Journal of Environmental Treatment Techniques  
2020, Volume 8, Issue 2, Pages: 646-651  
J. Environ. Treat. Tech.  
ISSN: 2309-1185  
Journal web link:  
Financial Distress Prediction across Firms  
Ali Akbar Rafatnia *, Suresh A/L Ramakrishnan , Dewi Fariha Binti Abdullah , Fazel  
Mohammadi Nodeh , Mohammad Farajnezhad  
Azman Hashim International Business School, UTM, Malaysia  
Department of Management, Lahijan Branch, Islamic Azad University, Lahijan, Iran  
Received: 18/11/2019 Accepted: 15/02/2020 Published: 20/05/2020  
One of the most important events in a firm’s life is financial distress, which can propel sectors into financial and sustainable growth  
problems. Moreover, independent variables in the background of financial distress are accounting ratios, which are extracted from financial  
statements and macroeconomic variables that are mostly beyond the control of a firm or sector. The current study analysed the information  
related to a sample of 300 public Iranian companies, during the periods of 2000-2007 and 2009-2016. Logistic regression and decision trees  
were applied to the prediction of financial distress. It was found that the profitability, liquidity, leverage, interest rate, cash flow, accruals,  
and GDP were statistically significant in distinguishing distressed from non-distressed firms across sectors. The obtained results showed that  
the predictive performance of a DT model was more successful than the other model.  
Keywords: Prediction of Financial Distress, Accounting ratio, Decision Trees  
Introduction 1  
The prediction of financial distress is absolutely vital for  
Furthermore, the stakeholders of a firm are generally  
concerned about the accuracy of financial distress predictions  
during business activities. To increase the accuracy of financial  
distress predictions, some studies have introduced different  
statistical and artificial intelligence-based models. For example,  
the multivariate model proposed in (6) was the initial study based  
on the discriminant analysis approach. Literature contains some  
artificial intelligence models that can be effectively used in this  
regard, including Neural Networks (7), Decision Trees (8), and  
Support Vector Machines (9). Furthermore, to increase the  
accuracy of the financial distress predictions, not only the  
financial statements information, but also other available data  
such as macroeconomic factors and market information are taken  
into account. To do an empirical study, the performance of a  
sample of 300 listed Iranian companies, during the periods of  
2000-2007 and 2009-2016, was considered. The whole  
accounting information was extracted from financial reports. Two  
prediction techniques of logistic regression and decision trees  
were applied to the research. The reset of the paper is organized  
as follows. The literature review and hypothesis are presented in  
Section 2, the methodology in Section 3, and finally, the result of  
the study and conclusions are presented in Section 4.  
traders, creditors, and suppliers. To avoid any financial loss, they  
need to assess the financial risk of a firm before they make any  
decisions. Financial distress is not the same as bankruptcy. The  
former occurs while the firm is not able to meet its financial  
obligations due to a decrease in the firm’s operations and  
excessive costs, while the latter is a very last state in which  
corporations stop doing commercial enterprise due to financial  
distress. The bankruptcy needs to be confirmed by a courtroom  
determination; then, its assets are bought to pay and cover all  
obligations of creditors (1). Thus, financial distress does not  
necessarily lead to bankruptcy.  
Based on a review of literature, some researchers implicitly  
suppose that firms’ annual statements give an honest and genuine  
view of the financial state of agencies; although, some annual  
accounts are indeed unreliable (2). Some studies have stated that  
despite the fact that the hyperlink between earnings management  
and financial distress is clear, only few studies have covered such  
indicators in financial distress prediction (3). Earnings  
management can be interpreted beneficial, neutral, or pernicious  
(4, 5). Providing private information on future economic  
performance through management activities, the beneficial  
earnings management improves the financial statements of the  
company. This type of management can be interpreted as neutral  
if earnings management can be economically efficient for  
maximizing ones own utility. Finally, earnings management is  
recognized pernicious when it is about concealing and  
misrepresenting financial reports of the company.  
Literature Review  
Financial ratios are vital for predicting financial distress  
among firms and have been already used by some researchers (6,  
0), (11). Every business has its own economic characteristics  
based on its defined activities. In addition, choosing appropriate  
Corresponding author: Ali Akbar Rafatnia, International Business School, UTM, Malaysia. Email: and  
Journal of Environmental Treatment Techniques  
2020, Volume 8, Issue 2, Pages: 646-651  
ratios well matched with the financial condition of any market is  
the key factor of the study. According to the results of few studies  
with high accuracy among ratios, accounting and macro ratios are  
used. Therefore, this study will attempt to answer the following  
research question:  
Research Question: What are the significant determinants of  
accounting ratios and macroeconomic level variables of financial  
distress prediction among the listed firms?  
shareholders during activities (22). The ratio of working capital  
to total assets is a significant factor that considers the liquidity in  
the firm. If the firm experience operating losses consistently, it  
will have a shrinkage in current liquidity in relation to total assets.  
According to literature, insolvency of businesses is instigated by  
the unsuitable practice of working capital measures, despite  
optimistic revenues or profitability due to such practices. Thus, it  
would be uncertain to just concentrate on profitability while  
overlooking liquidity (23). In addition, in (24), it was found that  
liquidity plays an important role in the determinants of the  
financial distress prediction. Alternatively, liquidity is one of the  
most significant indicators related to financial distress of firms.  
.1. Independent Variables  
.1.1. Accounting Ratios  
The financial distress researchers generally focus on the  
financial reports and market trends of the sectors during specific  
periods. All factors are collected through reliable available  
information. Earnings Management  
In the context of financial distress prediction, banks make  
lending decisions based on the firms’ financial statements  
disclosed (25-27). Financial information creates a loophole for  
firms by managing their earnings to obtain loans with more  
favorable terms. In this regard, the financial statements must  
provide reliable financial information to the external and internal  
stakeholders in accordance with International Financial  
Reporting Standards (IFRS) in a way to be well compared with  
others’ financial statements (28, 29). Collecting, preparing, and  
publishing the financial information is the managers’  
responsibility (30, 31). Earnings management as the process of a  
business uses the generally-accepted accounting procedures for  
the purpose of altering the earnings figures such as delayed  
recognition of expenses, premature recognition of revenue, and  
inventory methods such as last-in, first-out (Lifo) and first-in,  
first-out (Fifo) (32, 33). Remember that the motivation to manage  
earnings depends on the nature of the sectors. Various reasons  
have been suggested in literature for variations in earnings  
management activities including market development, the  
structure of ownership, economic factors, initial public offerings,  
and effective tax rates (34, 35). According to (36, 37), to avoid  
reporting annual losses, firms use earnings management methods.  
In addition, firms under financial distress are likely to take  
different measures in order to decrease the concern of future  
outcome events or any inherently uncertain conditions such as  
window-dressing financial statements (38, 39). In this study, the  
earnings management is discussed in terms of free cash flow of  
the firm and accruals, which is effective on financial distress  
prediction among different sectors.  
.1.1.1 Profitability  
A firm’s extreme survival is based on the profitability of its  
business. In fact, the profitability ratios indicate how well a firm  
has operated during the fiscal year. The static trade-off theory  
indicates that profitable firms are likely to have a high tax burden  
and low cost of bankruptcy (12). Moreover, the profitable firms  
have more capability to tolerate being indebted since they may be  
in a position to easily clear their debt on time. This indicator can  
have a significant role in the bankruptcy investigation. The extant  
studies on financial distress prediction found a significant  
relationship between profitability and financial distress (13).  
Their results suggested that financial distress intensities strongly  
decrease the level of profitability for all prediction horizons  
considered. In addition, the authors in (14) and (15) developed a  
prediction model of financial distress in Iran by Bayesian  
networks and genetic programming models, respectively. Their  
findings showed that when a firm has a good profitability level,  
creditors are sure that their interest’s expenses in the firm can be  
achievable. Moreover, in the context of the Iran economy, the  
authors in (14) found out that higher profitability makes higher  
efficiency and better liquidity, hence lowering default risk.  
Literature widely confirms the existence of a significant  
relationship between profitability and financial distress prediction  
.1.1.2 Leverage  
One of the main variables that explain financial distress is the  
firm’s leverage that can pose a big risk to the firm due to its high  
costs (17). This proxy demonstrates the risk and capital structure  
of a firm. Leverage has been investigated by some researchers in  
terms of its negative effects on the firm performance (18). For  
example, in (19), a significant negative effect of leverage was  
explored on the company’s risk in the non-financial sector. In  
addition, the authors in (20) found out that through the use of the  
agency argument, the benefits of leverage outweigh its cost. The  
most commonly-used leverage ratio in financial distress  
prediction is the debt ratio that is measured by dividing the total  
debt over total assets. Furthermore, some studies have concluded  
that the debt ratio is a significant factor in identifying the firms'  
assets to meet the obligations (21). Macroeconomic Variables  
Macroeconomic factors affect the feasibility of a firm, and  
these external factors are generally beyond the instant control of  
sectors (40, 41). Moreover, the macroeconomic variables causing  
financial distress are the interest rate, inflation, gross domestic  
product, monetary policy, oil price, financial crisis, and debt  
crisis. According to the authors in (42-47), macroeconomic  
indicators affect financial distress prediction. Consistently, an  
interest rate is the main macroeconomic indicator that affects the  
corporate success or failure (48). Furthermore, in (49), the  
interest rate is considered as an important variable that is effective  
on the company’s flexibility and adaptability. It has been also  
suggested that variation in inflation influences firms because of  
the rising cost of production or it may generate higher prices that,  
in turn, causes lower demand. Accordingly, GDP represents the  
economic performance among sectors and any decline in GDP  
causes the recession and other financial crises (50, 51). Financial  
.1.1.3 Liquidity  
A firm is able to pay off the obligations in a timely manner  
and indicate its performance improvement when it holds a high  
liquidity ratio. Therefore, the firms also can pay dividends to