基于风险网络的大型工程项目风险度量方法研究

风险度量是风险管理的基础,提出适合大型工程项目风险的风险度量方法.针对大型工程项目风险因素、风险信息、风险损失之间的复杂联系,构建大型工程项目风险网络,分别采用贝叶斯网络推理和网络层次分析法获得风险发生概率和风险量的估计,从而提出基于风险网络的大型工程项目风险度量方法.方法将风险损失量和风险损失发生概率进行了明确合理的结合,既可用于度量客观风险,也可用于度量主观风险.最后以槽菁头隧道施工风险管理为例说明该方法的具体应用步骤和效果.     

The impact of financial leverage on risk of equity measured by loss-oriented risk measures: An option pricing approach

We investigate how financial leverage influences the risk of equity in companies with limited liability. In our study, the risk is measured by loss-oriented risk measures (VaR, downside deviation, etc.). Also, the dependence of the risk premium on risk is under consideration. VaR-based and downside risk measures are considered in similar frameworks, and risk premium is introduced which is symmetrical to these risk measures. The value of equity is modeled by the price of a call option. In most cases there is a positive relationship between the level of leverage measured by the debt ratio and the risk measured by the loss-oriented risk measures. However, there exist exceptions. The risk premium is not a linear function of the risk. Still, for a reasonable range of leverage, the dependence of the risk premium on risk is approximately linear in most cases.     

考虑风险传导情形的供应风险评估方法

针对考虑风险传导情形的供应风险评估问题,提出了一种基于贝叶斯网络的供应风险评估方法。该方法中,通过识别引起供应链中各节点企业供应风险的关键风险因素,构建一个贝叶斯网络,并依据贝叶斯公式计算考虑风险传导情形下供应风险的发生概率,在此基础上,对考虑风险传导的供应风险进行评估。最后,通过一个算例说明了该方法的可行性和有效性。     

考虑两个风险情形的项目风险应对策略选择方法

项目风险应对是风险管理的一个值得关注的重要研究问题。本文是在文献[11]研究单一风险情形的项目风险应对策略选择方法的基础上,进一步给出了考虑两个风险情形的项目风险应对策略选择方法。在本文中,首先给出了项目风险应对策略的相关概念及数学描述;然后,考虑到针对一个风险所采取的应对策略会对另一个风险发生作用,给出了项目风险应对策略选择问题的分析,并在此基础上,构建了项目风险应对策略选择的优化模型,进而通过求解模型可进行选择最优风险应对策略;最后,通过一个实例分析说明了本文给出方法的可行性和有效性。     

考虑公众风险感知的突发事件风险传播模型及仿真研究

突发事件应对过程中,公众对突发事件的风险感知会在一定程度上决定其行为选择从而影响事件风险的传播。为此,本文通过分析突发事件风险信息、风险感知和风险传播的路径关系,在风险传播过程中引入传染病传播机制,构建基于微分方程的风险传播模型。综合考虑风险传播阈值、媒体报道力度、群体风险感知度、个人风险知识水平四类因素并结合仿真实验分析对风险感知和风险传播行为的影响。最后,通过实例研究表明模型结论的有效性。本文研究结论有助于为相关职能部门调节公众风险感知,制定风险防控措施提供理论依据与支持。     

Risk measuring under liquidity risk

We present a general framework for measuring the liquidity risk. The theoretical framework defines risk measures that incorporate the liquidity risk into the standard risk measures. We consider a one-period risk measurement model. The liquidity risk is defined as the risk that a security or a portfolio of securities cannot be sold or bought without causing changes in prices. The risk measures are decomposed into two terms, one measuring the risk of the future value of a given position in a security or a portfolio of securities and the other the initial cost of this position. Within the framework of coherent risk measures, the risk measures applied to the random part of the future value of a position in a determinate security are increasing monotonic and convex cash sub-additive on long positions. The contrary, in certain situations, holds for the sell positions. By using convex risk measures, we apply our framework to the situation in which large trades are broken into many small ones. Dual representation results are obtained for both positions in securities and portfolios. We give many examples of risk measures and derive for each of them the respective capital requirement. In particular, we discuss the VaR measure.     

Factor risk quantification in annuity models

Calculation of risk contributions of sub-portfolios to total portfolio risk is essential for risk management in insurance companies. Thanks to risk capital allocation methods and linearity of the loss model, sub-portfolio (or position) contributions can be calculated efficiently. However, factor risk contribution theory in non-linear loss models has received little interest. Our concern is the determination of factor risk contributions to total portfolio risk where portfolio risk is a non-linear function of factor risks. We employ different approximations in order to convert the non-linear loss model into a linear one. We illustrate the theory on an annuity portfolio where the main factor risks are interest-rate risk and mortality risk.     

Extending dynamic convex risk measures from discrete time to continuous time: A convergence approach

We present an approach for the transition from convex risk measures in a certain discrete time setting to their counterparts in continuous time. The aim of this paper is to show that a large class of convex risk measures in continuous time can be obtained as limits of discrete time-consistent convex risk measures. The discrete time risk measures are constructed from properly rescaled (‘tilted’) one-period convex risk measures, using a d-dimensional random walk converging to a Brownian motion. Under suitable conditions (covering many standard one-period risk measures) we obtain convergence of the discrete risk measures to the solution of a BSDE, defining a convex risk measure in continuous time, whose driver can then be viewed as the continuous time analogue of the discrete ‘driver’ characterizing the one-period risk. We derive the limiting drivers for the semi-deviation risk measure, Value at Risk, Average Value at Risk, and the Gini risk measure in closed form.     

Preserving the Rothschild–Stiglitz type of increasing risk with background risk

Background risk refers to a risk that is exogenous and is not subject to transformations by a decision-maker. In this paper, we extend the definition of the Rothschild–Stiglitz type of increasing risk to a background risk framework. We theoretically investigate a more general definition of increase in risk in the presence of background risk. The results suggest that an extended concept of expectation dependence plays a vital role.     

On cross-risk vulnerability

We introduce the notion of cross-risk vulnerability to generalize the concept of risk vulnerability introduced by Gollier and Pratt [Gollier, C., Pratt, J.W. 1996. Risk vulnerability and the tempering effect of background risk. Econometrica 64, 1109–1124]. While risk vulnerability captures the idea that the presence of an unfair financial background risk should make risk-averse individuals behave in a more risk-averse way with respect to an independent financial risk, cross-risk vulnerability extends this idea to the impact of a non-financial background risk on the financial risk. It provides an answer to the question of the impact of a background risk on the optimal coinsurance rate and on the optimal deductible level. We derive necessary and sufficient conditions for a bivariate utility function to exhibit cross-risk vulnerability both toward an actuarially neutral background risk and toward an unfair background risk. We also analyze the question of the sub-additivity of risk premia and show to what extent cross-risk vulnerability provides an answer.     

Entropic risk measures and their comparative statics in portfolio selection: Coherence vs. convexity

We conduct a decision-theoretic analysis of optimal portfolio choices and, in particular, their comparative statics under two types of entropic risk measures, the coherent entropic risk measure (CERM) and the convex entropic risk measure (ERM). Starting with the portfolio selection between a risky and a risk free asset (framework of Arrow (1965) and Pratt (1964)), we find a restrictive all-or-nothing investment decision under the CERM, while the ERM yields diversification. We then address a portfolio problem with two risky assets, and provide comparative statics with respect to the investor’s risk aversion (framework of Ross (1981)). Here, both the CERM and the ERM exhibit closely interrelated inconsistencies with respect to the interpretation of their risk parameters as a measure of risk aversion: for any two investors with different risk parameters, it may happen that the investor with the higher risk parameter invests more in the riskier one of the two assets. Finally, we analyze the portfolio problem “risky vs. risk free” in the presence of an independent background risk, and analyze the effect of changes in this background risk (framework of Gollier and Pratt (1996)). Again, we find questionable predictions: under the CERM, the optimal risky investment is always increasing instead of decreasing when a background risk is introduced, while under the ERM it remains unaffected.     

Active allocation of systematic risk and control of risk sensitivity in portfolio optimization

Portfolio risk can be decomposed into two parts, the systematic risk and the nonsystematic risk. It is well known that the nonsystematic risk can be eliminated by diversification, while the systematic risk cannot. Thus, the portfolio risk, except for that of undiversified small portfolios, is always dominated by the systematic risk. In this paper, under the mean–variance framework, we propose a model for actively allocating the systematic risk in portfolio optimization, which can also be interpreted as a model of controlling risk sensitivity in portfolio selection. Although the resulting problem is, in general, a notorious non-convex quadratically constrained quadratic program, the problem formulation is of some special structures due to the features of the defined marginal systematic risk contribution and the way to model the systematic risk via a factor model. By exploiting such special problem characteristics, we design an efficient and globally convergent branch-and-bound solution algorithm, based on a second-order cone relaxation. While empirical study demonstrates that the proposed model is a preferred tool for active portfolio risk management, numerical experiments also show that the proposed solution method is more efficient when compared to the commercial software BARON.     

Solvency II,regulatory capital,and optimal reinsurance: How good are Conditional Value-at-Risk and spectral risk measures?

We study the problem of optimal reinsurance as a means of risk management in the regulatory framework of Solvency II under Conditional Value-at-Risk and, as its natural extension, spectral risk measures. First, we show that stop-loss reinsurance is optimal under both Conditional Value-at-Risk and spectral risk measures. Spectral risk measures thus constitute a more general class of suitable regulatory risk measures than specific Conditional Value-at-Risk. At the same time, the established type of stop-loss reinsurance can be maintained as the optimal risk management strategy that minimizes regulatory capital. Second, we derive the optimal deductibles for stop-loss reinsurance. We show that under Conditional Value-at-Risk, the optimal deductible tends towards restrictive and counter-intuitive corner solutions or “plunging”, which is a serious objection against its use in regulatory risk management. By means of the broader class of spectral risk measures, we are able to overcome this shortcoming as optimal deductibles are now interior solutions. Especially, the recently discussed power spectral risk measures and the Wang risk measure are shown to avoid any plunging. They yield a one-to-one correspondence between the risk parameter and the optimal deductible and, thus, provide economically plausible risk management strategies.     

Risk measurement in the presence of background risk

A distortion-type risk measure is constructed, which evaluates the risk of any uncertain position in the context of a portfolio that contains that position and a fixed background risk. The risk measure can also be used to assess the performance of individual risks within a portfolio, allowing for the portfolio’s re-balancing, an area where standard capital allocation methods fail. It is shown that the properties of the risk measure depart from those of coherent distortion measures. In particular, it is shown that the presence of background risk makes risk measurement sensitive to the scale and aggregation of risk. The case of risks following elliptical distributions is examined in more detail and precise characterisations of the risk measure’s aggregation properties are obtained.     

An integrated approach for risk response development in project planning

The risk response development phase is a major phase in the project risk management process. We present a model that integrates project work contents, risk events, and risk reduction actions and their effects into a comprehensive framework. The model allows the representation of the overlapping effects of multiple risk reduction actions and of the impacts of secondary risk events, and supports the evaluation of the total risk exposure of the project under various combinations of risk reduction actions. The model can be treated with optimisation techniques in order to generate the most cost-effective combination of risk reduction actions. In this work we describe the model, outline a solution procedure and illustrate its application with an example taken from the software industry.     

Ruin-based risk measures in discrete-time risk models

For an insurance company, effective risk management requires an appropriate measurement of the risk associated with an insurance portfolio. The objective of the present paper is to study properties of ruin-based risk measures defined within discrete-time risk models under a different perspective at the frontier of the theory of risk measures and ruin theory. Ruin theory is a convenient framework to assess the riskiness of an insurance business. We present and examine desirable properties of ruin-based risk measures. Applications within the classical discrete-time risk model and extensions allowing temporal dependence are investigated. The impact of the temporal dependence on ruin-based risk measures within those different risk models is also studied. We discuss capital allocation based on Euler’s principle for homogeneous and subadditive ruin-based risk measures.     

股市风险构成间接分解模型的改进及实证

对Campbell等提出的分析股市风险构成的间接分解模型进行改进,并运用改进模型研究中国股票市场1995年至2005年的风险构成和趋势。结果发现,公司风险是个股收益率平均风险的最大组成部分,其次是系统风险,行业风险的重要性相对较小;中国股市收益率的平均风险随时间存在下降的趋势,而公司风险和行业风险的重要性随时间在增加;总的协方差风险序列对个股收益率平均风险的影响,随时间不具有一致性。在分析股市风险构成时,不应忽略对协方差风险序列的研究。     

Risk taking with background risk under recursive rank-dependent utility

This paper examines how background risk affects risk taking under rank-dependent utility. I assume that a decision-maker facing a risk taking decision in the presence of background risk views these risks as composing a compound lottery, and recursively evaluates this compound lottery using rank-dependent utility. I show that adding background risk increases risk aversion whenever the utility-for-wealth function is risk vulnerable (Gollier and Pratt, 1996) in this model.     

Extremes for coherent risk measures

Various concepts appeared in the existing literature to evaluate the risk exposure of a financial or insurance firm/subsidiary/line of business due to the occurrence of some extreme scenarios. Many of those concepts, such as Marginal Expected Shortfall or Tail Conditional Expectation, are simply some conditional expectations that evaluate the risk in adverse scenarios and are useful for signaling to a decision-maker the poor performance of its risk portfolio or to identify which sub-portfolio is likely to exhibit a massive downside risk. We investigate the latter risk under the assumption that it is measured via a coherent risk measure, which obviously generalizes the idea of only taking the expectation of the downside risk. Multiple examples are given and our numerical illustrations show how the asymptotic approximations can be used in the capital allocation exercise. We have concluded that the expectation of the downside risk does not fairly take into account the individual risk contribution when allocating the VaR-based regulatory capital, and thus, more conservative risk measurements are recommended. Finally, we have found that more conservative risk measurements do not improve the fairness of the cost of capital allocation when the uncertainty with parameter estimation is present, even at a very high level.