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The Application of Statistical Classification to Business Failure Prediction

Description: Bankruptcy is a costly event. Holders of publicly traded securities can rely on security prices to reflect their risk. Other stakeholders have no such mechanism. Hence, methods for accurately forecasting bankruptcy would be valuable to them. A large body of literature has arisen on bankruptcy forecasting with statistical classification since Beaver (1967) and Altman (1968). Reported total error rates typically are 10%-20%, suggesting that these models reveal information which otherwise is unavailable and has value after financial data is released. This conflicts with evidence on market efficiency which indicates that securities markets adjust rapidly and actually anticipate announcements of financial data. Efforts to resolve this conflict with event study methodology have run afoul of market model specification difficulties. A different approach is taken here. Most extant criticism of research design in this literature concerns inferential techniques but not sampling design. This paper attempts to resolve major sampling design issues. The most important conclusion concerns the usual choice of the individual firm as the sampling unit. While this choice is logically inconsistent with how a forecaster observes financial data over time, no evidence of bias could be found. In this paper, prediction performance is evaluated in terms of expected loss. Most authors calculate total error rates, which fail to reflect documented asymmetries in misclassification costs and prior probabilities. Expected loss overcomes this weakness and also offers a formal means to evaluate forecasts from the perspective of stakeholders other than investors. This study shows that cost of misclassifying bankruptcy must be at least an order of magnitude greater than cost of misclassifying nonbankruptcy before discriminant analysis methods have value. This conclusion follows from both sampling experiments on historical financial data and Monte Carlo experiments on simulated data. However, the Monte Carlo experiments reveal that as the cost ratio increases, robustness of linear ...
Date: December 1994
Creator: Haensly, Paul J.
Partner: UNT Libraries

IMG ER: A System for Microbial Genome Annotation Expert Review and Curation

Description: A rapidly increasing number of microbial genomes are sequenced by organizations worldwide and are eventually included into various public genome data resources. The quality of the annotations depends largely on the original dataset providers, with erroneous or incomplete annotations often carried over into the public resources and difficult to correct. We have developed an Expert Review (ER) version of the Integrated Microbial Genomes (IMG) system, with the goal of supporting systematic and efficient revision of microbial genome annotations. IMG ER provides tools for the review and curation of annotations of both new and publicly available microbial genomes within IMG's rich integrated genome framework. New genome datasets are included into IMG ER prior to their public release either with their native annotations or with annotations generated by IMG ER's annotation pipeline. IMG ER tools allow addressing annotation problems detected with IMG's comparative analysis tools, such as genes missed by gene prediction pipelines or genes without an associated function. Over the past year, IMG ER was used for improving the annotations of about 150 microbial genomes.
Date: May 25, 2009
Creator: Markowitz, Victor M.; Mavromatis, Konstantinos; Ivanova, Natalia N.; Chen, I-Min A.; Chu, Ken & Kyrpides, Nikos C.
Partner: UNT Libraries Government Documents Department

A Theoretical and Empirical Investigation into the Application af a Cash-Flow Accounting System

Description: The objective of this research is to make a theoretical and empirical investigation into the application of a cashflow accounting system. The theoretical investigation provides a definition for cash-flow accounting; it also examines the major arguments for a cash-flow reporting system. Three hypotheses are proposed for testing. The first states that during periods of changing prices, performance indicators that are based on the conventional accrual accounting will diverge from performance indicators that are based on cash-flow accounting and will continue to diverge over time. The second states that this divergence will disappear if the effects of inflation are partialled out. The third states that cash-flow statements, properly interpreted, will enable users to predict business failure.
Date: December 1983
Creator: Habib, Abo-El-Yazeed Tawfik
Partner: UNT Libraries

The Development and Evaluation of a Forecasting System that Incorporates ARIMA Modeling with Autoregression and Exponential Smoothing

Description: This research was designed to develop and evaluate an automated alternative to the Box-Jenkins method of forecasting. The study involved two major phases. The first phase was the formulation of an automated ARIMA method; the second was the combination of forecasts from the automated ARIMA with forecasts from two other automated methods, the Holt-Winters method and the Stepwise Autoregressive method. The development of the automated ARIMA, based on a decision criterion suggested by Akaike, borrows heavily from the work of Ang, Chuaa and Fatema. Seasonality and small data set handling were some of the modifications made to the original method to make it suitable for use with a broad range of time series. Forecasts were combined by means of both the simple average and a weighted averaging scheme. Empirical and generated data were employed to perform the forecasting evaluation. The 111 sets of empirical data came from the M-Competition. The twenty-one sets of generated data arose from ARIMA models that Box, Taio and Pack analyzed using the Box-Jenkins method. To compare the forecasting abilities of the Box-Jenkins and the automated ARIMA alone and in combination with the other two methods, two accuracy measures were used. These measures, which are free of magnitude bias, are the mean absolute percentage error (MAPE) and the median absolute percentage error (Md APE).
Date: May 1985
Creator: Simmons, Laurette Poulos
Partner: UNT Libraries

527 Organizations and Campaign Activity: Timing of Reporting Requirements under Tax and Campaign Finance Laws

Description: This report compares the timing of election activity reporting requirements under the Internal Revenue Code (IRC) and Federal Election Campaign Act (FECA), and discusses H.R. 1204, which would amend the timing of the IRC’s reporting requirements.
Date: July 25, 2008
Creator: Lunder, Erika & Whitaker, L. Paige
Partner: UNT Libraries Government Documents Department

Workshop on Monsoon Climate Systems: Toward Better Prediction of the Monsoon

Description: The Earth's monsoon systems are the life-blood of more than two-thirds of the world's population through the rainfall they provide to the mainly agrarian societies they influence. More than 60 experts gathered to assess the current understanding of monsoon variability and to highlight outstanding problems simulating the monsoon.
Date: December 20, 2005
Creator: Sperber, K R & Yasunari, T
Partner: UNT Libraries Government Documents Department

Affective Forecasting: the Effects of Immune Neglect and Surrogation

Description: Studies of affective forecasting examine people’s ability to predict (forecast) their emotional (affective) responses to future events. Affective forecasts underlie nearly all decisions people make and the actions they take. However, people engage in systematic cognitive errors when making affective forecasts and most often overestimate the intensity and duration of their emotional responses. Understanding the mechanisms that lead to affective forecasting errors (e.g., immune neglect) and examining the utility of methods for improving affective forecasting errors (e.g., surrogation) can provide highly valuable information for clinicians as they assist clients in determining their goals both for therapy and for life. The first purpose of the current study was to determine if affective forecasting errors due to immune neglect lead to misjudgments about the relative emotional impact of minor versus moderate negative experiences (i.e., trauma severity). The second purpose was to examine the utility of surrogation for improving affective forecasts. Potential interaction effects between these two variables were also examined. The current study utilized a 2 (Trauma Severity: minor, moderate) X 3 (Prediction Information: surrogation information only, simulation information only, both types of information) experimental design. Undergraduates were recruited via the SONA system and randomly assigned to one of the six experimental conditions. A preliminary study was conducted to obtain surrogation information for use in the main study. All participants in the main study predicted how they would feel 10 minutes after receiving negative personality feedback, using a 10-point scale ranging from (1) very unhappy to (10) very happy. These predictions constitute their affective forecasts. All participants then actually received the negative personality feedback (ostensibly from another participant, a peer, in a nearby room) and reported their actual affective states ten minutes later, using the same scale. These ratings constitute their affective reports. Affective forecasting error was calculated as the difference between ...
Date: August 2012
Creator: Burkman, Summer Dae
Partner: UNT Libraries

Forecasting Quarterly Sales Tax Revenues: A Comparative Study

Description: The purpose of this study is to determine which of three forecasting methods provides the most accurate short-term forecasts, in terms of absolute and mean absolute percentage error, for a unique set of data. The study applies three forecasting techniques--the Box-Jenkins or ARIMA method, cycle regression analysis, and multiple regression analysis--to quarterly sales tax revenue data. The final results show that, with varying success, each model identifies the direction of change in the future, but does not closely identify the period to period fluctuations. Indeed, each model overestimated revenues for every period forecasted. Cycle regression analysis, with a mean absolute percentage error of 7.21, is the most accurate model. Multiple regression analysis has the smallest absolute percentage error of 3.13.
Date: August 1986
Creator: Renner, Nancy A. (Nancy Ann)
Partner: UNT Libraries

Effects of vibrational motion on core-level spectra of prototype organic molecules

Description: A computational approach is presented for prediction and interpretation of core-level spectra of complex molecules. Applications are presented for several isolated organic molecules, sampling a range of chemical bonding and structural motifs. Comparison with gas phase measurements indicate that spectral lineshapes are accurately reproduced both above and below the ionization potential, without resort to ad hoc broadening. Agreement with experiment is significantly improved upon inclusion of vibrations via molecular dynamics sampling. We isolate and characterize spectral features due to particular electronic transitions enabled by vibrations, noting that even zero-point motion is sufficient in some cases.
Date: August 21, 2008
Creator: Uejio, Janel S.; Schwartz, Craig P.; Saykally, Richard J. & Prendergast, David
Partner: UNT Libraries Government Documents Department

Accelerators and the Accelerator Community

Description: In this paper, standing back--looking from afar--and adopting a historical perspective, the field of accelerator science is examined. How it grew, what are the forces that made it what it is, where it is now, and what it is likely to be in the future are the subjects explored. Clearly, a great deal of personal opinion is invoked in this process.
Date: June 1, 2008
Creator: Malamud, Ernest & Sessler, Andrew
Partner: UNT Libraries Government Documents Department

Elections Reform: Overview and Issues

Description: This report discusses several issues as the Congress considers legislation to reform the voting process, a number of issues have emerged as part of the debate: the reliability of different types of voting technologies; voting problems and irregularities in the 2000 election; problems for militaryand overseas voters; the electoral college; and early media projections of election results.
Date: September 7, 2001
Creator: Coleman, Kevin J & Fischer, Eric A
Partner: UNT Libraries Government Documents Department

EVIDENCE IN CRATER AGES FOR PERIODIC IMPACTS ON THE EARTH

Description: Recent evidence has indicated that the impact of a comet or asteroid may have been responsible for mass extinction at the ends of both the Cretaceous and the Eocene. Quantitative analysis by Raup and Sepkoski showed that mass extinctions occur with a 26-Myr period, similar to the period seen in qualitative pelagic records by Fischer and Arthur. To account for the possibility of periodic comet showers, Davis et al. proposed that such showers could be triggered by an unseen solar companion star as it passes through perihelion on a moderately eccentric orbit. To test a prediction implicit in this model we examined records of large impact craters on the Earth. We report here that most of the craters occur in a 28.4-Myr cycle. Within measurement errors, this period and its phase are the same as those found in the fossil mass extinctions. The probability that such agreement is accidental is 1 in 10.
Date: January 1, 1984
Creator: Alvarez, W. & Muller, R.A.
Partner: UNT Libraries Government Documents Department

An Integrated Hydrologic Bayesian Multi-Model Combination Framework: Confronting Input, parameter and model structural uncertainty in Hydrologic Prediction

Description: This paper presents a new technique--Integrated Bayesian Uncertainty Estimator (IBUNE) to account for the major uncertainties of hydrologic rainfall-runoff predictions explicitly. The uncertainties from the input (forcing) data--mainly the precipitation observations and from the model parameters are reduced through a Monte Carlo Markov Chain (MCMC) scheme named Shuffled Complex Evolution Metropolis (SCEM) algorithm which has been extended to include a precipitation error model. Afterwards, the Bayesian Model Averaging (BMA) scheme is employed to further improve the prediction skill and uncertainty estimation using multiple model output. A series of case studies using three rainfall-runoff models to predict the streamflow in the Leaf River basin, Mississippi are used to examine the necessity and usefulness of this technique. The results suggests that ignoring either input forcings error or model structural uncertainty will lead to unrealistic model simulations and their associated uncertainty bounds which does not consistently capture and represent the real-world behavior of the watershed.
Date: May 5, 2006
Creator: Ajami, N K; Duan, Q & Sorooshian, S
Partner: UNT Libraries Government Documents Department

Multi-Model Combination Techniques for Hydrological Forecasting: Application to Distributed Model Intercomparison Project Results

Description: This paper examines several multi-model combination techniques: the Simple Multimodel Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction.
Date: May 8, 2006
Creator: Ajami, N; Duan, Q; Gao, X & Sorooshian, S
Partner: UNT Libraries Government Documents Department

Annual Energy Outlook 2011: with Projections to 2035

Description: This report, prepared by the U.S. Energy Information Administration (EIA), presents long-term projections of energy supply, demand and prices through 2035, based on results from EIA's National Energy Modeling System (NEMS).
Date: April 2011
Creator: United States. Energy Information Administration.
Partner: UNT Libraries Government Documents Department

Annual Energy Outlook 2012: with Projections to 2035

Description: The Annual Energy Outlook 2012 (AEO2010), prepared by the U.S. Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2035, based on results from EIA's National Energy Modeling System (NEMS).
Date: June 2012
Creator: United States. Energy Information Administration.
Partner: UNT Libraries Government Documents Department

Annual Energy Outlook 2014: with Projections to 2040

Description: This report was prepared by the U.S. Energy Information Administration (EIA) and presents long-term annual projections of energy supply, demand, and prices focused on the U.S. through 2040, based on results from EIA's National Energy Modeling System (NEMS).
Date: April 2014
Creator: United States. Energy Information Administration.
Partner: UNT Libraries Government Documents Department

Annual Energy Outlook 2013: with Projections to 2040

Description: This report, prepared by the U.S. Energy Information Administration (EIA), presents long-term projections of energy supply, demand and prices through 2040, based on results from EIA's National Energy Modeling System (NEMS).
Date: April 2013
Creator: United States. Energy Information Administration.
Partner: UNT Libraries Government Documents Department

Annual Energy Outlook 2016: with Projections to 2040

Description: This report, prepared by the U.S. Energy Information Administration (EIA), presents long-term projections of energy supply, demand and prices through 2040, based on results from EIA's National Energy Modeling System (NEMS).
Date: August 2016
Creator: United States. Energy Information Administration.
Partner: UNT Libraries Government Documents Department

Illustrating the future prediction of performance based on computer code, physical experiments, and critical performance parameter samples

Description: In this paper, we present a generic example to illustrate various points about making future predictions of population performance using a biased performance computer code, physical performance data, and critical performance parameter data sampled from the population at various times. We show how the actual performance data help to correct the biased computer code and the impact of uncertainty especially when the prediction is made far from where the available data are taken. We also demonstrate how a Bayesian approach allows both inferences about the unknown parameters and predictions to be made in a consistent framework.
Date: January 1, 2009
Creator: Hamada, Michael S & Higdon, David M
Partner: UNT Libraries Government Documents Department