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Books on the topic 'Financial distress prediction models'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Almeida, Heitor. The risk-adjusted cost of financial distress. Cambridge, MA: National Bureau of Economic Research, 2005.

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2

Almeida, Heitor. The risk-adjusted cost of financial distress. Cambridge, MA: National Bureau of Economic Research, 2005.

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3

Lin, Feng Yu. A data mining approach to the prediction of financial distress. [S.l: The Author], 2004.

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4

Ramaswamy, Srichander. One-step prediction of financial time series. Basle, Switzerland: Bank for International Settlements, Monetary and Economic Dept., 1998.

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5

Ogawa, Kazuo. Financial distress and employment: The Japanese case in the 90s. Cambridge, Mass: National Bureau of Economic Research, 2003.

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6

Andrade, Gregor. How costly is financial (not economic) distress?: Evidence from highly leveraged transactions that became distressed. Cambridge, MA: National Bureau of Economic Research, 1997.

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7

E, Weinstein David, and National Bureau of Economic Research., eds. The myth of the patient Japanese: Corporate myopia and financial distress in Japan and the US. Cambridge, MA: National Bureau of Economic Research, 1996.

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8

Berg, Andrew. Are currency crises predictable?: A test. [Washington, D.C.]: International Monetary Fund, Research Department, 1998.

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9

Application of quantitative techniques for the prediction of bank acquisition targets. Singapore: World Scientific, 2006.

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10

Pasiouras, Fotios. Application of quantitative techniques for the prediction of bank acquisition targets. Singapore: World Scientific, 2005.

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11

Kolpakov, Vasiliy. Economic and mathematical and econometric modeling: Computer workshop. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/24417.

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The textbook presents mathematical research methods and models of economic objects and processes designed for the analysis and prediction of economic factors and develop control solutions as in the deterministic conditions, and in conditions of some uncertainty, and dynamics. Each Chapter of the book consists of a theoretical framework, discussed in detail several examples and tasks for independent work. As workbench simulation uses standard office the program Excel and Mathcad. Tutorial focused on independent performance of students individual tasks on disciplines "Economic-mathematical methods" and "Econometrics". Meets the requirements of Federal state educational standard of higher education of the last generation. The publication is intended for students and postgraduate students in economic disciplines. It can also be useful as they perform final qualifying works. The book will be useful for practitioners engaged in the analysis of the current financial and economic condition and future development of firms and businesses.

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12

Financial Statement Analysis And The Prediction Of Financial Distress. Now Publishers, 2011.

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13

Bi, Keqian. Bankruptcy studies: Empirical works on prediction and financial markets. 1989.

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14

The Use of Financial Scoring Models for the Prediction of Business Failure: Implications for Department of Defense Financial Analysis. Storming Media, 1996.

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15

Pasiouras, Fotios, Sailesh Tanna, and Constantin Zopounidis. Application of Quantitative Techniques for the Prediction of Bank Acquisition Targets (Series on Computers and Operations Research) (Series on Computers and Operations Research). World Scientific Publishing Company, 2005.

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16

Riley, Richard D., Danielle van der Windt, Peter Croft, and Karel G. M. Moons, eds. Prognosis Research in Health Care. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780198796619.001.0001.

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What is going to happen to me, doctor?’ ‘What outcomes am I likely to experience?’ ‘Will this treatment work for me?’ Prognosis—forecasting the future—has always been a part of medical practice and caring for the sick. In modern healthcare it now has a new importance, with large financial investments being made to personalize clinical decisions and tailor treatment strategies to improve individual health outcomes based on prognostic information. Prognosis research—the study of future outcomes in people with a particular health condition—provides the critical evidence for obtaining, evaluating, and implementing prognostic information within modern healthcare. This new book, written and edited by experts in the field, including clinicians, epidemiologists, statisticians, and other healthcare professionals, is a comprehensive and unified account of prognosis research in the broadest sense. It explains the concepts behind prognosis in medical practice and prognosis research, and provides a practical foundation for those developing, conducting, interpreting, synthesizing, and appraising prognosis studies. It recommends a framework of four basic prognosis research types, pioneered by the PROGRESS group, and provides explicit guidance on the conduct, analysis, and reporting of prognosis studies for each type. Key topics are overall prognosis in clinically relevant populations; prognostic factors associated with changes in prognosis across individuals; prognostic models for individual outcome risk prediction; and predictors of treatment effects. Examples are given of the impact of prognosis research across a broad range of healthcare topics, and the book also signals the latest developments in prognosis research, including systematic reviews and meta-analysis of prognosis studies, and the use of electronic health records and machine learning in prognosis research.

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