Risk Model Framework Research Articles

A risk modeling framework to evaluate the impacts of climate change and adaptation on food and water safety

Climate change may be a factor leading to increased risks of food- and waterborne illnesses from consumption of existing and emerging biological hazards. It is beneficial to develop integrated approaches to evaluate, and provide scientific assessments of, potential climate change adaptation measures to inform risk management related to climate and weather events. To this end, a risk modeling framework was created to facilitate estimations of the impact of weather and climate change on public health risks from biological hazards in food and water and to compare potential adaptation and risk mitigation strategies. The framework integrates knowledge synthesis methods, data storage and maintenance, and stochastic modeling. Risk assessment models were developed for food and water safety case studies for demonstrative purposes. Scenario analyses indicated that implementing intervention measures to adapt to changing climate impacts might mitigate future public health risks from pathogens to varying degrees. The framework brings a generic approach to allow for comparison of relative public health risks and potential adaptation strategies across hazards, exposure pathways, and regions to assist with preventive efforts and decision-making.

An integrated stress testing framework via Markov switching simulation

Capturing tail events, especially those that include the rare possibility of severe loss, is one of the important objectives of modern risk analysis. However, the past behavior of financial data is not necessarily an accurate predictor of possible scenarios in the future. The economic turmoil of recent years has resulted in calls for a more forward-looking approach to financial risk management that integrates expert knowledge on plausible future scenarios with classical risk management models calibrated on past behavior. As a complementary risk analysis tool, stress testing is receiving more and more attention, both from regulators and from practitioners. Nevertheless, classical risk analysis models, such as value-at-risk models, that are based on historical data, are often disconnected from stress testing. This disconnection can prevent a comprehensive view of the risk profile of a financial institution. This paper proposes a multiperiod switching simulation based method for integrated stress testing risk analysis that incorporates plausible events that are not necessarily captured in historical data or in historical stressed calibration of risk models. Our application focuses on the integration of rare stress events and model stress into a market risk portfolio. However, the proposed method is also applicable to other financial risk models, eg, portfolio credit risk models. An integrated risk model and stress testing framework not only leads to forward-looking tail risk measurement, which mitigates the black swan effect, but also takes stress testing into advanced risk management decision making analysis, such as scenario-based portfolio optimization.

Policy in Adaptive Financial Markets — The Use of Systemic Risk Early Warning Tools

How can a systemic risk early warning system (EWS) facilitate the financial stability work of policymakers? In the context of evolving financial market dynamics and limitations of microprudential policy, this study examines new directions for financial macroprudential policy. A flexible macroprudential approach is anchored in strategic capacities of systemic risk EWSs. Tactically, macroprudential applications are founded on information about the level, structure, and institutional drivers of systemic financial stress and aim to manage the financial system risk and imbalances in two dimensions: across time and institutions. Time-related EWS policy applications are analyzed in pursuit of prevention and mitigation. EWS applications across institutions are considered via common exposures and interconnectedness. Care must be taken in the calibration of macroprudential applications, given their reliance on quality of the underlying systemic risk-modeling framework.

Modeling Banking, Sovereign, and Macro Risk in a CCA Global VAR

The purpose of this paper is to develop a model framework for the analysis of interactions between banking sector risk, sovereign risk, corporate sector risk, real economic activity, and credit growth for 15 European countries and the United States. It is an integrated macroeconomic systemic risk model framework that draws on the advantages of forward-looking contingent claims analysis (CCA) risk indicators for the banking systems in each country, forward-looking CCA risk indicators for sovereigns, and a GVAR model to combine the banking, the sovereign, and the macro sphere. The CCA indicators capture the nonlinearity of changes in bank assets, equity capital, credit spreads, and default probabilities. They capture the expected losses, spreads and default probability for sovereigns. Key to the framework is that sovereign credit spreads, banking system credit risk, corporate sector credit risk, economic growth, and credit variables are combined in a fully endogenous setting. Upon estimation and calibration of the global model, we simulate various negative and positive shock scenarios, particularly to bank and sovereign risk. The goal is to use this framework to analyze the impact and spillover of shocks and to help identify policies that would mitigate banking system, sovereign credit risk and recession risk—policies including bank capital increases, purchase of sovereign debt, and guarantees.

Modeling Banking, Sovereign, and Macro Risk in a CCA Global VAR

The purpose of this paper is to develop a model framework for the analysis of interactions between banking sector risk, sovereign risk, corporate sector risk, real economic activity, and credit growth for 15 European countries and the United States. It is an integrated macroeconomic systemic risk model framework that draws on the advantages of forward-looking contingent claims analysis (CCA) risk indicators for the banking systems in each country, forward-looking CCA risk indicators for sovereigns, and a GVAR model to combine the banking, the sovereign, and the macro sphere. The CCA indicators capture the nonlinearity of changes in bank assets, equity capital, credit spreads, and default probabilities. They capture the expected losses, spreads and default probability for sovereigns. Key to the framework is that sovereign credit spreads, banking system credit risk, corporate sector credit risk, economic growth, and credit variables are combined in a fully endogenous setting. Upon estimation and calibration of the global model, we simulate various negative and positive shock scenarios, particularly to bank and sovereign risk. The goal is to use this framework to analyze the impact and spillover of shocks and to help identify policies that would mitigate banking system, sovereign credit risk and recession risk - policies including bank capital increases, purchase of sovereign debt, and guarantees.

Is graffiti risky? Insights from the internet and newspapers

The act of creating graffiti is often perceived as being tied to risks, such as arrest or becoming a target for rival gangs. While graffiti writers seem aware of these risks, some use graffiti to send messages about issues such as race relations, governmental oppression, and war, while others see graffiti as an art form similar to painting on a traditional canvas. Using Lash’s work on aesthetic reflexivity within a risk model framework, we investigate internet images and newspaper accounts of graffiti to highlight the gap between the aesthetics of graffiti writing and the accounts of those who hold positions of power within structures such as city offices and police departments. This gap makes it difficult to distinguish between graffiti that is meant to enliven an area and graffiti that is used to promote violence.

Monte Carlo‐based flood modelling framework for estimating probability weighted flood risk

AbstractThis study presents a new Monte Carlo‐based flood inundation modelling framework for estimating probability weighted flood risk using a computationally efficient graphics processing unit (GPU) two dimensional (2D) hydraulic model. The 2D flood model is programmed in the GPU framework providing a unique ability to run numerous simulations in a short period of time, permitting the integration of 2D hydraulic modelling into Monte Carlo analysis. The framework operates by performing many 2D flood simulations of randomly sampled input parameters to develop a spatially varied flood hazard map. The probabilistic framework is demonstrated using a 1% annual probability flood event and simulating 1000 different flood simulations by randomly selected peak flows of the Swannanoa River in Buncombe County, USA. The results, in general, display benefits of probabilistic flood risk approach compared with a single simulation approach. The latter approach underestimated 28% of flood risk relative to the former. As the number of simulations increased from 1 to 1000, areas identified as low danger and judgment zone increased by 87.4% and 36.8% respectively, whereas the high danger zone increased by 9.3%. In conclusion, the new Monte Carlo flood risk modelling framework has the ability to provide improved accuracy of flood risk and greater insight into the spatial distribution of flood risk.

Combining bioaccumulation and coping mechanism to enhance long-term site-specific risk assessment for zinc susceptibility of bivalves

The purpose of this study is to conduct a long-term site-specific risk assessment for zinc (Zn) susceptibility of bivalves, green mussel Perna viridis and hard clam Ruditapes philippinarum, based on published experimental data by linking the biologically-based damage assessment model with the subcellular partitioning concept. A comprehensive risk modeling framework was developed to predict susceptibility probability of two bivalve species exposed to waterborne Zn. The results indicated that P. viridis accumulates more Zn toxicity, whereas both toxic potency and the recovery rate of Zn are higher for R. philippinarum. We found that negative linear correlations exist in elimination–recovery and elimination–detoxification relationships, whereas a positive linear correlation was observed in recovery–detoxification relationships for bivalves exposed to waterborne Zn. Simulation results showed that the spatial differences of susceptibility primarily resulted from the variation of waterborne Zn concentration under field conditions. We found that R. philippinarum is more susceptible of Zn than P. viridis under the same exposure condition. Results also suggested that Zn posed no significant susceptibility risk to two bivalve species in Taiwan. We suggested that these two species can be used to biomonitor the water quality on Taiwan coastal areas.

Survey of Credit Risk Models in Relation to Capital Adequacy Framework for Financial Institutions

This article (i) iterates what is meant by credit risks and the mathematical/statistical modelling thereof, (ii) elaborates the conceptual and technical links between credit risk modelling and capital adequacy framework for financial institutions, particularly as per the New Capital Accord (Basel II)’s Internal Ratings-Based (IRB) approach, (iii) proffer a simple and intuitive taxonomy on contemporary credit risk modelling methodologies, and (iv) discuses in some details a number of key models pertinent, in various stages of development, to various application areas in the banking and financial sector.

Integrated risk assessment of household chemicals and consumer products: Addressing concerns about triclosan

Integrated risk assessment of household chemicals and consumer products: Addressing concerns about triclosan

A threat risk modeling framework for Geospatial Weather Information System (GWIS) a DREAD based study

Over the years, the focus has been on protecting network, host, database and standard applications from internal and external threats. The Rapid Application Development (RAD) process makes the web application extremely short and makes it difficult to eliminate the vulnerabilities. Here we study web application risk assessment technique called threat risk modeling to improve the security of the application. We implement our proposed mechanism the application risk assessment using Microsoft's threat risk DREAD model to evaluate the application security risk against vulnerability parameters. The study led to quantifying different levels of risk for Geospatial Weather Information System (GWIS) using DREAD model.

Development of a preliminary relative risk model for evaluating regional ecological conditions in the Delaware River Estuary, USA

Effective environmental management and restoration of urbanized systems such as the Delaware River Estuary requires a holistic understanding of the relative importance of various stressor-related impacts throughout the watershed, both historical and ongoing. To that end, it is important to involve as many stakeholders as possible in the management process and to develop a system for sharing of scientific data and information, as well as effective technical tools for evaluating and disseminating the data needed to make management decisions. In this study, we describe a preliminary assessment that was undertaken to evaluate the relative risks for the variety of stressors currently operating within the Delaware Estuary using a relative risk model (RRM) framework. This model was constructed using existing data and information on the ecological conditions and stressors in the main-stem Delaware River below the head of tide at Trenton, New Jersey, USA. A large database was developed with pertinent data from a variety of library, scientific, and regulatory sources. Data were compiled, reviewed, and characterized before development of the Estuary-specific RRM. Our primary goals and objectives in developing this preliminary RRM for the Estuary were to 1) determine if the RRM framework can be adapted to a large complex estuarine system such as the Delaware River, 2) identify the issues associated with adapting the model framework to the various management issues and regional areas/habitats of the River, 3) help identify data needs and potential refinements that might be needed to more specifically quantify relative stressor risks in various areas and habitats of the Estuary to better inform future management goals/actions by Stakeholders. The key conclusions of our preliminary assessment are 1) a diverse suite of stressors is likely affecting the ecological conditions of the Delaware Estuary, 2) chemical (toxicants/contaminants) and physical (sedimentation, habitat loss) stressors were found to be on par with regards to their ranking, and 3) the RRM, in its current form, made it difficult to effectively balance the inequality in the sizes of the study subareas considered in the assessment. Management objectives and related research activities should focus on collecting the necessary data and information to further refine the RRM and assess the relative impacts of these stressors at various scales in the Estuary. By having such a framework and tool available, we believe that stakeholders within the Delaware River watershed will be able to make more informed and risk-based management decisions regarding restoration options for the Estuary.

A Framework for Identifying (and Avoiding) Fraudulent Financial Reporting*

ABSTRACTThis commentary analyzes the relationship of fraud risk assessments to other risk assessments by auditors. The Public Company Accounting Oversight Board notes that this is a problem area of current practice. Effective detection of fraudulent financial reporting requires an integrative accounting/auditing conceptual framework. As a result, this paper is as much about accounting theory as it is about auditing. To simplify the development of such an integrated framework, this paper uses an expanded risk model. This effectively results in a risk perspective on fraudulent financial reporting. There are many potential implications but the major findings are as follows. First, the study identifies the crucial role of benchmarks based on acceptable levels of risk to help differentiate between intentional and unintentional misstatements. Such differentiation is critical to successfully implementing the American Institute of Certified Public Accountants' Statement on Auditing Standards (SAS) No. 99 and international standards ISA Nos. 240, 540, and 700. Second, the paper shows the importance of not allowing the major categories of risks identified here from getting too high. This paper explains the need to set acceptable levels of these risks, either by standard‐setters as a matter of broad policy, or by individual practitioners as part of the terms of specific engagements. I propose that a major factor in the concept of “present fairly” be the acceptable levels of accounting risks that are defined here, especially the risks due to intentional forecast errors. Third, this paper clarifies how the fraud risk of SAS No. 99, and similar international standards, relates to the current audit risk model framework.

Bond durations: Corporates vs. Treasuries

We compare the durations (the percentage price sensitivity with respect to the default-free short rate) of corporate and Treasury bonds in the reduced-form, intensity-based credit risk modeling framework. In a frequently used intensity-based model for corporate bond valuation we provide an example showing that, given the parameter estimates found in empirical studies, the duration of a corporate coupon bond may very well be larger than the duration of a similar Treasury bond. This finding contrasts with conclusions of previous studies. In a general, intensity-based recovery of market value framework we provide a simple sufficient condition for when the duration of a corporate bond will be smaller than that of a similar Treasury bond. We also provide an upper bound on the duration of the corporate coupon bond.

Bond Durations: Corporates vs. Treasuries

We compare the durations of corporate and Treasury bonds in the reduced-form, intensity based credit risk modeling framework. In the case where default risk is independent of default-free interest rates, we provide in each of the three most popular recovery regimes a sufficient condition under which the duration of the corporate bond is smaller than the duration of a similar Treasury bond. In the case where the default intensity and the recovery rate may depend on the default-free interest rate, we also provide a sufficient condition for the duration of a corporate bond to be smaller than the duration of the corresponding Treasury bond, assuming that recovery of market value applies. We illustrate our findings and offer more details in a specific setting in which default-free interest rates follow a Vasicek model and recovery of market value applies with a constant loss rate and a default intensity which is affine in the default-free short rate. While the unanimous conclusion of earlier papers is that the corporate bond has a smaller duration than the corresponding Treasury bond, we demonstrate in this setting that the duration of a corporate coupon bond can very well be greater than that of the similar Treasury bond.

A Risk Perspective on Fraudulent Financial Reporting

This paper analyzes the relationship of fraud risk assessments to other risk assessments by auditors. The PCAOB (2005, 17) notes this is a problem area of current practice. The major findings are as follows. First, the study identifies the crucial role of benchmarks in forensic accounting to help differentiate between intentional and unintentional misstatements. Second, the paper shows the importance of not allowing the major categories of risks identified here from getting too high. This explains the need to set acceptable levels of these risks either by standard setters as a matter of broad policy, or by individual practitioners as part of the terms of specific engagements. Third, this paper clarifies how the fraud risk of SAS No. 99 relates to the traditional audit risk model framework.

Factors affecting density of airborne Gibberella zeae inoculum

Fusarium head blight (FHB) is a disease of increasing concern in the production of wheat (Triticum aestivum). This work studied some of the factors affecting the density of airborne Gibberella zeae inoculum. Spore samplers were placed at the edge of a field in order to observe spore deposition over a period of 45 days and nights in September and October, the period that coincides with wheat flowering. Gibberella zeae colonies were counted for each period and values transformed to relative density. A stepwise regression procedure was used to identify weather variables helpful in predicting spore cloud density. In general, a predominant night-time spore deposition was observed. Precipitation and daily mean relative humidity over 90% were the factors most hightly associated with peak events of spores in the air. Models for predicting spore cloud density simulated reasonably well with the fluctuation of airborne propagules during both night and day, with potential to be integrated into an FHB risk model framework.

Recent Advances in Default Swap Valuation

Valuing credit risk sensitive instruments is one of the major growth areas in derivatives research. Two main approaches are being thoroughly explored. Merton9s „structural” approach models the stochastic evolution of total firm value, and default occurs if firm value hits a prespecified lower bound. In the „reduced form” approach, default is a random exogenous event, typically modeled as a Poisson process. The latter camp contains a variety of models that appear to handle the important parameters, jump intensity, the recovery rate in case of default, and riskless interest rates, very differently. In this article, Cheng presents a straightforward synthesis of the reduced form credit risk modeling framework and proves that the major existing models can all be seen as special cases of his general approach. This is extremely useful, both because it leads to a general valuation method, and also simply because it shows that the different existing models should all produce the same results with respect to such things as default probabilities implied by market prices for vulnerable instruments.

The Assessment and Integration of Materiality and Inherent Risk: An Analysis of Major Firms' Audit Practices

This study focuses on how inherent risk and materiality assessments are made and how they are integrated in the planning of audit testing. Both of these assessments are an integral part of the audit planning process under the current ‘audit risk model’.The analysis of audit manuals, other relevant decision aids and interviews with the technical partner or manager from each of the ‘Big 6’ accounting firms in Australia provided the source of data for the study. The findings indicate a diversity in firms' approaches to adopting the overall risk model framework, the inherent risk and control risk concepts and the levels at which these are assessed. Similarly, although all the firms set an overall planning materiality, diversity exists in relation to the level of guidance and judgment involved, the actual guidelines used, and the utilization of additional materiality levels such as an account level materiality. The firms' practices of integrating materiality and inherent risk are also diverse and the linkage is generally implicit rather than explicit. These findings are significant in terms of potential efficiency and effectiveness implications between different firms' practices.

How to link agricultural productivity, water availability and water demand in a risk context: a model for managing hydrological risks

The importance of water scarcity in irrigated agriculture in Spain provides the rationale for this paper, which analyses and evaluates the risk of water shortage on the economic result of this kind of agriculture. The main objective is to monitor this risk on a real-time basis. For this aim, we first estimated a number of regression models that explain irrigated agricultural productivity based on crop price indices, a time trend and water availability. These models, which correct for auto-correlation, yield good explanatory power. Second we carried out ex ante simulations of agricultural productivity using fitted distribution functions of water balance. The risk model framework provides the basis for a real time drought management system through a variety of distribution functions of expected economic results, which can be revised on a monthly basis before the beginning of the irrigation season. The results of the simulation show how this kind of risk model can be used to anticipate the effects of droughts and complement the hydrological models used to manage water storage in years of scarcity. Different risk profiles are identified. For example, in Genil-Cabra we found that the resilience of the system after a drought period is very high, whereas in La Plana de Castellón the risk of irrigation area abandonment is increasing year by year. In Genil-Cabra the estimated losses were 60 million euros in 2007. The models were applied to some of the most agriculturally relevant irrigation districts in Spain.