Systematic and multifactor risk models revisited

Systematic and multifactor risk models are revisited via methods which were already successfully developed in signal processing and in automatic control. The results, which bypass the usual criticisms on those risk modeling, are illustrated by several successful computer experiments.Comment: First Paris Financial Management Conference, Paris : France (2013

A Risk Management Model for Merger and Acquisitio

In this paper, a merger and acquisition risk management model is proposed for considering risk factors in the merger and acquisition activities. The proposed model aims to maximize the probability of success in merger and acquisition activities by managing and reducing the associated risks. The modeling of the proposed merger and acquisition risk management model is described and illustrated in this paper. The illustration result shows that the proposed model can help to screen the best target company with minimum associated risks in the merger and acquisition activity

Risk modeling concepts relating to the design and rating of agricultural insurance contracts

The authors identify the key issues and concerns that arise in the design and rating of crop yield insurance plans, with a particular emphasis on production risk modeling. The authors show how the availability of data shapes the insurance scheme and the ratemaking procedures. Relying on the U.S. experience and recent developments in statistics and econometrics, they review risk modeling concepts and provide technical guidelines in the development of crop insurance plans. Finally, they show how these risk modeling techniques can be extended to price risk in order to develop crop revenue insurance schemes.Health Economics&Finance,Insurance Law,Environmental Economics&Policies,Insurance&Risk Mitigation,Labor Policies,Insurance&Risk Mitigation,Crops&Crop Management Systems,Health Economics&Finance,Insurance Law,Environmental Economics&Policies

Predictive Modeling in Action: How 'Virtual Wards' Help High-Risk Patients Receive Hospital Care at Home

Describes a program to reduce hospitalizations by providing multidisciplinary case management and coordinated preventive care at home to chronic disease patients found to be at risk of emergency hospitalization by predictive modeling. Outlines challenges

Pitfalls and potential of institutional change: Rain-index insurance and the sustainability of rangeland management

Rain-index insurance is strongly advocated in many parts of the developing world to help farmers to cope with climatic risk that prevail in (semi-)arid rangelands due to low and highly uncertain rainfall. We present a modeling analysis of how the availability of rain-index insurance affects the sustainability of rangeland management. We show that a rain-index insurance with frequent payos, i.e. a high strike level, leads to the choice of less sustainable grazing management than without insurance available. However, a rain-index insurance with a low to medium strike level enhances the farmer's well-being while not impairing the sustainability of rangeland management.ecological-economic modeling, weather-index insurance, Namibia, grazing management, risk, sustainability, weather-based derivatives

Practical Volatility Modeling for Financial Market Risk Management

Being able to choose most suitable volatility model and distribution specification is a more demanding task. This paper introduce an analyzing procedure using the Kullback-Leibler information criteria (KLIC) as a statistical tool to evaluate and compare the predictive abilities of possibly misspecified density forecast models. The main advantage of this statistical tool is that we use the censored likelihood functions to compute the tail minimum of the KLIC, to compare the performance of a density forecast models in the tails. We include an illustrative simulation and an empirical application to compare a set of distributions, including symmetric/asymmetric distribution, and a family of GARCH volatility models. We highlight the use of our approach to a daily index, the Kuala Lumpur Composite index (KLCI). Our results shows that the choice of the conditional distribution appear to be a more dominant factor in determining the adequacy of density forecasts than the choice of volatility model. Furthermore, the results support the Skewed for KLCI return distribution.Density forecast; Conditional distribution; Forecast accuracy; KLIC; GARCH models

RISK PERCEPTIONS AND MANAGEMENT RESPONSES: PRODUCER-GENERATED HYPOTHESES FOR RISK MODELING

Farm level risk analyses have used price and yield variability almost exclusively to represent risk. Results from a survey of 149 agricultural producers in 12 states indicate that producers consider a broader range of sources of variability in their operations. Significant differences exist among categories with respect to the importance of the sources of variability in crop and livestock production. Producers also used a variety of management responses to variability. There were significant difference among categories in the importance given to particular responses and their use of them. These results have implications for research, extension, and policy programs.Risk and Uncertainty,

Practical volatility and correlation modeling for financial market risk management

What do academics have to offer market risk management practitioners in financial institutions? Current industry practice largely follows one of two extremely restrictive approaches: historical simulation or RiskMetrics. In contrast, we favor flexible methods based on recent developments in financial econometrics, which are likely to produce more accurate assessments of market risk. Clearly, the demands of real-world risk management in financial institutions - in particular, real-time risk tracking in very high-dimensional situations - impose strict limits on model complexity. Hence we stress parsimonious models that are easily estimated, and we discuss a variety of practical approaches for high-dimensional covariance matrix modeling, along with what we see as some of the pitfalls and problems in current practice. In so doing we hope to encourage further dialog between the academic and practitioner communities, hopefully stimulating the development of improved market risk management technologies that draw on the best of both worlds

Capital allocation for operational risk: welcome remarks to a conference held November 14-16, 2001 at the Federal Reserve Bank of Boston

The conference provided a comprehensive understanding of current and evolving best practices in identifying, measuring, and modeling operational risk and in managing and mitigating this risk through capital allocation, insurance, and other existing and potential risk management tools. The conference presented the perspectives of practitioners in the banking, securities, and insurance industries, as well as supervisors and academic specializing in these sectors. The conference also identified and discussed possible solutions to barriers that may be impeding the development of new approaches.Risk management