educated investment decisions. This study will conduct a comparative analysis of the risk-return attributes of the IDX in comparison to six well recognised benchmark indexes, specifically the S&P 500 Index, the Straits Times Index, the FTSE 100 Index, the Shanghai Stock Exchange Composite, the BSE Sensex, and the BOVESPA Index. The study employs several risk and return measures, such as standard deviation, coefficient of variation, and the Sharpe ratio, to assess the relative performance of the IDX. The objective of this study is to evaluate the comparative appeal of the Indonesian stock market when compared to international benchmarks, with a specific focus on risk and return. The aim is to determine the optimal level of stock market involvement and the inclination towards risk aversion or risk-seeking behaviour among retail investors in Indonesia.

Enhancing betting against beta with stochastic dominance

The performance of the widely used betting-against-beta (BAB) investment strategy is improved by controlling for the stochastic dominance (SD) relation between individual stocks and the market portfolio. Dominating stocks, preferred by all risk-averse and prudent investors, are excluded from the short leg of the BAB strategy. Stocks that are dominated by the market are excluded from the long leg of the strategy. This prefiltering significantly enhances a wide range of performance and risk measures including abnormal returns relative to various factor models. The improvements are especially pronounced for the third-order SD, are robust to transaction costs and different market conditions.

Well-posedness and regularity of mean-field backward doubly stochastic Volterra integral equations and applications to dynamic risk measures

In this paper, the theory of mean-field backward doubly stochastic Volterra integral equations (MF-BDSVIEs) is studied. First, we derive the well-posedness of M-solutions to MF-BDSVIEs, and prove the comparison theorem for such a type of equations. Furthermore, the regularity result of the M-solution for MF-BDSVIEs is established by virtue of Malliavin calculus. Finally, as an application of the comparison theorem, we obtain the properties of dynamic risk measures governed by MF-BDSVIEs.

Cooperative Investment Problem With an Authoritative Risk Determined by Central Bank

In this paper, we are interested in providing an analytic solution for cooperative investment risk. We reformulate cooperative investment risk by writing dual representations for each risk preference (Coherent risk measure). Finding an analytic solution for this problem for both cases individual and cooperative investment by using dual representation for each risk preference has a strong effect on the financial market. In addition, we formulate a problem that covers the risk minimization with an expected return maximization problem with risk constraint, for the general case of an arbitrary joint distribution for the asset return under certain conditions and assuming that all coherent risk measure is continuous from below. Thus, the optimal portfolio is written as the optimal Lagrange multiplier associated with an equality-constrained dual problem. Furthermore, a unique equilibrium allocation as a fair optimal allocation solution in terms of equilibrium price density function for each agent is also shown.

The effect of margin-trading and short-selling mechanism on left-tail risk: Evidence from a quasi-natural experiment in China

This research investigates the influence of a margin-trading and short-selling pilot program on the left-tail risk of equities, utilizing A-share stock data in China from January 2004 to July 2020 as a sample. By exploiting the staggered implementation of the pilot program within a difference-in-differences framework, we examine the impact of margin-trading and short-selling mechanism on left-tail risks of equities in China. Firstly, we present empirical evidence that the introduction of margin-trading and short-selling mechanism can significantly mitigate the left-tail risk for the designated stocks. In particular, the effect is mainly from short-selling activities. Secondly, the empirical evidence suggests that the presence of information asymmetry among investors plays a mediating role in the mitigating impact. Thirdly, the findings demonstrate that mitigating effect of the mechanism is particularly pronounced during periods characterized by high investor sentiment and high levels of economic policy uncertainty. Additionally, results are robust to DID models when shell value contamination is removed, an alternative time period and measure of left-tail risk are considered, and placebo tests are conducted.

A New Coherent Risk Measure of Entropic Value at Risk for Uncertain Systems

Uncertain risk analysis was initially explored by Liu, who introduced the concepts of loss function and risk index within uncertainty theory. Various risk measures, such as value at risk (VaR), tail VaR (TVaR), expected loss and entropic VaR (EVaR), have been proposed within probability theory. To date, Peng extended the concepts of VaR and TVaR, while Liu and Ralescu extended the notion of expected loss for uncertain systems. This paper mainly extends the concept of EVaR as a novel uncertain coherent risk measure. It will be demonstrated as the tightest upper bound one can find using Chernoff inequality for the VaR. In addition, we verify the properties of EVaR under uncertain measure, including positive homogeneity, translation invariance, monotonicity and subadditivity under independence. Furthermore, this paper provides a comparison of VaR, TVaR and EVaR under uncertain measure. Two examples will be given to illustrate this comparison.

Risk assessment in cryptocurrency portfolios: a composite hidden Markov factor analysis framework

In this paper, we deal with the estimation of two widely used risk measures such as Value-at-Risk (VaR) and Expected Shortfall (ES) in a cryptocurrency context. To face the presence of regime switching in the cryptocurrency volatilities and the dynamic interconnection between them, we propose a Monte Carlo-based approach using heteroskedastic factor analysis and hidden Markov models (HMM) combined with a structured variational Expectation-Maximization (EM) learning approach. This composite approach allows the construction of a diversified portfolio and determines an optimal allocation strategy making it possible to minimize the conditional risk of the portfolio and maximize the return. The out-of-sample prediction experiments show that the composite factorial HMM approach performs better, in terms of prediction accuracy, than some other baseline methods presented in the literature. Moreover, our results show that the proposed methodology provides the best performing crypto-asset allocation strategies and it is also clearly superior to the existing methods in VaR and ES predictions.

Carbon Risk Assessment in Investing Decision-Making: The Role of Carbon Pricing Policies

This study looks thoroughly into the important relationship between carbon risk assessment and investment decision-making, with a specific emphasis on the consequences of various carbon pricing regimes. Understanding how carbon risk and pricing regulations effect investment portfolios is critical in todays world, when environmental sustainability and battling climate change are vital. To clarify the topic, the study conducts a thorough assessment of current research, evaluating the several ways in which carbon price influences investment decisions. It also offers light on carbon risk measurement approaches and frameworks, providing critical insights into the complexity of environmental economics. Furthermore, the paper adds empirical case studies to its narrative, offering real-world context to theoretical frameworks and shining light on the actual implications of carbon risks and price on investment strategies. The findings are useful for investors, policymakers, and scholars attempting to navigate the complex environment of sustainable investing in a carbon-constrained society.

Systemic risk measurement: A Quantile Long Short-Term Memory network approach

In finance, systemic risk is the risk that the crisis of an institution could trigger instability or bring down an entire system or market. The Delta Conditional Value-at-Risk is a market-based measure proposed by the recent literature to quantify the systematicity of some financial institutions. Several methods have been proposed to estimate this measure, and the choice of the best method is still an open question. The bivariate constant conditional correlation GARCH model represents one of the most preferred approaches since it allows the computation of the Delta Conditional Value-at-Risk in a closed form. Nevertheless, it requires strong distributional assumptions that are often considered unrealistic. We develop a Quantile Long Short-Term Memory network approach that allows the estimation of the Delta Conditional Value-at-Risk of several financial institutions simultaneously. The model consists of a multi-output neural network able to provide, at the same time, the log-return quantiles of different institutions useful to measure the systemic risk. Furthermore, the proposed model does not need any particular assumption, and it is specifically designed to avoid quantile crossing issues affecting the traditional quantile regression-based approach. Numerical experiments on data of some global systemically important banks reported in the Financial Stability Board validated our approach. We obtain Delta Conditional Value-at-Risk estimates that accurately capture market dynamics and produce a ranking of systemic banks that meets the desired properties of stability and persistence.

Allocation of Portfolio Risk and Outside Options: Which is the Best Coalition Structure Value to Solve the Low-Risk Anomaly?

In this paper, we enhance the application of coalition structure (CS) games to the distribution of portfolio risk across individual assets in a portfolio. In a recent paper, CS games were applied for the first time as a risk measure that takes into account the contributions of individual assets to portfolio risk and contributions to the risk of the stock market as a whole. We enhance this approach by using five values for CS games in a simulation study. In this simulation, it can be shown that using CS games has an even higher potential to solve the so-called low-risk puzzle than shown in previous literature.

CEO power and stock price crash risk in India: the moderating effect of insider trades

PurposeThis study aims to explore the relationship between chief executive officer (CEO) power and stock price crash risk in India. Furthermore, it seeks to analyse how insider trades may moderate the impact of CEO power on stock price crash risk.Design/methodology/approachA study of 236 companies from the S&P BSE 500 Index (2014–2023) have been analysed through pooled ordinary least square (OLS) regression in the baseline analysis. To enhance the results' reliability, robustness checks include alternative methodologies, such as panel data regression with fixed-effects, binary logistic regression and Bayesian regression. Additional control variables and alternative crash risk measure have also been utilised. To address potential endogeneity, instrumental variable techniques such as two-stage least squares (IV-2SLS) and difference-in-difference (DiD) methodologies are utilised.FindingsStakeholder theory is supported by results revealing that CEO power proxies like CEO duality, status and directorship reduce one-year ahead stock price crash risk and vice versa. Insider trades are found to moderate the link between select dimensions of CEO power and stock price crash risk. These findings persist after addressing potential endogeneity concerns, and the results remain consistent across alternative methodologies and variable inclusions.Originality/valueThis study significantly advances research on stock price crash risk, especially in emerging economies like India. The implications of these findings are crucial for investors aiming to mitigate crash risk, for corporations seeking enhanced governance measures and for policymakers considering the economic and welfare consequences associated with this phenomenon.

Short Communication: Are Shortfall Systemic Risk Measures One Dimensional?

Short Communication: Are Shortfall Systemic Risk Measures One Dimensional?

Increasing Access to Medical Care for Hispanic Women Without Insurance: A Mobile Clinic Approach.

The purpose of this study was to describe the health status and barriersof people who sought care on a freemobile health clinic for women without insurance in California.Participants were 221 women who attended the Salud para Mujeres (Women's Health) mobile medical clinic between 2019 and 2021. Medical chart abstractions provided data on sociodemographic factors, medical history, barriers to care, depressive symptoms, anddietary factors. Anthropometric measure, blood pressure, and biomarkers of cardiometabolic disease risk were also abstracted.Participants were young adult (29.1 [SD 9.3] years), Hispanic (97.6%), farm-working (62.2%) women from Mexico (87.0%). Prevalent barriers to accessing (non-mobile) medical care included high cost (74.5%), language (47.6%), hours of operation (36.2%), and transportation (31.4%). The majority (89.5%) of patientshad overweight (34.0%) or obesity (55.5%), and 27% had hypertension. Among those (n = 127) receiving a lipid panel, 60.3% had higher than recommended levels of low-density lipoprotein and 89% had lower than recommended levels of high-density lipoprotein. Point-of-care HbA1c tests (n = 133) indicated that 9.0% had diabetes and 24.8% had prediabetes. Over half (53.1%) of patients reported prevalent occupational exposure to pesticides and 19% had moderate to severe depressive symptoms. Weekly or more frequent consumption of sugar sweetened beverages (70.9%) and fast food (43.5%) were alsoprevalent.Mobile health units have potential for reaching women who face several barriers to care and experience major risk factors for cardometabolic disease. Findings suggest a compelling need to assure that Hispanic and Indigenous women and farmworkers have access to healthcare.

The Xpert® MTB/RIF cycle threshold value predicts M. tuberculosis transmission to close contacts in a Brazilian prospective multicenter cohort.

The Xpert® MTB/RIF rapid molecular test provides a quantitative measure of Mycobacterium tuberculosis (Mtb) DNA in the form of cycle threshold (Ct) values. This information can be translated into mycobacterial load and used as a potential risk measure of bacterial spread for tuberculosis cases, which can impact infection control. However, the role of Ct values in assessing Mtb transmission to close contacts has not yet been demonstrated. A prospective study was performed to investigate the association between Xpert® MTB/RIF Ct values and Mtb transmission to close contacts of patients with culture-confirmed pulmonary TB in a multi-center Brazilian cohort. We evaluated clinical and laboratory data, such as age, sex, race, smoking habits, drug use, alcohol use, chest radiograph, Xpert® MTB/RIF results among pulmonary tuberculosis cases, and QuantiFERON(QFT)-Plus results at baseline and after six months for close contacts who had a negative result at baseline. A total of 1,055 close contacts of 382 pulmonary tuberculosis cases were included in the study. The median Ct values from pulmonary tuberculosis cases of QFT-Plus positive (at baseline or six months) close contacts were lower compared with those who were QFT-Plus negative. An adjusted logistic regression demonstrated that reduced Ct values from the index cases were independently associated with QFT-Plus conversion from negative to positive (OR: 1.61, 95% CI: 1.12-2.32) after adjusting for clinical characteristics. Close contacts of pulmonary TB index cases exhibiting low Xpert MTB/RIF Ct values displayed higher rates of TB infection, reflecting Mtb transmission.

Adjusted higher-order expected shortfall

How to detect different tail behaviors of two risk random variables with the same mean is an important task. In this paper, motivated by Burzoni et al. (2022), a class of convex risk measures, referred to as adjusted higher-order Expected Shortfall (ES), is introduced and studied. The adjusted risk measure quantifies risk as the minimum amount of capital that has to be raised and injected into a financial position to ensure that its higher-order ES does not exceed a pre-specified threshold for every probability level. This new risk measure is intimately linked to dual higher-order increasing convex order by choosing the risk threshold to be the higher-order ES of a special benchmark random loss. The dual representation for (adjusted) higher-order Expected Shortfall is also given.

Heterogeneous correlate and potential diagnostic biomarker of tinnitus based on nonlinear dynamics of resting-state EEG recordings.

Tinnitus is a heterogeneous condition of hearing a rattling sound when there is no auditory stimulus. This rattling sound is associated with abnormal synchronous oscillations in auditory and non-auditory cortical areas. Since tinnitus is a highly heterogeneous condition with no objective detection criteria, it is necessary to search for indicators that can be compared between and within participants for diagnostic purposes. This study introduces heterogeneous though comparable indicators of tinnitus through investigation of spontaneous fluctuations in resting-state brain dynamics. The proposed approach uses nonlinear measures of chaos theory, to detect tinnitus and cross correlation patterns to reflect many of the previously reported neural correlates of tinnitus. These indicators may serve as effective measures of tinnitus risk even at early ages before any symptom is reported. The approach quantifies differences in oscillatory brain dynamics of tinnitus and normal subjects. It demonstrates that the left temporal areas of subjects with tinnitus exhibit larger lyapunov exponent indicating irregularity of brain dynamics in these regions. More complex dynamics is further recognized in tinnitus cases through entropy. We use this evidence to distinguish tinnitus patients from normal participants. Besides, we illustrate that certain anticorrelation patterns appear in these nonlinear measures across temporal and frontal areas in the brain perhaps corresponding to increased/decreased connectivity in certain brain networks and a shift in the balance of excitation and inhibition in tinnitus. Additionally, the main correlations are lost in tinnitus participants compared to control group suggesting involvement of distinct neural mechanisms in generation and persistence of tinnitus.

Agricultural drought risk and local adaptation measures in the Upper Mun River Basin, Thailand

Northeast Thailand is one of the country's important agricultural regions. Yet, it is frequently grappled by droughts affecting crop production as most of the cultivation depends on rain-fed irrigation. This study employs a comprehensive framework for assessing the drought risk in the Mun River basin, including hazard, exposure, and vulnerability factors. Hazard is estimated using a multivariate approach considering drought duration and severity, while exposure and vulnerability are evaluated using eighteen proxy factors encompassing physical and socioeconomic aspects. Local adaptation measures adopted by farmers to cope with droughts are an integral part of the risk assessment framework. Factors are normalized to five equally spaced categories and are aggregated using weights obtained from AHP through a survey among 50 local experts. Further, an extensive survey was conducted among 122 farmers in two hotspots with high hazards but contrasting vulnerability to investigate adaptation practices. Experts in the region perceive a higher importance of adaptive capacity than drought susceptibility while defining vulnerability. The results show that people living in areas with high hazard levels and physical vulnerability also tend to have a higher adaptive capacity to manage water scarcity. Overall, 22% of the area is under high to very high drought risk. Specifically, 14% of the area in Nakhon Ratchasima, 15% in Buriram, 8% in Surin, and 19% in Si Sa Ket provinces have very high risk. Among two hotspots, Dan Khun Thot district farmers have diversified crops and practiced various adaptive measures to build their resilience against drought and have low vulnerability and risk. In contrast, adaptation measures are implemented to a far lesser extent in the Phlapphla Chai district and have high vulnerability and risk. The education level of farmers is found to be directly linked with the implementation of local adaptation measures. The disparity in the adaptive measures adopted in two districts highlights the significance of agricultural water management interventions. Access to climate information regarding droughts, building farm ponds, and crop management practices are the preferred adaptation measures taken by the farmers. The study recommends districts in each province identified as having high risk are prioritized and supported by the local government to improve farm-level water management practices and drought resilience. It is imperative as looming climate change will further exacerbate future droughts.

Prognostic value of home versus ambulatory blood pressure monitoring: a systematic review and meta-analysis of outcome studies.

Ambulatory (ABP) and self-home blood pressure (HBP) measurements are known to be superior to office blood pressure (OBP) measurements in predicting cardiovascular events. Whether ABP has superior prognostic ability than HBP, or the reverse, has not been adequately investigated. A systematic literature search was conducted to identify outcome studies investigating HBP and ABP in the same population. A meta-analysis was conducted to calculate the pooled measure of risk regarding the primary endpoint of each study for each method. Primary analysis included the comparison of pooled estimates of HBP versus 24 h ABP. Among 2587 articles retrieved, 6 fulfilled the inclusion criteria. Meta-analysis of five studies ( n = 4439, weighted age 57 years, men 52%, hypertension 68%, diabetes 15%, cardiovascular disease 11%) indicated pooled hazard ratio per 10 mmHg increase in systolic HBP 1.36 (95% CI 1.23-1.50) and in 24 h ABP 1.38 (1.22-1.57) for the primary endpoint of each study ( z -test P = NS). Meta-analysis of five studies ( n = 4497, weighted age 58 years, men 51%, hypertension 65%, diabetes 15%, cardiovascular disease 9%) indicated pooled hazard ratio per 10 mmHg increase in systolic HBP 1.29 (1.14-1.47), daytime ABP 1.30 (1.15-1.46) and nighttime ABP 1.31 (1.14-1.50) ( z -test, P = NS). Data for DBP were similar. All studies were deemed to have low risk of bias. In studies comparing all the three methods, OBP provided the lowest hazard ratio. This meta-analysis of the available prospective outcome studies suggested that HBP and ABP have similar ability in predicting outcome and superior to OBP.

Risk Management and Financial Performance of Commercial Banks in Nigeria.

This study establishes the degree to which risk management has impacted profitability of commercial banks with the aim of contributing to improving the financial performance improvement. This study used secondary data from listed banks extracted from Central Bank of Nigeria list of financial institutions. The study was 2012 to 2021. The sample size of fourteen commercial banks in Nigeria was utilized for the study. Data were analysed using descriptive, Pearson correlation, r and Multiple linear regression (ANOVA) r statistical analysis. Findings were that the Pearson results posted significant relationships among credit risk, operational risk as measures of risks with profitability measures of net interest margin except the liquidity risk. The linear regression result indicated that Credit risk has significant effect on Net interest margin. However, there is no significant effect of liquidity and operation risk on net interest margin of commercial banks in Nigeria. The findings suggest that effective risk management strategy play a key role in commercial banks profitability in Nigeria. Therefore, this study recommended that effective risk management framework to improve financial performance.