RISK MANAGEMENT AND DATA QUALITY SELECTION: AN INFORMATION ECONOMICS APPROACH

Data quality has been shown to be a major determinant of the value of systems that utilize input data feeds and transform them into valuable information under a variety of business contexts. For this study, we have chosen a financial risk management context to investigate the relationship between data quality and value of risk management forecasting systems. Three attributes of data quality, frequency, response time, and accuracy, along with the cost of data are considered. Joint impacts of attributes are also considered. It is shown that an increase in report frequency results in an increase in the utility of a risk management forecasting system, but this increase is limited by the responsiveness of the hedging scheme. Frequency is shown to improve the utility of the forecasting systems in two ways: First, an increase in frequency pushes the predicted states closer to the actual states and second, an increase in frequency causes the reliability of the forecasting model to increase. A delay in response time of reports is predicted to have a greater impact on utility for high frequency reports than for low frequency reports. Finally, data inaccuracies are recommended to be the first concern of a portfolio manager before an attempt is made to increase the reporting frequency.Information Systems Working Papers Serie

PARAMETER HETEROGENEITY IN A MODEL WHICH ESTIMATES THE BUSINESS VALUE OF INFORMATION TECHNOLOGY

Developing robust and refined measures to quantify strategic impacts is a major challenge facing researchers who seek to improve methods for information technology (IT) investment evaluation. This paper presents a means to test for parameter heterogeneity in a model which quantifies the strategic contribution of IT. An iterative "jackknife" procedure is used to diagnose if different local competitive and demographic conditions present in branch banking enhance or suppress leverage on deposit market share associated with membership in an automated teller machine (ATM) network. The results are validated using correlation analysis and re-estimating partitioned data sets for a market share model developed by Banker and Kauffman (1988). Overall, the results suggest this new approach will be useful for managers who need to evaluate similar ITS which operate in different environments.Information Systems Working Papers Serie

COMPARING THE PERFORMANCE OF REGRESSION AND NEURAL NETWORKS AS DATA QUALITY VARIES: A BUSINESS VALUE APPROACH

Under circumstances where data quality may vary (due to inaccuracies or lack of timeliness, for example), knowledge about the potential performance of alternate predictive models can help a decision maker to design a business value-maximizing information system. This paper examines a real-world example from the field of finance to illustrate a comparison of alternative modeling tools. Two modeling alternatives are used in this example: regression analysis and neural network analysis. There are two main results: (1) Linear regression outperformed neural nets in terms of forecasting accuracy, but the opposite was true when we considered the business value of the forecast. (2) Neural net-based forecasts tended to be more robust than linear regression forecasts as data accuracy degraded. Managerial implications for financial risk management of MBS portfolios are drawn from the results.Information Systems Working Papers Serie

QUANTIFYING THE VALUE OF MODELS AND DATA: A COMPARISON OF THE PERFORMANCE OF REGRESSION AND NEURAL NETS WHEN DATA QUALITY VARIES

Under circumstances where data quality may vary, knowledge about the potential performance of alternate predictive models can enable a decision maker to design an information system whose value is optimized in two ways. The decision maker can select a model which is least sensitive to predictive degradation in the range of observed data quality variation. And, once the "right" model has been selected, the decision maker can select the appropriate level of data quality in view of the costs of acquiring it. This paper examines a real-world example from the field of finance -- prepayments in mortgage-backed securities (MBS) portfolio management -- to illustrate a methodology that enables such evaluations to be made for two modeling alternative: regression analysis and neural network analysis. The methodology indicates that with "perfect data," the neural network approach outperforms regression in terms of predictive accuracy and utility in a prepayment risk management forecasting system (RMFS). Further, the performance of the neural network model is more robust under conditions of data quality degradation.Information Systems Working Papers Serie

FINANCIAL RISK AND FINANCIAL RISK MANAGEMENT TECHNOLOGY (RMT): ISSUES AND ADVANTAGES

Methods for sound risk management are of increasing interest among Wall Street investment banking and brokerage firms in the aftermath of the October 1987 crash of the stock market. As the knowledge of advanced technology applications in risk management increases, financial firms are finding innovative ways to use them practically, in order to insulate themselves. The recent development in models, the software and hardware, and the market data to track risk are all considered advances in Risk Management Technology (RMT). These advances have affected all three stages of risk management: the identification, the measurement, and the formulation of strategies to control financial risk. This article discusses the advances made in five areas of RMT: communication software, object-oriented programming, parallel processing, neural nets and artificial intelligence. Systems based on any of these areas may be used to add value to the business of a firm. A business value linkage analysis shows how the utility of advanced systems can be measured to justify their costs.Information Systems Working Papers Serie

APPLICATIONS: Financial risk and financial Risk Management Technology (RMT): Issues and advances

Methods for sound risk management are of increasing interest among Wall Street investment banking and brokerage firms in the aftermath of the October 1987 crash of the stock market. As the knowledge of advanced technology applications in risk management increases, financial firms are finding innovative ways to use them practically, in order to insulate themselves. The recent development in models, the software and hardware, and the market data to track risk are all considered advances in Risk Management Technology (RMT). -. These advances have affected all three stages of risk management: the identification, the measurement, and the formulation of strategies to control financial risk. This article discusses the advances made in five areas of RMT: communication software, object-oriented programming, parallel processing, neural nets and artificial intelligence. Systems based on any of these areas may be used to add value to the business of a firm. A business value linkage analysis shows how the utility of advanced systems can be measured to justify their costs.Information Systems Working Papers Serie

FINANCIAL RISK AND FINANCIAL RISK MANAGEMENT TECHNOLOGY (RMT): ISSUES AND ADVANCES

Methods for sound risk management are of increasing interest among Wall Street investment banking and brokerage firms in the aftermath of the October 1987 crash of the stock market. We present an overview of the basic definitions and issues related to risk, and the management of financial risk and financial risk management technology (RMT) for information systems (IS) technology professionals. We discuss of the content of risk management technology, including the models, the software and hardware, and the market data required to track risk. We also discuss the identification of risky events, alternative approaches to the measurement of risk, and how investment firms go about formulating strategies to control financial risk. We next show how changes in the information technologies supporting these tasks have led to improvements in the control of risk and in the design of products which involve financial risk. Advances in five areas that are of interest are: communications software, object-oriented programming, the use of parallel processors and supercomputers, and the application of artificial intelligence and neural nets. Although these new information technologies create significant opportunities to improve global and departmental risk management, a basic question that must be addressed involves the costs associated with their implementation. Thus, a third contribution of this paper is to analyze the extent to which the implementation of these technologies will affect firm costs. To this end, we evaluate the components of the cost function for risk management, and consider some ways that the new technologies can be applied to reduce overall costs.Information Systems Working Papers Serie

MACHINE LEARNING ASSISTED QUICK EYESCAN (MLAQE) FOR SIGNAL INTEGRITY CHECK

Presented herein is a quick scan method for signal integrity checks through sampling of four points under certain thermal condition. The techniques presented herein use a machine learning trained model to ensure signal integrity check fidelity

Barrier modification in sub-barrier fusion reactions using Wong formula with Skyrme forces in semiclassical formalism

We obtain the nuclear proximity potential by using semiclassical extended Thomas Fermi (ETF) approach in Skyrme energy density formalism (SEDF), and use it in the extended $\ell$-summed Wong formula under frozen density approximation. This method has the advantage of allowing the use of different Skyrme forces, giving different barriers. Thus, for a given reaction, we could choose a Skyrme force with proper barrier characteristics, not-requiring extra ``barrier lowering" or ``barrier narrowing" for a best fit to data. For the $^{64}$Ni+$^{100}$Mo reaction, the $\ell$-summed Wong formula, with effects of deformations and orientations of nuclei included, fits the fusion-evaporation cross section data exactly for the force GSkI, requiring additional barrier modifications for forces SIII and SV. However, the same for other similar reactions, like $^{58,64}$Ni+$^{58,64}$Ni, fits the data best for SIII force. Hence, the barrier modification effects in $\ell$-summed Wong expression depends on the choice of Skyrme force in extended ETF method.Comment: INPC2010, Vancouver, CANAD

Parachute mitral valve with late presentation: rare case reports

Congenital mitral stenosis involves the annulus, the zone immediately above and contiguous with the annulus, the leaflets, the chordae tendineae, and the papillary muscles. In a parachute mitral valve (PMV), all chordae tendineae which are usually shorter and thicker than normal type, inserted into this single papillary muscle. This condition restricts the motion of leaflets and obstructs the blood flow into the left ventricle during diastole. Here we present two cases of severe congenital mitral stenosis with severe pulmonary hypertension due to parachute mitral valve that allowed survival into adulthood without any specific treatment