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The return to Great Power Competition has led to a reexamination of naval priorities, force structures, and concepts. A key point in the 2020 Tri-Service (Marine Corps, Navy, and Coast [...]

This article is a reprint of an article featured in the Defense Acquisition Review Journal (July 2010) Vol. 17 issue 3, pp. 375-386, by John F. Rice. The Defense Acquisition [...]

The present study experimentally investigated human cooperation (sharing) in a laboratory foraging task that simulated environmental variability and resource scarcity (shortfall risk). Specifically, it investigated whether a risk-reduction model of food sharing derived from the energy budget rule could predict human cooperative behavior. Participants responded on a computer task for money and were given the choice between working alone or working with others and pooling earnings. Earnings could be kept only if the sum exceeded an earnings requirement (i.e., a need level). The effects of social variables on sharing were investigated to determine whether they constrained optimal decision making. The experiments investigated choice when participants were told the partner was a computer or a (fictitious) partner (Experiment 1) and when the earnings between the participant and partner were inequitable (Experiment 2). The results showed that social variables had no effect on decision making. Instead, sharing patterns were in accord with predictions of the risk-reduction model. These results provide additional evidence that a risk-reduction model of food sharing derived from risk-sensitive foraging models may be useful for predicting human cooperation for monetary outcomes. Keywords Sharing * Risk-sensitive foraging * Energy-budget * Cooperation * Risk reduction, Food sharing has been widely observed in human societies (see Winterhalder, Lu, & Tucker, 1999). Sharing may take the form of reciprocal exchange, such as when individuals give to others [...]

I. INTRODUCTION II. CLIMATE RESILIENCE REFORM A. Executive Action B. Federal Agency Implementation III. EXISTING FEDERAL LAW RELATED TO FLOOD MANAGEMENT A. The Army Corps of Engineers' Flood Control Efforts [...], Global climate change will increase inland and coastal flooding, and strain already stressed flood damage prevention and mitigation systems. In the face of Congressional unwillingness to deal with the increased flood risks, the Obama Administration has undertaken several initiatives to support local resilience in the face of climate change-induced floods and sea level rise. We place these initiatives in the context of existing flood control and insurance programs which encourage moral hazard behavior. We argue that the reforms are promising, but the Obama Administration's approach is severely limited because the existing patchwork of flood-related legislation remains unreformed. The current, competing missions could hinder the reforms' effectiveness. The federal government's lack of a comprehensive climate change response and its retreat from flood control spending pushes the problem to local governments that must cope with increased flood events. Local governments, however, face them own political, fiscal, and legal barriers to adapt to the increased risks of climate change-induced floods. In this constrained environment, the federal government should induce local governments to align their land-use policies with emerging federal policies. Local governments should lead on flood management because they are on the front lines of flooding; they also can most readily control land-use to manage floodplain development, a key strategy for reducing flood damage. We can no longer rely almost exclusively on structural solutions to coastal sea level rise, storm surges and inland floods. Science does not support this position. The federal and state governments must encourage integrated flood management by providing guidelines and increasing incentives. The proposed federal flood risk management standard, new commitments to regional climate data collection, and existing federal grant programs--such as hazard mitigation planning grants and community block development grants--can provide important direction to local governments. Takings jurisprudence has the potential to chill these efforts. Courts also need to incorporate the moral hazard concept into takings analysis to support beneficial land-use policies that suit a climate-changed world. Ultimately, the United States should move toward the European Union's risk-based flood management approach and adopt integrated floodplain and coastal management in a comprehensive federal statutory scheme. Federal involvement in flood management can prevent disparity between states and provide an integrated structure that works across states lines.

In management and planning it is commonplace for additional information to become available gradually over time. It is well known that most risk measures (risk functionals) are time inconsistent in [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.techfore.2010.01.013 Byline: Gang Xie (a), Wuyi Yue (b), Shouyang Wang (a), Kin Keung Lai (c) Keywords: Dynamic risk management; Petroleum; Variable precision rough set; Multi-objective programming Abstract: In this paper, an adaptive algorithm is designed for dynamic risk management in petroleum project investment based on a variable precision rough set (VPRS) model. In risk management, at each stage of decision-making, experts are invited to identify risk indices and support the decision-maker in evaluating the risk exposure (RE) of individual projects. The VPRS model is used to mine risk rules and determine the significance of risk indices from RE decision tables. Considering that there are multiple risks involved in any petroleum project investment, we use multi-objective programming to obtain the optimal selection of projects with minimum RE, where the significance of risk indices is assigned to each of the corresponding multi-objective functions as a weight. Moreover, we develop a risk ranking model to measure the degree of risk for individual projects in a portfolio. Finally, a numerical example based on a Chinese petroleum company's investments in overseas projects is presented to illustrate the proposed approach, and then conclusions are drawn. Author Affiliation: (a) Academy of Mathematics and Systems Science, Chinese Academy of Sciences (CAS), 55 Zhongguancun East Road, Haidian District, Beijing 100190, China (b) Department of Intelligence and Informatics, Konan University, 8-9-1 Okamoto, Kobe 658-8501, Japan (c) Department of Management Sciences, City University of Hong Kong, Hong Kong Article History: Received 30 January 2009; Revised 7 October 2009; Accepted 30 November 2009

Enterprise risk management (ERM) has become an important topic in today's more complex, interrelated global business environment, replete with threats from natural, political, economic, and technical sources. Banks especially face financial risks, as the news makes ever more apparent in 2008. This paper demonstrates support to risk management through validation of predictive scorecards for a large bank. The bank developed a model to assess account creditworthiness. The model is validated and compared to credit bureau scores. Alternative methods of risk measurement are compared. Journal of the Operational Research Society (2010) 61, 179-190. doi: 10.1057/jors.2008.144 Published online 7 January 2009 Keywords: enterprise risk management; model risk management; credit risk; statistical analysis

The stronger dependence of lower returns compared to the dependence of upper returns in financial markets is a well-established stylized fact known as asymmetric dependence. This article analyzes the implications [...]

A risk based approach to engineering provides a rational way to balance cost against the need to avoid failure. Such an approach has not been systematically incorporated into the design and operation of wastewater treatment plants. This is perhaps because engineers do not have the means to make risk based predictions of performance. We have adapted a classical technique for incorporating risk in engineering predictions to the oxidation of ammonia, the first step in nitrification. The approach incorporated random changes in load, aeration, and kinetic parameters. Two and three species models were used to evaluate the effect of increasing aeration on the risk of failure. Surprisingly, increased aeration did not lead to a monotonically decreasing risk of failure. Intermediate aeration rates typically increased the standard deviation of the effluent ammonia and thus the risk of failure. Reliable performance was predicted when there was a high abundance of one species or a similar abundance of both. These preliminary but encouraging results suggest risk based approaches offer new and important insights into the operation of biological treatment systems. DOI: 10.1061/(ASCE)0733-9372(2009) 135:8(660) CE Database subject headings: Ammonia: Activated sludge; Failures; Risk management; Nitrification.

This paper studies a partial-contracting model where an agent may provide effort to increase a project's scope before some later (operative) decisions have to be taken. Consistent with existing empirical evidence, we find a positive relationship between exogenous risk and delegation. That is, only if the exogenous risk is sufficiently large may the risk-neutral principal prefer to delegate authority over decisions to the risk-averse agent. Intuitively, for incentive reasons, the principal may optimally want to allow the agent to reduce his risk exposure. Nevertheless, even endogenous risk may be higher when the risk-averse agent has control. (JEL: D 86, D 21, D 23, G 34, L 14)

The theory of the firm under uncertainty has been traditionally studied using the expected utility approach. There are very few works done in this field of study using the risk-return approach despite the popularity of this dichotomy in the business world. This paper, therefore, applies various mean-risk models to the output decision making of a competitive firm facing uncertainty in the product price. The risk formulation used in this paper involves a pre-specified target level of profit, similar to those discussed in Fishburn (1977 and 1984). Furthermore, the measure of risk-aversion used in this model indicates the relative weight given by the agent to the risk component of the mean-risk objective function. The results of various mean-risk models are compared to those in the corresponding expected utility literature, and significant differences are found in many cases. One important difference is that whenever expected utility results require decreasing absolute risk aversion as a sufficient condition, the corresponding sufficient condition in the risk-return model of this paper is given by the condition that marginal cost is at least as large as the sum of average cost and average target level of profit. The results of this paper, in our opinion, are intuitively more appealing compared to the relatively abstract concept of decreasing absolute risk aversion., INTRODUCTION Traditionally, risk-return models have been used in portfolio theory. The theory of the firm under uncertainty has not been analyzed with the risk-return approach except for few works such [...]

This paper gives an overview about the sixteen papers included in this special issue. The papers in this special issue cover a wide range of topics. Such topics include discussing a class of tests for correlation, estimation of realized volatility, modeling time series and continuous-time models with long-range dependence, estimation and specification testing of time series models, estimation in a factor model with high-dimensional problems, finite-sample examination of quasi-maximum likelihood estimation in an autoregressive conditional duration model, and estimation in a dynamic additive quantile model. Keywords: Continuous-time model Correlation test Dynamic additive model Estimation of realized volatility Factor model Long-range dependence

Hidden Markove models (HMMs) in credit risk management are used to determine default rates' quantiles with the consideration of discrete- and continuous-state HMMs. Findings show the overestimation of high quantiles by continuous-state HMM and the underestimation of high quantiles by discrete-state HMM.

Planned (e.g., regular maintenance) and unplanned (e.g. pipe burst) interruptions occur regularly in water distribution systems leading to their reduced performance. This paper presents an extended period simulation model capable of assessing system's performance under these conditions. The extended period simulation model is based on the recently developed steady-state pressure driven hydraulic model and is capable of calculating pressures, flows, and hence actual water demands delivered under modified network topology conditions (caused by the use of isolation valves). The model is accompanied by several reliability indicators which can be used to assess system's performance under interruptions. The above-mentioned methodology is demonstrated on a real-life case study in Italy. The role of isolation valve design and uncertainty in valve operability is analyzed and discussed. The case study results obtained demonstrate that the least cost design/rehabilitation of water distribution systems is likely to result in unreliable systems if the actual network configurations obtained by closing isolation valves in abnormal working conditions are not taken into account. DOI: 10.1061/(ASCE)0733-9496(2008)134:6(527) CE Database subject headings: Water distribution systems; Network analysis; System reliability; Algorithms; Simulation; Risk management.

The scalar special case of the BEKK multivariate GARCH model is derived using a multivariate extension of the random coefficient autoregressive model. The scalar BEKK and the DCC model are similar in terms of providing parameter estimates and forecasting value-at-risk thresholds.

Correlation forecasting techniques are compared using standard statistical and risk management loss functions. GARCH models better explain correlations in stock and bond portfolios, while simpler moving average models suit the currency portfolio better.

In financial risk management, coherent risk measures have been proposed as a way to avoid undesirable properties of measures such as value at risk that discourage diversification and do not account for the magnitude of the largest, and therefore most serious, losses. A coherent risk measure equals the maximum expected loss under several different probability measures, and these measures are analogous to 'populations' or 'systems' in the ranking-and-selection literature. However, unlike in ranking and selection, here it is the value of the maximum expectation under any of the probability measures, and not the identity of the probability measure that attains it, that is of interest. We propose procedures to form fixed-width, simulation-based confidence intervals for the maximum of several expectations, explore their correctness and computational efficiency, and illustrate them on risk-management problems. The availability of efficient algorithms for computing coherent risk measures will encourage their use for improved risk management. Key words: simulation; ranking and selection; good deal bounds; coherent risk measures; risk management, 1. Introduction Both poor risk measures and scarcity of computational resources hamper effective risk management. For example, value at risk (VaR) is currently used by nearly all major financial institutions [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2006.08.028 Byline: Mark Goh (a)(c), Joseph Y.S. Lim (b), Fanwen Meng (c) Keywords: Supply chains; Risk Management; Stochastic programming; Moreau-Yosida regularization Abstract: With the increasing emphasis on supply chain vulnerabilities, effective mathematical tools for analyzing and understanding appropriate supply chain risk management are now attracting much attention. This paper presents a stochastic model of the multi-stage global supply chain network problem, incorporating a set of related risks, namely, supply, demand, exchange, and disruption. We provide a new solution methodology using the Moreau-Yosida regularization, and design an algorithm for treating the multi-stage global supply chain network problem with profit maximization and risk minimization objectives. Author Affiliation: (a) Department of Decision Sciences, National University of Singapore, 1 Business Link, Singapore 117592, Singapore (b) Department of Finance and Accounting, National University of Singapore, 1 Business Link, Singapore 117592, Singapore (c) The Logistics Institute - Asia Pacific, National University of Singapore, 7 Engineering Drive 1, Singapore 117574, Singapore Article History: Received 11 February 2004; Accepted 1 August 2006

A model of the relationship between market liquidity and risk management is presented. It was observed that tighter practices of risk management results in illiquidity, which in turn leads to even tighter risk management. The feedback effect between risk management and market liquidity is analyzed further.

This paper tests new 'independence' properties to compare three models of risky decision making. According to the rank-affected multiplicative (RAM) weights model, all three properties should be satisfied; according to the transfer of attention exchange (TAX) model, two should be satisfied and one can be violated. However, according to cumulative prospect theory (CPT), all three properties will be violated if the probability weighting function is nonlinear. Although CPT is flexible enough to accommodate violations of these properties, its predicted violations based on previously estimated parameters failed to materialize. In 14 choices for which the CPT model disagreed with TAX, CPT correctly predicted the modal choice in only one case and TAX predicted the modal choice in the other 13. New versions of three other paradoxes were also tested and found to refute CPT. Key words: choice; cumulative prospect theory; decision making; distribution independence; expected utility; paradoxes; prospect theory; rank-dependent utility, 1. Introduction This study introduces three new 'independence' properties and examines if they are descriptive of risky decision making. The three properties are all implied by expected utility (EU) theory, [...]

Byline: Alois Geyer (1), Stephan Kossmeier (2), Stefan Pichler (3) Keywords: affine term structure model; credit spreads; EMU; intensity model; Kalman filter; multi-issuer model Abstract: This paper focuses on the joint dynamics of yield spreads derived from government bonds issued by member states of the European Monetary Union (EMU). A descriptive analysis shows that there are substantial and volatile spreads between zero coupon yields of EMU member countries and German Bund yields. These yield spreads form an important source of additional risk that has to be taken into account by any pricing or risk management model dealing with EMU government bonds. We extract risk factors driving observed yield spreads by employing a multi-issuer version of the model originally proposed by Duffie and Singleton (1999). We adopt a state-space approach to implement the model whereby we can extract factor series and model parameters simultaneously. Our findings indicate that a parsimonious two-factor version of the multi-issuer model sufficiently captures the main features of the data. In this model the first factor turns out to be related to long term yield spreads across different issuers, whereas the second factor is related to short term yield spreads. Our evidence suggests that EMU government bond spreads are related to corporate bond spreads and swap spreads whereas we do not find evidence for a significant impact of macroeconomic or liquidity related variables. Author Affiliation: (1) Department of Operations Research, Vienna University of Economics, Austria (2) Department of Finance, Vienna University of Technology, Austria (3) Department of Banking and Financial Services, Vienna University of Economics, Austria Article History: Registration Date: 04/10/2004

ABSTRACT This paper deals with the analysis of the low-tail behaviour of a sample. This issue is very important in the financial field, where the fat-tailedness characterizes many series. In [...]

The influence of hedging with forward contracts on the firm's probability of bankruptcy (POB) is analyzed. Minimizing this probability, can help in maximizing shareholders wealth.

The Basle Committee's backtesting criteria is adopted here to compare performance of various simple Value-at-Risk (VaR) models. The central banks in major money centers currently use VaR systems for evaluating their supervised banks' market risks.

Predicting and modeling volatility in the stock market is important for representing portfolio risk. This paper examines various statistical models for forecasting the day-to-day volatility of several important financial market time-series in the United Kingdom.

Conflict arises in decision making when the choice alternatives present strong advantages and disadvantages over one another, that is, when the trade-offs involved are large. Conflict affects human response to choice, in particular, it increases decision difficulty and response unreliability On the other hand, larger trade-offs, i.e., higher conflict, reveal more information about an individual's preferences and mitigate the influence of measurement unreliability on preference model estimation. This suggests, somewhat counterintuitively, that there may exist some optimal level of conflict for efficient measurement of preferences. How to determine this level? This issue is examined from behavioral and analytical angles. We outline a general analysis of the interaction between trade-off size and modeling accuracy, and demonstrate its application on a simple example. The kind of analysis developed here can be conveniently implemented in a computer spreadsheet, and would be especially valuable when large amounts of preference data are to be collected, as in consumer preference studies, experimental research, and contingent valuation surveys. (Preference Modeling; Utility Assessment; Decision Analysis; Value Trade-off; Response Bias and Error), 1. Conflict in Choice Conflict arises when the alternatives among which one must choose involve large give and take. This would be the case when alternatives are dissimilar on different [...]

This article presents a genetic project risk management process that has been particularized for construction projects from the point of view of the owner and the consultant who may be assisting the owner. The process could also be adapted to the needs of other project participants, and many points referred to in the article can be directly applied to them. Any project risk management process must be tailored to the particular circumstances of the project and of the organization undertaking it. First, the article explains a complete or genetic project risk management process to be undertaken by organizations with the highest level of risk management maturity in the largest and most complex construction projects. After that, factors influencing possible simplifications of the genetic process are identified, and simplifications are proposed for some cases. Then the application to a real project is summarized. As a final validation, a Delphi analysis has been developed to assess the project risk management methodology explained here, and the results are presented. CE Database keywords: Construction; Risk management; Project management; Construction planning; Methodology.

Financial disclosure reporting and risk management in the foreign exchange market are research and reported. Models from empirical evidence are also developed concerning disclosure regulation.

Using multiple cointegration vectors, it was found that the terms of exchange futures premiums remained stable during the 1920s except for a period of speculation about the value of gold.