A Binary Model Versus Discriminant Analysis to Corporate Bankruptcies for Emerging Market
The problem of the firm bankruptcy prediction was investigated by foreign researchers in the 1930s and it still remains relevant. Since publishing of the major Altman’s work (1968), based on multiple discriminant analysis, this methodological area has been considerably changed. Taking into consideration that new data have appeared in the course of time, companies’ average size has changed and the accounting standards have been changed (Altman (1977)) methods and models should be renewed to be appropriate for the present day situation.
The purpose of this investigation is the revealing of factors causing bankruptcy and using models appropriate for prediction bankruptcy in the area of a construction industry during financial crisis.
This investigation has been carried out on the basis of logit and probit analysis. The main reasons of bankruptcy revealed in the course of this investigation are the following:
• non-optimal capital structure formation
• ineffective liquidity management
• decrease in assets profitability
• decrease in short-term assets turnover
The most reliable indicators, which give warning of bankruptcy ahead of others are financial instability and liquidity ratios.
The chief aim of this paper is to analyse dynamics of linear and non-linear methods to predict bankruptcy for Russian private small and medium-sized retail and wholesale trade companies. We use financial and non-financial data prior and subsequent to the economic crisis of 2008—2009. We use the following methods: logistic regression and random forest.
This research will be of vital importance especially to banks and other credit organisations providing loans to small and medium businesses.
Our dataset comprises from 200,000 to 600,000 companies depending on specific year. We use data from the Ruslana database which covers the period from 2004 to 2012.
The definition of default is extended to financial difficulties by adding voluntary liquidated firms to those liquidated as a result of legal bankruptcy. We study active companies and two types of liquidated ones.
Heterogeneity of Russian companies is taken into account in several ways. In addition to financial ratios derived from financial statements we include non-financial variables such as regional distribution, age, size and legal form into statistical models.
Evaluation of the prediction performance is done with the help of out-of-sample forecasts. We obtain models with quite high predictive power, area under ROC curve reaches 0.75. Random forest outperformed logit-model. Adding non-financial information such as age and federal region leads to the improved forecasts while legal form and size do not have a great impact on the outcome. Among financial measures liquidity, profitability and leverage ratios turned out to be essential. Moreover, our models captured a structural change which was likely to be caused by the crisis of 2008—2009.
The paper presents research question and some results devoted to analyses of companies’ strategic processes in international business networks.
This paper is concerned with stock liquidity as a factor in making capital structure decisions by managers of Russian firms. Although a big number of studies on capital structure occurred over the last few decades, stock liquidity has only recently attracted scholars’ attention as a possible driver for the choice of capital structure. Yet the existing papers are based on data from the developed capital markets. The latter differ substantially from the Russian market in terms of institutional environment and more liquid stocks. Against the background of revisions in the Russian clearing system that are expected to boost liquidity of stocks, this paper gains in currency.
The theoretic mechanisms behind the interplay of stock liquidity and capital structure are discussed in previous studies. Lower stock liquidity is associated with higher transaction costs and informational asymmetry, and thus with higher required return. Therefore it is assumed that the managers aiming at firm value maximization would prefer debt to equity financing in case if stock is not liquid enough. There are also theoretic grounds to expect an opposite impact of capital structure on stock liquidity.
Globalization and growing competition force companies to look for new markets for their business. International operations give companies an opportunity to use their resources more efficiently and simultaneously the internationalization processes increase a firm‘s risks and strategic problems. The choice of an international strategy defines a company‘s priorities on partnership development, which are necessary for a quicker understanding of new markets‘ features, and also for decreasing strategic and commercial business risks. The strategic process is influenced by a number of factors, such as institutional and sociopolitical, and also business-sector specifics and national culture. Strategy development and implementation together with stable network relations define company‘s success in a new market. The paper presents the main results of an empirical research, devoted to analyses of international companies‘strategies and factors, affecting strategic choice and implementation process in the Russian market.
This article provides the results of development of bankruptcy prediction static model and its testing on the sample of more than thousand companies of manufacturing industry. The main scenarios of bankruptcy are identified and it is shown that depending on the bankruptcy scenario possible insolvency can be predicted one or four years before.