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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 [...]

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 [...]

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)

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, [...]

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 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 [...]

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.

The paper studies the implementation problem, first analyzed by Maskin and Moore (1999), in which two agents observe an unverifiable state of nature and may renegotiate inefficient outcomes following play of the mechanism. We develop a first-order approach to characterizing the set of implementable utility mappings in this problem, paralleling Mirrlees's (1971) first-order analysis of standard mechanism design problems. We use this characterization to study optimal contracting in hold-up and risk-sharing models. In particular, we examine when the contracting parties can optimally restrict attention to simple contracts, such as noncontingent contracts and option contracts (where only one agent sends a message). KEYWORDS: Implementation with renegotiation, first-order approach, option contracts, noncontingent contracts, relationship-specific investments, risk sharing.

This paper presents a systematic approach for solving the management problem of a contaminated groundwater supply system. The proposed methodology begins with the selection of a supply water quality criterion based on a stochastic health risk assessment and concludes with the establishment of a trade-off relationship between the increased management cost and the desired level of protection. In the uncertainty analysis, Gaussian quadrature numerical integration is used as an alternative to nested Monte Carlo simulation. Two management approaches--treating the contaminated groundwater with granular activated carbon and using imported water to lower the contamination level in the supply water--are used in a test problem. A random hydraulic conductivity field is used to produce the contamination variability at each extraction well. A trade-off relationship is obtained between the increased management cost and the level of protection by performing the uncertainty analysis at several supply water quality criteria for each of the two management approaches. This study demonstrates that despite the complexity in a contaminated groundwater supply system, a systematic approach can be used to quantify the many uncertainties associated with the management problem. DOI: 10.1061/(ASCE)0733-9496(2002)128:1(33) CE Database keywords: Uncertainty analysis; Aquifers; Groundwater management; Risk management; Contamination.

This paper presents a risk assessment model for international construction projects. The International Construction Risk Assessment Model (ICRAM-1) assists the user in evaluating the potential risk involved in expanding operations in an international market by analyzing risk at the macro (or country environment), market, and project levels. The paper discusses some of the existing models for country risk assessment, presents potential risk indicators at the macro, market, and project levels, and explains the ICRAM-1 methodology through an applied example. The ICRAM-1 provides a structured approach for evaluating the risk indicators involved in an international construction operation and is designed to examine a specific project in a foreign country. It can be used as a tool to quantify the risk involved in an international construction investment as one of the preliminary steps in project evaluation. Four main results are obtained from the ICRAM-1 analysis: (1) High-risk indicators; (2) impact of country environment on a specific project; (3) impact of market environment on a specific project; and (4) overall project risk.

A framework was developed for integrated risk management in information technology (IT). The framework, which can be utilized to lessen the losses resulting from the realization of threats related to IT use, involves four major risk-management components, namely risk identification, risk analysis, risk-reducing measures and risk monitoring. Risk identification process enables organizations to identify early the potential effect of the realization of internal and external threats on the whole IT environment. Risk analysis process, meanwhile, entails the use of several methodologies, namely quantitative, qualitative or a combination of both, to assess the extent of IT assets losses resulting from the realization of internal and external threats.

A product representation technique featuring products of binomial trees for use in simultaneous management of several risky assets is presented and evaluated. The technique goes around the disproportional representation of products by presenting a condition of the marginal utility being optimally independent thus resulting in the proper defining of risk neutral probabilities in the product tree.

The risks arising from accumulated hedging errors generated by discretely rebalanced option hedges over different rebalancing intervals were examined. Specifically, an approach that combines options into portfolios was proposed for significantly reducing the risk of option arbitrage caused by hedging errors. The risk in arbitrage strategies suggested by the Black-Scholes option pricing method is represented by the variance of the accumulated hedging errors up to maturity. Empirical results showed that the hedging errors arising from the different options written on the same instrument are highly correlated, particularly for options whose moneyness is close. This finding suggests that the risk of arbitrage can be substantially reduced by combining options into portfolios.

A complicated cluster of coping risk reduction strategies (RRSs) has direct correlation with the overall perceived risk (OPR) of female consumers whose decision purchases are made jointly with their husbands. Females employ the RRSs when looking for target purchases to get positive outcomes from the decision making. Thus, the utilization of the RRSs may not just be connected with the selection of brand, channel, and product. RRSs are also employed to manage the decision-making situations themselves.

Building on agency and prospect theory theory views, we construct, in this article, a behavioral agency model of executive risk taking. In the model we combine elements of internal corporate governance with problem framing to explain executive risk-taking behavior. The model suggests that executive risk taking varies across and within different forms of monitoring and that agents may exhibit risk-seeking as well as risk-averse behaviors. We develop specific propositions that combine monitoring with performance and the framing of strategic problems to explain executive choices of strategic risk. The resulting propositions enhance and extends the agency-based corporate governance literature on executive risk taking. (Reprinted by permission of the publisher.)

Bayesian analysis is performed to scrutinize the compound loss distribution using sampling based methods. Both the number and the size of the losses are treated in a stochastic manner. Model selection, forecasting and reinsurance are studied from the predictive distribution. Model uncertainty is incorporated in forecasting through the use of posterior probabilities. The variation of the aggregate claim amount is analyzed under different reinsurance treaties. The methodology for modeling collective distributions of insurance losses is illustrated by an example. Key words: Collective loss; Forecasting; MCMC; Model uncertainty; Posterior probability

The optimal bond model is an effective tool for cost-effective structuring of debts and evaluating trade-offs in managerial decision making. The model uses mathematical programming in evaluating self-insurance options to finance a municipalities' liabilities. Self-insurance plans are found to show substantially lower costs than conventional insurance. Managerial objectives and risk preferences appear to have an influence over decision when revenue flows are inadequate to finance expected losses.

The Generalized Method of Moments establishes the applicability of the risk-adjusted Hotelling model used to determine the optimal depletion of a finite resource. This particular model manipulates the standard delta by lambda over lambda equals rho equation to integrate initial, risk-free stocks, the homogenous capital-consumption good and the exhaustible supply in a two-period competitive economy. However, used in industry-level extraction costs, the results are imperfect and problem-laden. These problems are mainly due to inadequate data and other inherent limitations of the model used.

This study tested a model of firm risk-return relations in which risk was conceptualized in terms of downside outcomes. Drawing on the behavioral theory of the firm, we developed a set of hypotheses involving downside risk, return, and organizational slack. The hypothesized risk and return relations were tested using both downside risk and the conventional standard deviation of returns. The results indicate downside risk results in improved subsequent performance. Performance shows a negative relation with subsequent downside risk. (Reprinted by permission of the publisher.)

A model for risk management is developed which considers variations in the response of investors to potential outcomes that are below expected returns. Previous models were formulated without regard for variations in outcome. The risk measure is computed by subtracting the above-target deviations from the below-target deviations. The usefulness of the model for different marketing strategies could be evaluated with determined efficient sets.

A normative technique is developed for the selection of a sampling plan for an inspection lot. The method incorporates various factors from information economics, quality control, decision theory and financial portfolio selection. An information system based on expected payoff and standard payoff distribution is also considered. The model is shown to be effective in the determination of sampling plans for specific situations.

A goal programming model is formulated to help a commercial bank manage its exposure to interest rate risk, thus enabling the bank to protect its equity position against innovations in interest rates while at the same time optimizing its market value. A duration gap framework that does not need interest rate forecasts is thus created. The use of such a model indicates that the option strategy offers better immunization against interest rate risk than the short futures position for larger interest rate changes.