...Rev Account Stud (2009) 14:534–558 DOI 10.1007/s11142-008-9080-5 Bankruptcy prediction: the case of Japanese listed companies Ming Xu Æ Chu Zhang Published online: 26 July 2008 Ó Springer Science+Business Media, LLC 2008 Abstract This paper investigates if bankruptcy of Japanese listed companies can be predicted using data from 1992 to 2005. We find that the traditional measures, such as Altman’s (J Finance 23:589–609, 1968) Z-score, Ohlson’s (J Accounting Res 18:109–131, 1980) O-score and the option pricing theory-based distance-todefault, previously developed for the U.S. market, are also individually useful for the Japanese market. Moreover, the predictive power is substantially enhanced when these measures are combined. Based on the unique Japanese institutional features of main banks and business groups (known as Keiretsu), we construct a new measure that incorporates bank dependence and Keiretsu dependence. The new measure further improves the ability to predict bankruptcy of Japanese listed companies. Keywords Bankruptcy risk measure Á Accounting information Á Option pricing theory Á Japanese listed companies Á Bank dependence Á Keiretsu JEL Classifications G15 Á G33 1 Introduction When a company falls into bankruptcy, its stakeholders lose some or all the value they invested in the company. From an investor’s point of view, it is important to M. Xu (&) School of Accounting and Finance, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China e-mail:...
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...Contents lists available at SciVerse ScienceDirect Knowledge-Based Systems journal homepage: www.elsevier.com/locate/knosys Bankruptcy prediction models based on multinorm analysis: An alternative to accounting ratios Javier de Andrés ⇑, Manuel Landajo, Pedro Lorca University of Oviedo, Spain a r t i c l e i n f o a b s t r a c t In this paper we address the bankruptcy prediction problem and outline a procedure to improve the performance of standard classifiers. Our proposal replaces traditional indicators (accounting ratios) with the output of a so-called multinorm analysis. The deviations of each firm from a battery of industry norms (computed by nonparametric quantile regression) are used as input variables for the classifiers. The approach is applied to predict bankruptcy of firms, and tested on a representative data set of Spanish firms. Results indicate that the approach may provide significant improvements in predictive accuracy, both in linear and nonlinear classifiers. Ó 2011 Elsevier B.V. All rights reserved. Article history: Received 9 February 2011 Received in revised form 2 October 2011 Accepted 3 November 2011 Available online 30 December 2011 Keywords: Bankruptcy prediction Classification techniques Nonparametric methods Quantile regression Accounting ratios 1. Introduction Under the current economic conditions, bankruptcy early warning systems have become tools of key importance in order to guarantee the stability of the economy, as a consequence of...
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...in practice end in two different ways. Bankruptcy can be brought up on itself controllably and voluntarily by an insolvent debtor, alternatively, it may be also forced to end on court orders issued on creditors’ request as a result of financial difficulties. Bankruptcy is a legal procedure for liquidating a business which cannot fully pay its debts out of its current assets. Two major objectives of a bankruptcy are first of all, fair settlement of the legal claims of the creditors through an equitable distribution of a debtor’s assets. The second objective is to provide the debtor and opportunity to a fresh start. Bankruptcy can be a very tough process that causes losses for all stakeholders. For example, is a society...
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...MP A R Munich Personal RePEc Archive The Pecking Order, Trade-off, Signaling, and Market-Timing Theories of Capital Structure: a Review Anton Miglo University of Bridgeport 2010 Online at http://mpra.ub.uni-muenchen.de/46691/ MPRA Paper No. 46691, posted 6. May 2013 19:07 UTC The Pecking Order, Trade-off, Signaling, and Market-Timing Theories of Capital Structure: a Review Anton Miglo Associate professor, University of Bridgeport, School of Business, Bridgeport, CT 06604, phone (203) 576-4366, email: amiglo@bridgeport.edu. This version: 2013 Initial version: 2010 Abstract. This paper surveys 4 major capital structure theories: trade-off, pecking order, signaling and market timing. For each theory, a basic model and its major implications are presented. These implications are compared to the available evidence. This is followed by an overview of pros and cons for each theory. A discussion of major recent papers and suggestions for future research are provided. Introduction The modern theory of capital structure began with and the famous proposition of Modigliani Miller (1958) that described the conditions of capital structure irrelevance. Since then, been changing these conditions to explain factors driving capital many economists have structure decisions. Harris and Raviv (1991) synthesized major theoretical literature in the field, related these to the known empirical evidence, and suggested promising avenues for future research. They argued...
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...Accounting Information and Predicting Financial Performance: Accounting information can be useful in order to help predict future performance in the short and long term. It is important to note however that accounting information including accounting ratios show a company’s performance at a period in time. It is historical data. Trends can be identified by comparing data in sequential periods and future forecasts can be determined using historical data. There is no evidence or proof however, that these patterns will predict the future at a level of complete certainty. In my opinion, it would be hard to argue that decreasing profits over an extended period of time, or deteriorating liquid assets and increasing long term debt will have a negative impact if a trend continues. Eventually a company will have financial difficulties. Another type of predictive model that utilizes accounting information includes regression analysis. Regression analysis is viewed by many to be more useful that financial data or ratios alone. Regression analysis often test whether past stock prices, sales, profit, financial ratios, solvency, and other items are related to other variables including GDP, interest rates, market saturation of the industry, etc. In addition, a degree of confidence can be determined concerning the relationship of the variables in regression analysis Accounting ratios are determined from financial data, which as mentioned is historical. I do not feel that all financial ratios...
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...2000 *Max L. Heine Professor of Finance, Stern School of Business, New York University. This paper is adapted and updated from E. Altman, “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy,” Journal of Finance, September 1968; and E. Altman, R. Haldeman and P. Narayanan, “Zeta Analysis: A New Model to Identify Bankruptcy Risk of Corporations,” Journal of Banking & Finance, 1, 1977. Predicting Financial Distress of Companies: Revisiting the Z-Score and ZETA® Models Background This paper discusses two of the venerable models for assessing the distress of industrial corporations. These are the so-called Z-Score model (1968) and ZETA® 1977) credit risk model. Both models are still being used by practitioners throughout the world. The latter is a proprietary model for subscribers to ZETA Services, Inc. (Hoboken, NJ). The purpose of this summary are two-fold. First, those unique characteristics of business failures are examined in order to specify and quantify the variables which are effective indicators and predictors of corporate distress. By doing so, I hope to highlight the analytic as well as the practical value inherent in the use of financial ratios. Specifically, a set of financial and economic ratios will be analyzed in a corporate distress prediction context using a multiple discriminant statistical methodology. Through this exercise, I will explore not only the quantifiable characteristics of potential bankrupts but also the utility...
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...equity, EBITDA, EBITDAM, financial ethics, financial benchmarking I am very familiar with. I must admit that understanding financial ratio analysis I found somehow difficult, this is why I decided to concentrate on this topic. Summary of Articles The first article that I read is called “Financial Ratios, Discriminant Analysis and the Predictions of Corporate Bankruptcy” by Edward I. Altman, published 1968 in the Journal of Finance. The article says that academicians are seeking to eliminate ratio analysis as an analytical technique in assessing the performance of a business. According to the article theorists are attacking the relevance of ratio analysis. The article explores the possibility of whether the gap between traditional ratio analysis and more rigorous statistical techniques can be bridged. According to the article the traditional ratio analysis is no longer an important analytical technique in the academic environment because of the unsophisticated manner in which it has been presented. The research combined financial ratios with discriminate analysis, applying this to the problem of corporate bankruptcy prediction. The article concludes that if the ratios are analyzed within a multivariate framework they take on greater statistical significance than ratio comparisons...
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...the business Influences the cost of borrowing; perhaps the ability to borrow, Influences the market for its securities given that some investors such as certain pension funds may invest in a firm only if the credit rating exceeds a certain amount. The firms pay the agencies to be rated. Ratings are for specific debt issues; not the entire corporation. In early 2008, Defaultrisk.com reported that at that time, there were 64 rating agencies worldwide. SEC registration. Nationally Recognized S Ratings Organizations are credit rating services that meet certain criteria enabling them to register with the SEC. Eight firms qualified when the book was published; increased to 10 (as of Fall 2008). Page 4-25 managerial decision case. When businesses take measures to improve credit ratings, what are the potential costs? Evaluating Credit Risk -- the Five C’s Character Expected reaction when things get rough Capacity Ability to generate future cash flow for loan service Conditions The future of the business and the economy Capital The balance sheet Collateral Tangible assets including personal guarantees Estimating the Lender’s Expected Loss Expected loss = Probability of default x Amount of loss given default The Probability of Default A function of the underlying business risks (based upon our business analysis) Estimate cash flows to service debt Structure the loan to minimize the probability of default ...
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...Predicting Financial Stress 2014MAY – FSA712 Final Project Abstract This research paper will discuss methods used for measuring and predicting financial stress for business enterprises. The accounting literature includes several financial stress prediction models, the most common of which are the Altman Z-Score and Ohlson O-Score. The role of the above models is to focus on the use of financial ratios, earnings measures, market values and cash flow. Models that predict the financial stress of companies can be used as early warning tools meant to direct a company’s management to take necessary corrective action before the company goes into financial difficulty and eventual bankruptcy proceedings. This paper specifically will discuss and analyze the three main financial stress prediction models, the Altman Z-Score, Ohlson’s O-Score and Merton’s Distance to Default. The two selected companies that will be analyzed are Home Depot and Lowes’ Company. The Home Depot, Inc. operates as a home improvement retailer. The Home Depot stores sell various building materials, home improvement products, and lawn and garden products as well as provide installation, home maintenance, and professional service programs to do-it-yourself, do-it-for-me, and professional customers. The company offers installation programs that include flooring, cabinets, countertops, water heaters, and sheds, as well as act...
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...Chapter-1: Introduction 1. Problem Identification 2. Objectives 3. Scope 4. Methodology 5. Limitation 1.1 Problem Identification The export-oriented readymade garments segment of the Textile & Clothing industry in Bangladesh enjoyed a gigantic growth rate in terms of foreign trade for last one and half decade. Bangladesh economy is highly dependent on the export of ready-made garments. Currently more than 6000 RMG units are operating in the country. But the concern for the T&C industry is that about 70% of the fabric requirement is fulfilled by imports. Hardly will you find apparels manufacturers who have their own capacity of producing fabrics. Large-scale producers of fabrics are as well very few in numbers. It is a severe problem for the industry so that after 2004 the global T&C market has been absolutely opened. Quota provisions for LDCs has void. Reasonably the world market will become extremely competitive and low-cost producers will be succeeded. Bangladeshi apparels producers will possibly lose lots of suppliers as because in the quota-free world they would find manufacturing RMG more profitable. So it is a high time for the T&C industry. BEXTEX Limited, the leading textile company in the country is very much willing to take the challenge of global competition. BTL promotes its products directly to the foreign importer of RMG. The company perceives the RMG manufacturing units just as channels to reach the customers. But...
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...Positive and Negative Effects of the Global Financial Crisis Harlita H. Tomlinson Capella University BMGT8114: Accounting in the Global Era Dr. Wendy Achilles June 8,2014 Table of Contents Abstract 3 Positive and Negative Effects of the Global Financial Crisis 4 Background on the Global Financial Crisis 5 Global Financial Crisis and Its Negative Effects 9 Lack of Financial Sector Regulation and Oversights 9 Increase in the Number of Bankruptcies 11 Global Financial Crisis and Its Positive Effects 12 Designing Regulations to Monitor the Financial Sector 12 Global Governance as a Side Effect of the Global Financial Crisis 13 Lessons Learned 16 Domestic Lessons Learned 16 Global Lessons Learned 17 Lessons from Romania. 18 The Role of Financial Executives in GFC 19 Conclusions 21 References 24 Abstract The first financial crisis of the twenty-first century has not yet ended, according to Gorton and Metrick (2012), the wave of research on the crisis has already exceeded any single reader’s capacity, with the pace of new work only making this task harder. The Global Financial Crisis is considered by many economists to be the worst financial crisis since the Great Depression. Global Financial Crisis resulted in the threat of the total collapse of large financial institutions, the bailout of banks by national governments, and market downturns around the world. In the aftermath of this crisis, the housing market declined significantly and has not...
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...TURBMW06_013234761X.QXD 3/7/07 8:07 PM ONLINE CHAPTER Page 1 Neural Networks 6 for Data Mining Learning Objectives ◆ Understand the concept and different types of artificial neural networks (ANN) ◆ Learn the advantages and limitations of ANN ◆ Understand how backpropagation neural networks learn ◆ Understand the complete process of using neural networks ◆ Appreciate the wide variety of applications of neural networks N eural networks have emerged as advanced data mining tools in cases where other techniques may not produce satisfactory predictive models. As the term implies, neural networks have a biologically inspired modeling capability, but are essentially statistical modeling tools. In this chapter, we study the basics of neural network modeling, some specific applications, and the process of implementing a neural network project. 6.1 Opening Vignette: Using Neural Networks to Predict Beer Flavors with Chemical Analysis 6.2 Basic Concepts of Neural Networks 6.3 Learning in Artificial Neural Networks (ANN) 6.4 Developing Neural Network–Based Systems 6.5 A Sample Neural Network Project 6.6 Other Neural Network Paradigms 6.7 Applications of Artificial Neural Networks 6.8 A Neural Network Software Demonstration 6.1 OPENING VIGNETTE: USING NEURAL NETWORKS TO PREDICT BEER FLAVORS WITH CHEMICAL ANALYSIS Coors Brewers Ltd., based in Burton-upon-Trent, Britain’s brewing capital, is proud of having the United Kingdom’s top beer brands...
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...Final Paper: Case Study of WorldCom Financial Statement Fraud Introduction This paper will discuss the financial statement fraud committed by WorldCom by examining what led up to the fraud, who committed it and why, and the impact it caused on various stakeholders and the economy. WorldCom applied aggressive and undisclosed accounting tactics to provide financial statements that reflected a $10 billion profit for the years 2000 and 2001, rather than the actual combined loss of $73.7 billion that occurred (Romar, 2006). Opportunity, pressure, and rationalization were all present in this severe example of financial statement fraud which had a devastating impact on stakeholders globally. Basis for Understanding Financial Statement Fraud Prior to taking a deep dive into this specific example, it is important to first understand what constitutes financial statement fraud. Financial statement fraud can be defined as “deliberate misstatements or omissions of amounts or disclosures of financial statements to deceive financial statement users, particularly investors and creditors” (Wells, 2011, p. 299). Financial statement frauds can be broken down into five distinct categories: fictitious revenues, improper asset valuations, concealed liabilities and expenses, timing differences, and improper disclosures” (Wells, 2011, p. 292). The History of WorldCom “WorldCom began in Mississippi as a small provider of long distance telephone services” (Lyke, 2002). However, due to deregulation...
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...Introduction- What is a financial statement analysis: Financial statement analysis is defined as the process of identifying financial strengths and weaknesses of the firm by properly establishing relationship between the items of the balance sheet and the profit and loss account. There are various methods or techniques that are used in analyzing financial statements, such as comparative statements, schedule of changes in working capital, common size percentages, funds analysis, trend analysis, and ratios analysis. Financial statements are prepared to meet external reporting obligations and also for decision making purposes. They play a dominant role in setting the framework of managerial decisions. But the information provided in the financial statements is not an end in itself as no meaningful conclusions can be drawn from these statements alone. However, the information provided in the financial statements is of immense use in making decisions through analysis and interpretation of financial statements. Objectives- What manager need to analysis Financial statement: 1. Prepare and interpret financial statements in comparative and common-size form. 2. Compute and interpret financial ratios that would be most useful to a common stock holder. 3. Compute and interpret financial ratios that would be most useful to a short-term creditor 4. Compute and interpret financial ratios that would be most useful to long -term creditors. 1.Assessment Of Past Performance Past...
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...rate public and private corporate bond issues, commercial paper, preferred stock, and some large debt offerings of foreign companies and governments. Other rating agencies are Duff and Phelps, and Fitch’s. The information provided by the rating agencies is one of the factors that the marketplace uses to determine the appropriate yield on debt securities. Since many institutional investors can only own bonds above a certain rating, the rating also determines who will or will not buy the issue. A bond rating may also influence the value of a company’s common equity, since some common stock rating services take bond ratings into account when they rate stocks. A committee of the rating agency is responsible for ratings. Initially, in the case of corporate bonds, the company seeking a rating for a new issue makes a presentation to the rating agency. Based on these and other data, such as company visits, a bond analyst employed by the rating agency prepares a report on the company that measures the probability of trouble or loss for the investor, especially from default and poor marketability of the bonds. In this report, the analyst assesses the likelihood of earnings declining or turning negative, the likelihood of a company’s survival during a recession, and the likelihood that the issuer will be able to repay the principal borrowed and pay the interest owed at the times agreed upon. The analyst may suggest a rating to the rating committee. The rating agencies charge...
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