Critical Asset and Portfolio Risk Analysis: An All-Hazards Framework

This article develops a quantitative all-hazards framework for critical asset and portfolio risk analysis (CAPRA) that considers both natural and human-caused hazards. Following a discussion on the nature of security threats, the need for actionable risk assessments, and the distinction between asset and portfolio-level analysis, a general formula for all-hazards risk analysis is obtained that resembles the traditional model based on the notional product of consequence, vulnerability, and threat, though with clear meanings assigned to each parameter. Furthermore, a simple portfolio consequence model is presented that yields first-order estimates of interdependency effects following a successful attack on an asset. Moreover, depending on the needs of the decisions being made and available analytical resources, values for the parameters in this model can be obtained at a high level or through detailed systems analysis. Several illustrative examples of the CAPRA methodology are provided.     

Confidence deficits and reducibility: Toward a coherent conceptualization of uncertainty level

Outside of the field of risk analysis, an important theoretical conversation on the slippery concept of uncertainty has unfolded over the last 40 years within the adjacent field of environmental risk. This literature has become increasingly standardized behind the tripartite distinction between uncertainty location, the nature of uncertainty, and uncertainty level, popularized by the “W&H framework.” This article introduces risk theorists and practitioners to the conceptual literature on uncertainty with the goal of catalyzing further development and clarification of the uncertainty concept within the field of risk analysis. It presents two critiques of the W&H framework's dimension of uncertainty level—the dimension that attempts to define the characteristics separating greater uncertainties from lesser uncertainties. First, I argue the framework's conceptualization of uncertainty level lacks a clear and consistent epistemological position and fails to acknowledge or reconcile the tensions between Bayesian and frequentist perspectives present within the framework. This article reinterprets the dimension of uncertainty level from a Bayesian perspective, which understands uncertainty as a mental phenomenon arising from “confidence deficits” as opposed to the ill-defined notion of “knowledge deficits” present in the framework. And second, I elaborate the undertheorized concept of uncertainty “reducibility.” These critiques inform a clarified conceptualization of uncertainty level that can be integrated with risk analysis concepts and usefully applied by modelers and decisionmakers engaged in model-based decision support.     

Physiologically Based Liver Modeling and Risk Assessment

Because of the inherent complexity of biological systems, there is often a choice between a number of apparently equally applicable physiologically based models to describe uptake and metabolism processes in toxicology or risk assessment. These models may fit the particular data sets of interest equally well, but may give quite different parameter estimates or predictions under different (extrapolated) conditions. Such competing models can be discriminated by a number of methods, including potential refutation by means of strategic experiments, and their ability to suitably incorporate all relevant physiological processes. For illustration, three currently used models for steady-state hepatic elimination--the venous equilibration model, the parallel tube model, and the distributed sinusoidal perfusion model--are reviewed and compared with particular reference to their application in the area of risk assessment. The ability of each of the models to describe and incorporate such physiological processes as protein binding, precursor-metabolite relations and hepatic zones of elimination, capillary recruitment, capillary heterogeneity, and intrahepatic shunting is discussed. Differences between the models in hepatic parameter estimation, extrapolation to different conditions, and interspecies scaling are discussed, and criteria for choosing one model over the others are presented. In this case, the distributed model provides the most general framework for describing physiological processes taking place in the liver, and has so far not been experimentally refuted, as have the other two models. These simpler models may, however, provide useful bounds on parameter estimates and on extrapolations and risk assessments.     

基于行业特性的多元系统风险因子CreditRisk+模型

本文提出了基于行业特性的多元系统风险因子CreditRisk+模型。假设行业风险因子之间相互独立是原CreditRisk+模型存在的不足,随后试图对其进行修正的单因子模型、复合Gamma CreditRisk+模型和两阶段CreditRisk+模型仍存在问题。本文在引入多元系统风险因子的基础上,将行业风险因子的形参数表示为系统风险因子的线性组合与一反映该行业风险因子内在特性的参数之积,对原CreditRisk+模型行业风险因子相关性进行了拓展,使得拓展后的基于行业特性的多元系统风险因子CreditRisk+模型解决了两阶段CreditRisk+模型忽视行业风险因子自身特性这一缺陷,将系统和行业两重风险因子有机地结合起来;新模型能够将一般情形的行业风险因子协方差矩阵纳入该模型框架内,从而克服了复合Gamma CreditRisk+模型要求行业风险因子之间的协方差必须相等的缺陷。本文证明了原CreditRisk+模型、复合Gamma CreditRisk+模型和两阶段CreditRisk+模型都只是新模型的极端情形,这些情形难以将行业风险因子协方差矩阵很好地纳入模型框架内,从而影响贷款组合非预期损失计算的精度。     

Futures studies versus planning

The growing interest in the study of the future and the increasing number of organizations and commissions in this field, raises the question of how this area of study is to be distinguished from conventional planning. One may wonder about this question, since there would appear to be correspondence, or at least similarity, in that both are future-oriented and express thinking about the future. The thesis of this paper is that despite the similarity between planning and futures studies and their inter-relationship, it is possible and even desirable to distinguish between them, a distinction which has both analytical and practical significance. A conceptual framework based on this distinction will be presented and its implications examined.     

`Quantitative' and `Qualitative' Research: An Analysis

It is widely believed that there is a clear distinction between `quantitative' and `qualitative' research, and these embedded or institutionalised terms profoundly affect the practice of such research. In this article the clarity and/or usefulness of the distinction is challenged together with the whole idea that there are given `methodologies' for research. Almost everything turns on conceptual clarity in relation to the initial research-questions: that leads the research to methods which follow logically from the concepts involved. The alleged `quantitative'/`qualitative' distinction does no more than pre-empt methods and procedures of research which should be left open.     

Market‐Implied Spread for Earthquake CAT Bonds: Financial Implications of Engineering Decisions

In the event of natural and man‐made disasters, owners of large‐scale infrastructure facilities (assets) need contingency plans to effectively restore the operations within the acceptable timescales. Traditionally, the insurance sector provides the coverage against potential losses. However, there are many problems associated with this traditional approach to risk transfer including counterparty risk and litigation. Recently, a number of innovative risk mitigation methods, termed alternative risk transfer (ART) methods, have been introduced to address these problems. One of the most important ART methods is catastrophe (CAT) bonds. The objective of this article is to develop an integrative model that links engineering design parameters with financial indicators including spread and bond rating. The developed framework is based on a four‐step structural loss model and transformed survival model to determine expected excess returns. We illustrate the framework for a seismically designed bridge using two unique CAT bond contracts. The results show a nonlinear relationship between engineering design parameters and market‐implied spread.     

Probabilistic Framework for the Estimation of the Adult and Child Toxicokinetic Intraspecies Uncertainty Factors

Human health risk assessments use point values to develop risk estimates and thus impart a deterministic character to risk, which, by definition, is a probability phenomenon. The risk estimates are calculated based on individuals and then, using uncertainty factors (UFs), are extrapolated to the population that is characterized by variability. Regulatory agencies have recommended the quantification of the impact of variability in risk assessments through the application of probabilistic methods. In the present study, a framework that deals with the quantitative analysis of uncertainty (U) and variability (V) in target tissue dose in the population was developed by applying probabilistic analysis to physiologically-based toxicokinetic models. The mechanistic parameters that determine kinetics were described with probability density functions (PDFs). Since each PDF depicts the frequency of occurrence of all expected values of each parameter in the population, the combined effects of multiple sources of U/V were accounted for in the estimated distribution of tissue dose in the population, and a unified (adult and child) intraspecies toxicokinetic uncertainty factor UFH-TK was determined. The results show that the proposed framework accounts effectively for U/V in population toxicokinetics. The ratio of the 95th percentile to the 50th percentile of the annual average concentration of the chemical at the target tissue organ (i.e., the UFH-TK) varies with age. The ratio is equivalent to a unified intraspecies toxicokinetic UF, and it is one of the UFs by which the NOAEL can be divided to obtain the RfC/RfD. The 10-fold intraspecies UF is intended to account for uncertainty and variability in toxicokinetics (3.2x) and toxicodynamics (3.2x). This article deals exclusively with toxicokinetic component of UF. The framework provides an alternative to the default methodology and is advantageous in that the evaluation of toxicokinetic variability is based on the distribution of the effective target tissue dose, rather than applied dose. It allows for the replacement of the default adult and children intraspecies UF with toxicokinetic data-derived values and provides accurate chemical-specific estimates for their magnitude. It shows that proper application of probability and toxicokinetic theories can reduce uncertainties when establishing exposure limits for specific compounds and provide better assurance that established limits are adequately protective. It contributes to the development of a probabilistic noncancer risk assessment framework and will ultimately lead to the unification of cancer and noncancer risk assessment methodologies.     

A Definition and Categorization System for Advanced Materials: The Foundation for Risk‐Informed Environmental Health and Safety Testing

Novel materials with unique or enhanced properties relative to conventional materials are being developed at an increasing rate. These materials are often referred to as advanced materials (AdMs) and they enable technological innovations that can benefit society. Despite their benefits, however, the unique characteristics of many AdMs, including many nanomaterials, are poorly understood and may pose environmental safety and occupational health (ESOH) risks that are not readily determined by traditional risk assessment methods. To assess these risks while keeping up with the pace of development, technology developers and risk assessors frequently employ risk‐screening methods that depend on a clear definition for the materials that are to be assessed (e.g., engineered nanomaterial) as well as a method for binning materials into categories for ESOH risk prioritization. The term advanced material lacks a consensus definition and associated categorization or grouping system for risk screening. In this study, we aim to establish a practitioner‐driven definition for AdMs and a practitioner‐validated framework for categorizing AdMs into conceptual groupings based on material characteristics. Results from multiple workshops and interviews with practitioners provide consistent differentiation between AdMs and conventional materials, offer functional nomenclature for application science, and provide utility for future ESOH risk assessment prioritization. The definition and categorization framework established here serve as a first step in determining if and when there is a need for specific ESOH and regulatory screening for an AdM as well as the type and extent of risk‐related information that should be collected or generated for AdMs and AdM‐enabled technologies.     

The Distinction Between Risk and Hazard: Understanding and Use in Stakeholder Communication

A major issue in all risk communication efforts is the distinction between the terms “risk” and “hazard.” The potential to harm a target such as human health or the environment is normally defined as a hazard, whereas risk also encompasses the probability of exposure and the extent of damage. What can be observed again and again in risk communication processes are misunderstandings and communication gaps related to these crucial terms. We asked a sample of 53 experts from public authorities, business and industry, and environmental and consumer organizations in Germany to outline their understanding and use of these terms using both the methods of expert interviews and focus groups. The empirical study made clear that the terms risk and hazard are perceived and used very differently in risk communication depending on the perspective of the stakeholders. Several factors can be identified, such as responsibility for hazard avoidance, economic interest, or a watchdog role. Thus, communication gaps can be reduced to a four‐fold problem matrix comprising a semantic, conceptual, strategic, and control problem. The empirical study made clear that risks and hazards are perceived very differently depending on the stakeholders’ perspective. Their own worldviews played a major role in their specific use of the two terms hazards and risks in communication.     

The meaning of work and job

This article proposes that the concepts of work and job derive meaning from different dimensions. Work is viewed as having meaning that relates to a social framework and goes beyond organizational boundaries. Here two dimensions of work meaning are termed acceptability and instrumentality. Job meaning on the other hand, is viewed to be the result of an interplay between situational characteristics and organizational dimensions, and the value and relevance of those to an individual. These dimensions are here referred to as situational and personal relevance job meaning. It is suggested that making a distinction between work and job meaning will facilitate comparisons between groups that are of different employment status.     

The Phenomenology of Earnings Management within the Confines of Agency Theory

Agents' selective and acceptable reporting of economic events by different accounting systems, compounded by alternative accounting methods and estimates, make financial statements an approximation of economic reality. The tendency to delay accounting recognition of some transactions suggests that financial statements lag behind reality. The difference between reality and imaginary is often referred to as the agency problem. An essential characteristic of this problem is risk attitudes of principals (shareholders) and agents (management). Shareholders are considered risk neutral in their preferences for individual firms. They are in a position to diversify their shareholdings across multiple firms. Agents on the other hand have security and income that are inextricably linked to one firm. It would not be surprising to find agents exhibiting risk aversion in decisions regarding the firm. Immediately one's attention is drawn to the opportunity costs that arise for the risk-neutral shareholders who prefer that agents maximize their returns. The risk differential between agents and principals creates a problem in principal-agent relationship. It is within this framework that supervisory and incentive alignment mechanisms that alter the risk orientation of agents are set up. Powerful incentives act upon agents as they exercise their judgment, particularly when the judgment can trigger a stock market response that will, in turn, affect the firm in numerous ways. The responsibility of agents is to manage earnings. From a principal's perspective not all of the methods used to achieve this goal are equally desirable. Agents can either increase productivity or they can strategically manipulate accounting choices to affect earnings. The latter method need not come with any associated changes in productivity. Consequently, there is misstatement of the financial results and position. The calculus of earnings management is considered within the confines of agents' treatment of risk. Using an Agency Theory framework, this study examines the techniques used by agents to manage and manipulate earnings. The study initially tests the hypothesis whether earnings are really managed. For this purpose two manipulation indices were developed and based upon these indices the phenomenology earnings management was considered.     

供应链融资业务中钢材质押贷款动态质押率设定的VaR方法

异于债券、股票等质押融资业务,存货质押业务动态质押的核心在于预测其长期价格风险。从分析存货质押市场收益率的统计特征出发,以场外现货交易为主的钢材((HRB335)日数据为例,建立能刻画钢材收益率序列异方差性和尖峰厚尾特性的VaR-GARCH(1,1)-GED模型。同时,提出置于多风险窗口下运用样本外预测未来质押期内钢材价格风险水平,给出厚尾分布下长期风险VaR的计算解析式,得出与银行风险承受能力相一致的质押率。进而,基于失效率法则建立长期风险的碰撞序列函数,回测多风险窗口下长期VaR值。实证分析显示,模型得到的质押率在控制好风险的同时降低了效率损失,为商业银行提供一种动态质押率的风险管理模式和框架。     

期望效用视角下的风险对冲效率

与传统文献将风险下降比率作为风险对冲效率指标不同,本文引入期望效用理论来比较最小方差对冲策略、最小在险价值(VaR)对冲策略和最小条件在险价值(CVaR)对冲策略的对冲效率,从而将人们的风险态度同对冲策略选择联系起来,以实现不同风险态度的投资者选择不同风险对冲策略的目的。借用风险中性效用函数、二次效用函数和CARA效用函数,本文严格证明:在这三种对冲策略中,最小方差对冲策略过于保守,最小VaR对冲策略最为激进,风险厌恶程度大的投资者偏好最小方差对冲策略,风险中性投资者和风险厌恶程度小的投资者更偏好最小VaR对冲策略,最小CVaR对冲策略介于二者之间。     

Comparative Risk and Policy Analysis in Environmental Health

There is increasing interest in the integration of quantitative risk analysis with benefit-cost and cost-effectiveness methods to evaluate environmental health policy making and perform comparative analyses. However, the combined use of these methods has revealed deficiencies in the available methods, and the lack of useful analytical frameworks currently constrains the utility of comparative risk and policy analyses. A principal issue in integrating risk and economic analysis is the lack of common performance metrics, particularly when conducting comparative analyses of regulations with disparate health endpoints (e.g., cancer and noncancer effects or risk-benefit analysis) and quantitative estimation of cumulative risk, whether from exposure to single agents with multiple health impacts or from exposure to mixtures. We propose a general quantitative framework and examine assumptions required for performing analyses of health risks and policies. We review existing and proposed risk and health-impact metrics for evaluating policies designed to protect public health from environmental exposures, and identify their strengths and weaknesses with respect to their use in a general comparative risk and policy analysis framework. Case studies are presented to demonstrate applications of this framework with risk-benefit and air pollution risk analyses. Through this analysis, we hope to generate discussions regarding the data requirements, analytical approaches, and assumptions required for general models to be used in comparative risk and policy analysis.     

Union Wage Setting,Employment and Investment: a Survey of Theory and Empirical Evidence

Abstract. This paper provides a survey of recent theoretical and empirical research on union wage setting, employment and investment. The basic models of union wage setting and employment are presented in a unified framework. The distinction between insiders and outsiders is introduced as an extension of the basic models. Empirical evidence on union preferences and on the performance of the various models is accessibly ordered. Finally, attention is paid to the effects of strategic behaviour between union and firm on wages, employment and investment.     

Does Diesel Exhaust Cause Human Lung Cancer?

Recent reviews of epidemiological evidence on the relation between exposure to diesel exhaust (DE) and lung cancer risk have reached conflicting conclusions, ranging from belief that there is sufficient evidence to conclude that DE is a human lung carcinogen (California EPA, 1994) to conclusions that there is inadequate evidence to support a causal association between DE and human lung cancer (Muscat and Wynder, 1995). Individual studies also conflict, with both increases and decreases in relative risks of lung cancer mortality being cited with 95% statistical confidence. On balance, reports of elevated risk outnumber reports of reduced risk. This paper reexamines the evidence linking DE exposures to lung cancer risk. After briefly reviewing animal data and biological mechanisms, it surveys the relevant epidemiological literature and examines possible explanations for the discrepancies. These explanations emphasize the distinction between statistical associations, which have been found in many studies, and causal associations, which appear not to have been established. Methodological threats to valid causal inference are identified and new approaches for controlling them are proposed using recent techniques from artificial intelligence (AI) and computational statistics. These threats have not been adequately controlled for in previous epidemiological studies. They provide plausible noncausal explanations for the reported increases in relative risks, making it impossible to infer causality between DE exposure and lung cancer risk from these studies. A key contribution is to show how recent techniques developed in the AI-and-statistics literature can help clarify the causal interpretation of complex multivariate data sets used in epidemiological risk assessments. Applied to the key study of Garshick et al. (1988), these methods show that DE concentration has no positive causal association with occupational lung cancer mortality risk.