Decomposition of Fraud‐Risk Assessments and Auditors' Sensitivity to Fraud Cues*

Practitioners and regulators are concerned that when auditors perceive management's attitude or character as indicative of low fraud risk, they are not sufficiently sensitive to high levels of incentive or opportunity risks in their overall fraud‐risk assessments. In this study, we examine whether a fraud‐triangle decomposition of fraud‐risk assessments (that is, separately assessing attitude, opportunity, and incentive risks prior to assessing overall fraud risk) increases auditors' sensitivity to opportunity and incentive cues when perceptions of management's attitude suggest low fraud risk. In an experiment with 52 practicing audit managers, we find that auditors who decompose fraud‐risk assessments are more sensitive to opportunity and incentive cues when making their overall assessments than auditors who simply make an overall fraud‐risk assessment. However, this increased sensitivity to opportunity and incentive cues appears to happen only when those cues suggest low fraud risk. When opportunity and incentive cues suggest high fraud risk, auditors are equally sensitive to those cues whether they use a decomposition or a holistic approach. We discuss and examine potential explanations for this finding.     

Game-theoretic properties of Final-Offer Arbitration

Final-Offer Arbitration (FOA) is a dispute settlement procedure in which an arbitrator chooses one side's final position as the resolution. Game-theoretic models of FOA in two-sided interest disputes are reviewed, especially models of the disputants' final offer choices under uncertainty about the arbitrator's preferences. The extent to which the Brams-Merrill Theorem (1986) reveals optimal strategic behavior under FOA, and the implications for efficiency and equity, are assessed. Analysis of a model not satisfying the hypotheses of the Theorem suggests that, for some arbitrators, FOA can have an undesirable tendency. Another game model is used to address the question of how disputants' differential risk-aversion is reflected in their strategic behavior, and in the fairness of FOA outcomes. This calculation clarifies some apparently contradictory empirical evidence about FOA.     

A framework for the analysis of firm risk communication

In this paper, we propose a framework for the analysis of risk communication and an index to measure the quality of risk disclosure. Mainstream literature on voluntary disclosure has emphasized that quantity can be used as a sound proxy for quality. We contend that, in the analysis of the disclosure of risks made by public companies, attention has to be paid not only to how much is disclosed but also to what is disclosed and how.We apply the framework to a sample of nonfinancial companies listed in the ordinary market on the Italian Stock Exchange. To verify that the framework and synthetic index are not influenced by the two factors recognized in the literature as the most powerful drivers of disclosure behavior for listed companies, we use an OLS model. The regression shows that the index of disclosure quantity is not influenced either by size or industry. Thus, the synthetic measure can be used to rank the quality of the disclosure of risks.     

Analysing Perceived Downside Risk: the Component Value‐at‐Risk Framework

Multinational companies face increasing risks arising from external risk factors, e.g. exchange rates, interest rates and commodity prices, which they have learned to hedge using derivatives. However, despite increasing disclosure requirements, a firm's net risk profile may not be transparent to shareholders. We develop the ‘Component Value‐at‐Risk (VaR)’ framework for companies to identify the multi‐dimensional downside risk profile as perceived by shareholders. This framework allows for decomposing downside risk into components that are attributable to each of the underlying risk factors. The firm can compare this perceived VaR, including its composition and dynamics, to an internal VaR based on net exposures as it is known to the company. Any differences may lead to surprises at times of earnings announcements and thus constitute a litigation threat to the firm. It may reduce this information asymmetry through targeted communication efforts.     

关于证券市场投资者风险偏好的实证研究

根据显现偏好理论,投资者的投资行为显现了其内在的风险偏好。在本文中,采用均衡分析方法,以中国证券市场中的指数序列为样本,综合期望收益、方差,自相关系数等统计量,准确反映证券组合的投资价值,揭示市场中投资者作为一个整体所具有的风险偏好和投资组合无差异曲线的形式。     

BOT方式中项目投资者的风险管理

对基础设施、特别是经营性基础设施的融资市场化，是我国投融资改革的方向。作为项目融资的方式之一，BOT越来越广泛的得到应用，并从最初只适用于外商投资项目，到适用于包括民营资本投资在内的各种基础设施项目。但由于基础设施的特点和BOT方式的复杂性，投资者存在较大的风险。如何识别、控制这些风险，以获得项目的成功，对BOT项目的投资者来说至关重要。从项目投资者的角度分析了BOT项目可能存在的主要风险及应采取的防范措施。     

Simpler Probabilistic Population Forecasts: Making Scenarios Work

The traditional high-low-medium scenario approach to quantifying uncertainty in population forecasts has been criticized as lacking probabilistic meaning and consistency. This paper shows, under certain assumptions, how appropriately calibrated scenarios can be used to approximate the uncertainty intervals on future population size and age structure obtained with fully stochastic forecasts. As many forecasting organizations already produce scenarios and because dealing with them is familiar territory, the methods presented here offer an attractive intermediate position between probabilistically inconsistent scenario analysis and fully stochastic forecasts.     

基于顾客导向的物流企业风险预警

文中通过回顾企业风险预警管理相关文献,分析了物流企业风险形成主要影响因素,并结合物流企业运营特征,建立基于顾客导向的物流企业预警指标体系,运用灰关联分析方法评价物流企业顾客满意度,对物流企业的风险进行预警。     

Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models

Nine macroeconomic variables are forecast in a real-time scenario using a variety of flexible specification, fixed specification, linear, and nonlinear econometric models. All models are allowed to evolve through time, and our analysis focuses on model selection and performance. In the context of real-time forecasts, flexible specification models (including linear autoregressive models with exogenous variables and nonlinear artificial neural networks) appear to offer a useful and viable alternative to less flexible fixed specification linear models for a subset of the economic variables which we examine, particularly at forecast horizons greater than 1-step ahead. We speculate that one reason for this result is that the economy is evolving (rather slowly) over time. This feature cannot easily be captured by fixed specification linear models, however, and manifests itself in the form of evolving coefficient estimates. We also provide additional evidence supporting the claim that models which ‘win’ based on one model selection criterion (say a squared error measure) do not necessarily win when an alternative selection criterion is used (say a confusion rate measure), thus highlighting the importance of the particular cost function which is used by forecasters and ‘end-users’ to evaluate their models. A wide variety of different model selection criteria and statistical tests are used to illustrate our findings.     

THEORIES OF CHOICE UNDER IGNORANCE AND UNCERTAINTY

Abstract. In this paper, Knight's distinction between risk and uncertainty, and its significance for economic analysis are examined. The paper consists of a survey of some recent developments on the theory of choice under uncertainty and some applications of these theories to problems for which Bayesian Decision Theory has not proved entirely satisfactory. Two problems are examined in detail. The first is that of finance and insurance and the second is that of risktaking behaviour with special emphasis on lotteries.