General Risk Model Research Articles

Impact of childhood adversity on corticolimbic volumes in youth at clinical high-risk for psychosis

Childhood adversity is among the strongest risk factors for psychosis-spectrum disorders, though the nature and specificity of the biological mechanisms underlying this association remains unclear. Previous research reveals overlaps in the volumetric alterations observed in both adversity-exposed individuals and in psychosis-spectrum populations, highlighting the possibility that deviations in corticolimbic gray matter development may be one mechanism linking adversity and psychosis. Given that childhood adversity encompasses a wide range of adverse experiences, there is also a critical need to examine whether these different types of experiences have unique effects on corticolimbic regions. This study examined the association between childhood adversity and cortical, hippocampal, and amygdalar volume in a large sample of youth at clinical-high risk (CHR) for psychosis. We utilized a novel differentiated adversity approach that distinguishes exposures along dimensions of threat (e.g., abuse) and deprivation (e.g., poverty, neglect) to test for differential associations. Participants were drawn from the North American Prodromal Longitudinal Study (NAPLS) and completed an MRI scan and a retrospective assessment of childhood adversity at baseline. We found that deprivation exposure, but not threat, was uniquely associated with smaller cortical volume and smaller right hippocampal volume in CHR youth. These associations were masked in a generalized risk model that utilized a total adversity score. The findings suggest that deprivation exposures during childhood contribute to the subtle volumetric reductions observed in clinical high-risk samples and highlight the importance of disentangling different dimensions of adversity.

Which obesity index is the best predictor for high cardiovascular disease risk in middle-aged and elderly population?

Background and aimsThe aim was to investigate the relationships between visceral fat rating scale (VFR), waist circumference (WC), body mass index (BMI) and cardiovascular disease (CVD) risk. MethodsIn this cross-sectional, community-based study, participants completed questionnaire that included personal and medical history, and underwent anthropometric measurement and blood sampling. The 2008 general CVD risk model was used to predict CVD risk. Associations between CVD risk and VFR, WC, BMI were evaluated by means of analysis of covariance (ANCOVA) with gender as covariate, Chi-squared test, Pearson’s correlation, Cochran-Armitage test, multivariate logistic regression and receiver operating characteristic curves. ResultsA total of 377 people were enrolled. A significant association was identified between VFR, WC, BMI, and CVD risk, with coefficient of determination (r2) of 0.32 (p < 0.001), 0.18 (p < 0.001) and 0.03 (p = 0.001), respectively. There was a trend toward increasing prevalence of high CVD risk as VFR, WC, and BMI increased (all p values <0.05). Multivariate logistic regression revealed VFR (OR = 1.21; 95%CI = 1.02–1.24), WC (OR = 1.07; 95%CI = 1.04–1.11) and BMI (OR = 1.11; 95%CI = 1.02–1.21) to be independent predictors of high CVD risk. In male, the area under curves of VFR and WC are greater than BMI: 0.641, 0.647 and 0.562. In female, the area under curves of VFR and WC are also greater than BMI: 0.656, 0.688 and 0.601. ConclusionsVFR and WC were more strongly associated with high CVD risk than BMI among middle-aged and elderly persons in Taiwan.

Dividends: From Refracting to Ratcheting

In this paper we consider an alternative dividend payment strategy in risk theory, where the dividend rate can never decrease. This addresses a concern that has often been raised in connection with the practical relevance of optimal classical dividend payment strategies of barrier and threshold type. We study the case where once during the lifetime of the risk process the dividend rate can be increased and derive corresponding formulae for the resulting expected discounted dividend payments until ruin. We first consider a general spectrally-negative Levy risk model, and then re fine the analysis for a diffusion approximation and a compound Poisson risk model. It is shown that for the diffusion approximation the optimal barrier for the ratcheting strategy is characterized by an unexpected relation to the case of refracted dividend payments. Finally, numerical illustrations for the diffusion case indicate that with such a simple ratcheting dividend strategy the expected value of discounted dividends can already get quite close to the respective value of the refracted dividend strategy, the latter being known to be optimal among all admissible dividend strategies.

A Characterization of Exponential Distribution in Risk Model

In the general risk model (or the Sparre-Andersen model), it is well-known that the following assertion holds: if the claim size is exponentially distributed then the non-ruin probability distribution is a mixture of exponential distributions. In this paper, under some general conditions, we prove that the converse statement of the previous assertion is also true. Besides, we define a new non-ruin measure associated with the aggregate logarithms of the claim-over-profit ratios and obtain a result on Pareto-type distributions.

Risks of Allergic Contact Dermatitis Elicited by Nickel, Chromium, and Organic Sensitizers: Quantitative Models Based on Clinical Patch Test Data.

Risks of allergic contact dermatitis (ACD) from consumer products intended for extended (nonpiercing) dermal contact are regulated by E.U. Directive EN 1811 that limits released Ni to a weekly equivalent dermal load of ≤0.5μg/cm2 . Similar approaches for thousands of known organic sensitizers are hampered by inability to quantify respective ACD-elicitation risk levels. To help address this gap, normalized values of cumulative risk for eliciting a positive ("≥+") clinical patch test response reported in 12 studies for a total of n = 625 Ni-sensitized patients were modeled in relation to observed ACD-eliciting Ni loads, yielding an approximate lognormal (LN) distribution with a geometric mean and standard deviation of GMNi = 15μg/cm2 and GSDNi = 8.0, respectively. Such data for five sensitizers (including formaldehyde and 2-hydroxyethyl methacrylate) were also ∼LN distributed, but with a common GSD value equal to GSDNi and with heterogeneous sensitizer-specific GM values each defining a respective ACD-eliciting potency GMNi /GM relative to Ni. Such potencies were also estimated for nine (meth)acrylates by applying this general LN ACD-elicitation risk model to respective sets of fewer data. ACD-elicitation risk patterns observed for Cr(VI) (n = 417) and Cr(III) (n = 78) were fit to mixed-LN models in which ∼30% and ∼40% of the most sensitive responders, respectively, were estimated to exhibit a LN response also governed by GSDNi . The observed common LN-response shape parameter GSDNi may reflect a common underlying ACD mechanism and suggests a common interim approach to quantitative ACD-elicitation risk assessment based on available clinical data.

Precise local large deviations for heavy-tailed random sums with applications to risk models

In this paper, we investigate the precise local large deviation probabilities for random sums of independent real-valued random variables with a common heavy-tailed distribution F, where is an -regularly varying function for some fixed constant (finite or infinite). We also obtain some results on precise local large deviation probabilities for the claim surplus process of generalized risk models in which the premium income until time t is simply assumed to be a nondecreasing and nonnegative stochastic process. In particular, the results we obtained are also valid for the global case, i.e. case .

Planning Risk-Based Statistical Quality Control Strategies: Graphical Tools to Support the New Clinical and Laboratory Standards Institute C24-Ed4 Guidance.

Clinical and Laboratory Standards Institute (CLSI)'s new guideline for statistical quality control (SQC; C24-Ed4) (CLSI C24-Ed4, 2016; Parvin CA, 2017) recommends the implementation of risk-based SQC strategies. Important changes from earlier editions include alignment of principles and concepts with the general patient risk model in CLSI EP23A (CLSI EP23A, 2011) and a recommendation for optimizing the frequency of SQC (number of patients included in a run, or run size) on the basis of the expected number of unreliable final patient results. The guideline outlines a planning process for risk-based SQC strategies and describes 2 applications for examination procedures that provide 9-σ and 4-σ quality. A serious limitation is that there are no practical tools to help laboratories verify the results of these examples or perform their own applications. Power curves that characterize the rejection characteristics of SQC procedures were used to predict the risk of erroneous patient results based on Parvin's MaxE(Nuf) parameter (Clin Chem 2008;54:2049-54). Run size was calculated from MaxE(Nuf) and related to the probability of error detection for the critical systematic error (Pedc). A plot of run size vs Pedc was prepared to provide a simple nomogram for estimating run size for common single-rule and multirule SQC procedures with Ns of 2 and 4. The "traditional" SQC selection process that uses power function graphs to select control rules and the number of control measurements can be extended to determine SQC frequency by use of a run size nomogram. Such practical tools are needed for planning risk-based SQC strategies.

Asymptotics for the finite-time ruin probability of a risk model with a general counting process

This paper considers a general risk model. In this risk model there does not need independent or dependent assumption on the inter-arrival times. When the claim sizes have the WUOD structure, the asymptotics of the finite-time ruin probability of this risk model have been given. The obtained results extend and improve some existed results.

Examining temporal effects on cancer risk in the international nuclear workers' study.

The paper continues the series of publications from the International Nuclear Workers Study cohort that comprises 308,297 workers from France, the United Kingdom and the United States, providing 8.2 million person-years of observation from a combined follow-up period (at earliest 1944 to at latest 2005). These workers' external radiation exposures were primarily to photons, resulting in an estimated average career absorbed dose to the colon of 17.4 milligray. The association between cumulative ionizing radiation dose and cancer mortality was evaluated in general relative risk models that describe modification of the excess relative risk (ERR) per gray (Gy) by time since exposure and age at exposure. Methods analogous to a nested-case control study using conditional logistic regression of sampled risks sets were used. Outcomes included: all solid cancers, lung cancer, leukemias excluding chronic lymphocytic, acute myeloid leukemia, chronic myeloid leukemia, multiple myeloma, Hodgkin lymphoma and non-Hodgkin lymphoma. Significant risk heterogeneity was evident in chronic myeloid leukemia with time since exposure, where we observed increased ERR per Gy estimates shortly after exposure (2-10 year) and again later (20-30 years). We observed delayed effects for acute myeloid leukemia although estimates were not statistically significant. Solid cancer excess risk was restricted to exposure at age 35+ years and also diminished for exposure 30 years prior to attained age. Persistent or late effects suggest additional follow-up may inform on lifetime risks. However, cautious interpretation of results is needed due to analytical limitations and a lack of confirmatory results from other studies.

Closed-Form Absolute Ruin Problems of the Risk Models with State-Dependent Switched Claims

This letter mainly investigates a general risk model with the threshold dividend strategy under assumption that the claim amounts obey a state-dependent switched exponential distribution. By establishing the differential-integral equations for the Gerber-Shiu discounted penalty function, and applying the hypergeometric functions, the closed-form absolute ruin probability is derived.

Path-consistent wrong-way risk: a structural model approach

We present a general and path-consistent wrong-way risk (WWR) model, which does not require simulation of credit and market variables simultaneously. Although similar so-called copula models are well known, our approach is novel in several ways. First, our method can model a wide range of dependence structures while always guaranteeing path consistency of default probabilities (the possibility of path-inconsistencies in copula models was highlighted in a recent article). Second, we place special emphasis on the difficult task of calibrating the underlying dependence structure. In particular, we consider a default correction of the dependence structure. Third, our model serves as a bridge between structural model approaches, where dependence between exposure and equity price is modeled, and copula models, where exposure is directly correlated to default time. Finally, we apply our method in realistic situations and show that we can achieve a wide range of WWR impacts.

A class of nonzero-sum investment and reinsurance games subject to systematic risks

Recently, there have been numerous insightful applications of zero-sum stochastic differential games in insurance, as discussed in Liu et al. [Liu, J., Yiu, C. K.-F. & Siu, T. K. (2014). Optimal investment of an insurer with regime-switching and risk constraint. Scandinavian Actuarial Journal 2014(7), 583–601]. While there could be some practical situations under which nonzero-sum game approach is more appropriate, the development of such approach within actuarial contexts remains rare in the existing literature. In this article, we study a class of nonzero-sum reinsurance-investment stochastic differential games between two competitive insurers subject to systematic risks described by a general compound Poisson risk model. Each insurer can purchase the excess-of-loss reinsurance to mitigate both systematic and idiosyncratic jump risks of the inter-arrival claims; and can invest in one risk-free asset and one risky asset whose price dynamics follows the famous Heston stochastic volatility model [Heston, S. L. (1993). A closed-form solution for options with stochastic volatility with applications to bond and currency options. Review of Financial Studies 6, 327–343]. The main objective of each insurer is to maximize the expected utility of his terminal surplus relative to that of his competitor. Dynamic programming principle for this class of nonzero-sum game problems leads to a non-canonical fixed-point problem of coupled non-linear integral-typed equations. Despite the complex structure, we establish the unique existence of the Nash equilibrium reinsurance-investment strategies and the corresponding value functions of the insurers in a representative example of the constant absolute risk aversion insurers under a mild, time-independent condition. Furthermore, Nash equilibrium strategies and value functions admit closed forms. Numerical studies are also provided to illustrate the impact of the systematic risks on the Nash equilibrium strategies. Finally, we connect our results to that under the diffusion-approximated model by proving explicitly that the Nash equilibrium under the diffusion-approximated model is an -Nash equilibrium under the general Poisson risk model, thereby establishing that the analogous Nash equilibrium in Bensoussan et al. [Bensoussan, A., Siu, C. C., Yam, S. C. P. & Yang, H. (2014). A class of nonzero-sum stochastic differential investment and reinsurance games. Automatica 50(8), 2025–2037] serves as an interesting complementary case of the present framework.

First crossing time, overshoot and Appell–Hessenberg type functions

We consider a general insurance risk model with extended flexibility under which claims arrive according to a point process with independent increments, their amounts may have any joint distribution and the premium income is accumulated following any non-decreasing, possibly discontinuous, real valued function. Point processes with independent increments are in general non-stationary, allowing for an arbitrary (possibly discontinuous) claim arrival cumulative intensity function which is appealing for insurance applications. Under these general assumptions, we derive a closed form expression for the joint distribution of the time to ruin and the deficit at ruin, which is remarkable, since as we show, it involves a new interesting class of what we call Appell–Hessenberg type functions. The latter are shown to coincide with the classical Appell polynomials in the Poisson case and to yield a new class of the so called Appell–Hessenberg factorial polynomials in the case of negative binomial claim arrivals. Corollaries of our main result generalize previous ruin formulas e.g. those obtained for the case of stationary Poisson claim arrivals.

Multifactor risk models and heterotic CAPM

We give a complete algorithm and source code for constructing general multifactor risk models (for equities) via any combination of style factors, principal components (betas) and/or industry factors. For short horizons we employ the Russian-doll risk model construction to obtain a nonsingular factor covariance matrix. This generalizes the heterotic risk model construction to include arbitrary non-industry risk factors as well as industry risk factors with generic "weights". The aim of sharing our proprietary know-how with the investment community is to encourage organic risk model building. The presentation is intended to be essentially self-contained and pedagogical. So, stop wasting money and complaining, start building risk models and enjoy!

Finite difference methods for estimating marginal risk contributions in asset management

The decomposition of portfolio risks in terms of the underlying assets, which are extremely important for risk budgeting, asset allocation and risk monitoring, is well described by risk contributions. However, risk contributions cannot be calculated analytically for a considerable number of the risk models used in practice. We therefore study the use of finite difference methods for estimating risk contributions. We find that for practically relevant setups the additional estimation errors of the finite difference formulas are negligibly small. Since finite difference methods work for complex risk models and are independent of decisions about underlying distributions, we suggest the use of finite difference methods as the standard procedure for estimating risk contributions. As an application, we consider a general risk model that fits a kernel density estimation to the historical asset return distribution combined with a finite difference method in order to arrive at the risk contributions. It turns out that this general risk model combined with a finite difference method for calculating risk contributions works well in terms of estimation error.

Multifactor Risk Models and Heterotic CAPM

We give a complete algorithm and source code for constructing general multifactor risk models (for equities) via any combination of style factors, principal components (betas) and/or industry factors. For short horizons we employ the Russian-doll risk model construction to obtain a nonsingular factor covariance matrix. This generalizes the heterotic risk model construction to include arbitrary non-industry risk factors as well as industry risk factors with generic weights. The aim of sharing our proprietary know-how with the investment community is to encourage organic risk model building. The presentation is intended to be essentially self-contained and pedagogical. So, stop wasting money and complaining, start building risk models and enjoy!

A note on some joint distribution functions involving the time of ruin

In a recent paper, Willmot (2015) derived an expression for the joint distribution function of the time of ruin and the deficit at ruin in the classical risk model. We show how his approach can be applied to obtain a simpler expression, and by interpreting this expression by probabilistic reasoning we obtain solutions for more general risk models. We also discuss how some of Willmot’s results relate to existing literature on the probability and severity of ruin.

Value of E-PASS models for predicting postoperative morbidity and mortality in resection of perihilar cholangiocarcinoma and gallbladder carcinoma

BackgroundIt has previously been reported that a general risk model, Estimation of Physiologic Ability and Surgical Stress (E-PASS), and its modified version, mE-PASS, had a high predictive power for postoperative mortality and morbidity in a variety of gastrointestinal surgeries. This study evaluated their utilities in proximal biliary carcinoma resection. MethodsE-PASS variables were collected in patients undergoing resection of perihilar cholangiocarcinoma and gallbladder carcinoma in Japanese referral hospitals. ResultsAnalysis of 125 patients with gallbladder cancer and 97 patients with perihilar cholangiocarcinoma (n = 222). Fifty-six patients (25%) underwent liver resection with either hemihepatectomy or extended hemihepatectomy. The E-PASS models showed a high discrimination power to predict in-hospital mortality; areas under the receiver operating characteristic curve (95% confidence intervals) were 0.85 (0.76–0.94) for E-PASS and 0.82 (0.73–0.91) for mE-PASS. The predicted mortality rates correlated with the severity of postoperative complications (Spearman's rank correlation coefficient: ρ = 0.51, P < 0.001 for E-PASS; ρ = 0.47, P < 0.001 for mE-PASS). ConclusionsThe E-PASS models examined herein may accurately predict postoperative morbidity and mortality in proximal biliary carcinoma resection. These models will be useful for surgical decision-making, informed consent, and risk adjustments in surgical audits.

On the probability of ruin in a continuous risk model with two types of delayed claims

ABSTRACTThis article studies a risk model involving one type of main claims and two types of by-claims, which is an extension of the general risk model with delayed claims. We suppose that every main claim may not induce any by-claims or may induce one by-claim belonging to one of the two types of by-claims with a certain probability. In addition, assume that the by-claim and its associated main claim may occur at the same time and that the occurrence of the by-claim may be delayed. An integro-differential equation system for survival probabilities is derived by using two auxiliary risk models. The expression of the survival probability is obtained by applying Laplace transforms and Rouché theorem. Furthermore, we provide a method for solving the survival probability when the two by-claim amounts satisfy different exponential distributions. As a special case, an explicit expression of survival probability is given when all the claim amounts obey the same exponential distribution. Finally, numerical results are provided to examine the proposed method.

Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

This paper illustrates a dynamic model of conditional value-at-risk (CVaR) measure for risk assessment and mitigation of hazardous material transportation in supply chain networks. The well-established market risk measure, CVaR, which is commonly used by financial institutions for portfolio optimizations, is investigated. In contrast to previous works, we consider CVaR as the main objective in the optimization of hazardous material (hazmat) transportation network. In addition to CVaR minimization and route planning of a supply chain network, the time scheduling of hazmat shipments is imposed and considered in the present study. Pertaining to the general dynamic risk model, we analyzed several scenarios involving a variety of hazmats and time schedules with respect to optimal route selection and CVaR minimization. A solution algorithm is then proposed for solving the model, with verifications made using numerical examples and sensitivity analysis.