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Bankruptcy Prediction
Bankruptcy prediction is the art of predicting bankruptcy and various measures of financial distress of public firms. It is a vast area of finance and accounting research. The importance of the area is due in part to the relevance for creditors and investors in evaluating the likelihood that a firm may go bankrupt. The quantity of research is also a function of the availability of data: for public firms which went bankrupt or did not, numerous accounting ratios that might indicate danger can be calculated, and numerous other potential explanatory variables are also available. Consequently, the area is well-suited for testing of increasingly sophisticated, data-intensive forecasting approaches. History The history of bankruptcy prediction includes application of numerous statistical tools which gradually became available, and involves deepening appreciation of various pitfalls in early analyses. Research is still published that suffers pitfalls that have been understood for many ...
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Bankruptcy
Bankruptcy is a legal process through which people or other entities who cannot repay debts to creditors may seek relief from some or all of their debts. In most jurisdictions, bankruptcy is imposed by a court order, often initiated by the debtor. Bankrupt is not the only legal status that an insolvent person may have, and the term ''bankruptcy'' is therefore not a synonym for insolvency. Etymology The word ''bankruptcy'' is derived from Italian ''banca rotta'', literally meaning "broken bank". The term is often described as having originated in renaissance Italy, where there allegedly existed the tradition of smashing a banker's bench if he defaulted on payment so that the public could see that the banker, the owner of the bench, was no longer in a condition to continue his business, although some dismiss this as a false etymology. History In Ancient Greece, bankruptcy did not exist. If a man owed and he could not pay, he and his wife, children or servants were forced into " ...
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Logit Regression
In statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination). Formally, in binary logistic regression there is a single binary dependent variable, coded by an indicator variable, where the two values are labeled "0" and "1", while the independent variables can each be a binary variable (two classes, coded by an indicator variable) or a continuous variable (any real value). The corresponding probability of the value labeled "1" can vary between 0 (certainly the value "0") and 1 (certainly the value "1"), hence the labeling; the function that converts log-odds to probability is the logistic function, hence the name. The unit of measurement for the log-odds scale i ...
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British Accounting Review
The ''British Accounting Review'' is an academic journal of the British Accounting and Finance Association that was established in 1969. Serving its purpose to educate and connect users, the ''British Accounting Review'' helps uphold the mission of the British Accounting and Finance Association. Even though the journal was founded in the UK, the academic journal accepts UK and non-UK sourced research, reflecting the multinational users of the academic journal. Besides the British Accounting and Finance Association, creditable accounting agencies, like the American Accounting Association, use the ''British Accounting Review''. The journal is freely accessible and can include anything relating to the widespread areas of accounting or finance, such as internal management or audit quality. Some of the most cited articles from the academic journal discuss balance scorecard trends and capital accounting and debate. Multiple research methodologies are accepted, from analytical to survey. ...
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Journal Of Finance
''The Journal of Finance'' is a peer-reviewed academic journal published by Wiley-Blackwell on behalf of the American Finance Association. It was established in 1946 and is considered to be one of the premier finance journals. The editor-in-chief is Antoinette Schoar. According to the ''Journal Citation Reports'', the journal has a 2020 impact factor of 7.544. It is listed as one of the 50 journals used by the ''Financial Times'' to compile its business-school research ranking and ''Bloomberg Businessweek''s Top 20 Journals. Editors The editorial board of the journal of finance consists of the editor, co-editors and associate editors. The executive editor is Antoinette Schoar (MIT The Massachusetts Institute of Technology (MIT) is a private land-grant research university in Cambridge, Massachusetts. Established in 1861, MIT has played a key role in the development of modern technology and science, and is one of the m ...), the first female in the position. The following ...
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Journal Of Accounting Research
The ''Journal of Accounting Research'' is a leading peer review, peer-reviewed academic journal associated with the University of Chicago. It was established in 1963 and is published by Wiley-Blackwell on behalf of the Accounting Research Center (Formerly the Institute of Professional Accounting) at the University of Chicago Booth School of Business. Its current senior editors are Philip G. Berger, Luzi Hail, Christian Leuz, Haresh Sapra, Douglas J. Skinner, Rodrigo Verdi, and Regina Wittenberg Moerman. It is listed as one of the 50 journals used by the ''Financial Times'' to compile its business-school research ranks and ''Bloomberg Businessweeks Top 20 Journals. According to the ''Journal Citation Reports'', it has a 2018 impact factor of 4.891, ranking it third out of 103 journals in the category "Business, Finance". Former Editors * Sidney Davidson * David O. Green *Nicholas Dopuch *Katherine Schipper * Richard Leftwich * Abbie J. Smith *Ray J. Ball, Ray Ball * Merle Erick ...
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FitzPatrick 1932
FitzPatrick 1932 is an early paper in the field of bankruptcy prediction. In a series of three articles in the monthly ''The Certified Public Accountant'' in 1932, Paul J. FitzPatrick presented data for 20 matched pairs of firms and discussed accounting ratios as indicators of bankruptcy. It is historically significant as an early attempt in this field, and it is notable also for its publishing a data set, now in the public domain. Beaver (1968), an important paper in accounting research which employs statistical analysis to a similar matched sample, cites the paper. The dataset includes 13 accounting ratios calculated for 40 firms for each of three years. However some fields are missing for some firm-year observations. Sample selection Example data Analysis and discussion References FitzPatrick, Paul J., Ph.D. 1932. "A Comparison of the Ratios of Successful Industrial Enterprises With Those of Failed Companies". ''The Certified Public Accountant'' Beaver 1968. ''Jou ...
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Cross-validation (statistics)
Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how the results of a statistical analysis will generalize to an independent data set. Cross-validation is a resampling method that uses different portions of the data to test and train a model on different iterations. It is mainly used in settings where the goal is prediction, and one wants to estimate how accurately a predictive model will perform in practice. In a prediction problem, a model is usually given a dataset of ''known data'' on which training is run (''training dataset''), and a dataset of ''unknown data'' (or ''first seen'' data) against which the model is tested (called the validation dataset or ''testing set''). The goal of cross-validation is to test the model's ability to predict new data that was not used in estimating it, in order to flag problems like overfitting or selection bias and to give an insight o ...
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Ant Colony Algorithm
In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Artificial ants stand for multi-agent methods inspired by the behavior of real ants. The pheromone-based communication of biological ants is often the predominant paradigm used. Combinations of artificial ants and local search algorithms have become a method of choice for numerous optimization tasks involving some sort of graph, e.g., vehicle routing and internet routing. As an example, ant colony optimization is a class of optimization algorithms modeled on the actions of an ant colony. Artificial 'ants' (e.g. simulation agents) locate optimal solutions by moving through a parameter space representing all possible solutions. Real ants lay down pheromones directing each other to resources while exploring their environment. The simulated 'ants' similarly record th ...
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Forward Selection
In statistics, stepwise regression is a method of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure. In each step, a variable is considered for addition to or subtraction from the set of explanatory variables based on some prespecified criterion. Usually, this takes the form of a forward, backward, or combined sequence of F-test, ''F''-tests or t-test, ''t''-tests. The frequent practice of fitting the final selected model followed by reporting estimates and confidence intervals without adjusting them to take the model building process into account has led to calls to stop using stepwise model building altogetherFlom, P. L. and Cassell, D. L. (2007) "Stopping stepwise: Why stepwise and similar selection methods are bad, and what you should use," NESUG 2007. or to at least make sure model uncertainty is correctly reflected.Chatfield, C. (1995) "Model uncertainty, data mining and statistical inference," J. R. Statist. Soc. A ...
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Rule-based System
In computer science, a rule-based system is used to store and manipulate knowledge to interpret information in a useful way. It is often used in artificial intelligence applications and research. Normally, the term ''rule-based system'' is applied to systems involving human-crafted or curated rule sets. Rule-based systems constructed using automatic rule inference, such as rule-based machine learning, are normally excluded from this system type. Applications A classic example of a rule-based system is the domain-specific expert system that uses rules to make deductions or choices. For example, an expert system might help a doctor choose the correct diagnosis based on a cluster of symptoms, or select tactical moves to play a game. Rule-based systems can be used to perform lexical analysis to compile or interpret computer programs, or in natural language processing. Rule-based programming attempts to derive execution instructions from a starting set of data and rules. This is ...
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James Ohlson
James is a common English language surname and given name: *James (name), the typically masculine first name James * James (surname), various people with the last name James James or James City may also refer to: People * King James (other), various kings named James * Saint James (other) * James (musician) * James, brother of Jesus Places Canada * James Bay, a large body of water * James, Ontario United Kingdom * James College, a college of the University of York United States * James, Georgia, an unincorporated community * James, Iowa, an unincorporated community * James City, North Carolina * James City County, Virginia ** James City (Virginia Company) ** James City Shire * James City, Pennsylvania * St. James City, Florida Arts, entertainment, and media * ''James'' (2005 film), a Bollywood film * ''James'' (2008 film), an Irish short film * ''James'' (2022 film), an Indian Kannada-language film * James the Red Engine, a character in ''Thomas the Tank En ...
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Financial Distress
Financial distress is a term in corporate finance used to indicate a condition when promises to creditors of a company are broken or honored with difficulty. If financial distress cannot be relieved, it can lead to bankruptcy. Financial distress is usually associated with some costs to the company; these are known as ''costs of financial distress''. Cost A common example of a cost of financial distress is bankruptcy costs. These direct costs include auditors' fees, legal fees, management fees and other payments. Cost of financial distress can occur even if bankruptcy is avoided (indirect costs). Financial distress in companies requires management attention and might lead to reduced attention on the operations of the company. Another source of indirect costs of financial distress are higher costs of capital as usually banks increase the interest rates if a state of financial distress occurs. Options for relieving financial distress If high debt burden is the cause of financia ...
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