A.azadinamin FinancialdistressSSRN

FINANCIAL DISTRESS: SIGNS, SOURCES, & ELIMINATION 1

Financial Distress: Major Signs, Sources, & Ways to Eliminate Them

Amirsaleh AzadinaminDoctorate of Finance Program

Swiss Management Center (SMC) [email protected]

April 18, 2023

AbstractThis paper looks upon the issue of financial distress as many companies or individual projects run within the company face the issue. Financial distress, how it is defined in various literatures, major signs of distress, methods used in detecting the distress, potential sources of financial distress, and feasible ways in eliminating distress factors are the topics constituting this paper. Financial statements are the main tools in the prediction process as selected ratios are chosen for forecasting the distress. Altman's z-score, which itself could be cited as a byproduct of financial statements, is specifically mentioned here as one of the most used and reliable ways for looking into the future of the company and making valuable assessment in prediction of financial distress and infliction point. Moreover, one could look into the change in the direction of Z-score in addition to perceiving the score as an absolute value. Though the fluctuations and disruptions in cash flows are noted as the cause of distress, one should not forget that the economic cycle and the macroeconomic factors as a whole are some of the main and leading causes of disruptions in cash flows. Macroeconomic factors are indicated as the cause and fluctuations in cash flows are the effect. The remaining part of the paper discusses ways to eliminate the risks influencing and fluctuating cash flows. Some of these methods are change in managerial methods and using financial tools and options which protect the project against uncertainties.

Key Words: Financial distress, prediction, Altman, Z-score, bankruptcy, failure, net present value, negative cash flow, insolvency, macroeconomic factors, negative net present value, NPV.


IntroductionOccurrence of stressor events, like changes in financial variables, sometimes called

negative financial events, can contribute to financial distress (O’Neill et al., 2006). Various definitions and perceptions on the concept of failure exist. In general it is believed that there are two main reasons for the failure of a project or a company. First, the failure may occur due to their withdrawal from uneconomic operations even though they are actually capable of covering their liabilities. The second reason is insolvency which means failing to pay liabilities when they fall due (Tomas and Dimitric, 2011). This definition is very broad but the details will be looked upon in the paper. Bhunia and Mukhuti (2011) offer their view on the essentiality of predicting a financial distress:

Financial distress in companies can lead to problems that can reduce the efficiency of management. As maximizing firm value and maximizing shareholder value cease to be equivalent managers who are responsible to shareholders might try to transfer value from creditors to shareholders. The result is a conflict of interest between bondholders (creditors) and shareholders. As a firm's liquidation value slips below its debt, it is the shareholder's interest for the company to invest in risky projects which increase the probability of the firm's value to rise over debt. Risky projects are not in the interest of creditors, since they also increase the probability of the firm’s value to decrease further, leaving them with even less. Since these projects do not necessarily have a positive net present value, costs may arise from lost profits (p. 210-211)There are various methods developed and used in predicting a financial distress. These

methods may play an essential and preventive role in bringing the firm to bankruptcy. Most researchers have used financial ratios as part of the method. “The derived models are based, for the most part, on multivariate techniques of statistical analysis” (p. 782). These potential sources and quantitative methods used in prediction models will be discussed here in details.

The State of DistressFinancial distress is a subjective phenomenon in which every individual, company, or

project, even with the same levels of income or cash flow, may have different levels of perceived financial distress, and this is the reason that various literatures offer various definitions on financial distress. However, one must know how financial distress is defined and recognized before it can be properly predicted and furthermore prevented. In general, financial distress refers to the inability of a company to pay its financial obligations as they become due (Beaver et al., 2011). Beaver (2006) also sees companies with large overdraft funds, in which the overdraft is not to pay dividends or corporate debt, as companies experiencing financial distress. Pustylnick (2012) believes there are two different types of distress, which are the negative net present value (NPV) and negative cash flow, in which the cash deficit could happen any time in the project due to simply raising operational cost. Kordestani et al. (2011) also review some of the definitions that are offered in literature of finance and economics. They mention financial distress as situation that the outflow of cash outweighs the cash inflow. This will lead to a situation where the company cannot satisfy its financial obligations and hence falling into a


financial distress. In most cases the financial obligation that the company is required to meet is the periodical payments which include the principle and the interest of the loan acquired by the company.

Major Signs and a Prediction Method of DistressIf one thing regarding the detection of financial distress is for certain that is the fact that

analysis on financial statements has been used to assess the likelihood of a distress. Predicting the early signs of distress could be a make-or-break point for corporations and their projects. Jantadej (2006) believes if a company reports loss for three consecutive months, it is financially distressed. He also believes that discontinuation of preferred dividends and the decrease in common stock dividends are signs of financial distress.

"The development of empirical models that successfully discriminated between failing firms and the surviving firms started in the mid 1960s. The pioneer research can be traced back to Beaver (1966) and Altman's (1968) who work in business failure classification" (Meng-Fen and Jui-Chang, 2011, p.71). One of the major applications of financial statements is their ability to look into the future of the project or the company, a look that is based on the findings of financial statements (Bardia, 2012).

Financial ratios have long been used to predict bankruptcy. Beaver (1966) is credited with being the first to propose the univariate model to obtain the probability of predicting bankruptcy using financial ratios. Of the 6 financial ratios he selected from among 29, he concluded that the best predictive variable was cash flow against total debt, followed by the debt ratio and return on assets (Meng-Fen and Jui-Chang, 2011, p.76).Models of financial distress analyze the trends of selected ratios. All such models presume that evidence of financial distress can be traced in selected ratios and distress can be detected at the early stages. Thus, it can be checked by taking appropriate actions immediately to either avoid risk of huge loss or to capitalize on this information” (Wild et al., 2007, p. 540).As for the projects and the stakeholders such as investors, banks, and suppliers detecting

early signs of distress could prevent the bankruptcy events. Detecting the signs early on in the project could be a tremendous help, specifically to smaller stakeholders. This could safeguard them from the takeover attacks by bigger companies. Astebro and Winter (2012) explain the process as they distinguish the two concepts of financial distress and insolvency stating that financial distress is a broader concept than insolvency. The concept of financial distress covers insolvency as well as experiencing difficulty in meeting financial obligations, namely payments. "However, many firms experience financial distress without being in economic distress and, therefore, are likely targets for takeovers" (p. 1). In their study of standard bankruptcy and financial distress models, Asterbo and Winter (2012) focus on accounting data and financial ratio analysis. They emphasize that their approach is rationalized with the argument that inefficient management along with random events could lead to systematic deterioration of firm's financial standing and possibly its failure. They also use Altman's Z-score as a measure in their studies stating that "ratios of solvency, liquidity, profitability, and leverage tend to serve as the most


important indicators of impeding bankruptcy" (p. 2). The hypothesis is simply logical: the greater the operational and financial performance the lower the likelihood of a financial distress. Altman’s Z-score is one of the most reliable indicators of financial distress (Bardia, 2012). In his 10-year research using Altman’s Z-score model aimed at predicting the financial distress of two leading steel manufacturing companies in India, Steel Authority of India Limited (SAIL), and Tata Steel Limited, Bardia (2012) comes to the conclusion that his conclusion from corporations under his research is in complete harmony with the Z-score interpretation, which is a Z-score of less than 1.20 suggests high chances of bankruptcy and a score of over 2.90 implies low or no chances of financial distress. Understanding the Z-score and its power in prediction will surely help the reader in better digesting the concept. Altman’s Z-score

The Z-Score was developed some 30 years ago by Edward Altman, a professor at New York University. Altman, by examining a large sampling of corporate bankruptcies, discovered that certain financial ratios had more predictive power than others in forecasting financial distress and insolvency (Avoid the ‘next Enron’ using Z-scores, 2002, p. 7).Altman’s z-score formula has been used to predict the nearness of infliction or failure for

the company. As Russ et al., (2009) also explain, the Altman z-score was introduced in 1968 and since it has been used as a measure of financial distress. “Numerous papers have been written on the subject of bankruptcy prediction and have suggested alternative methods, but none of these alternatives have replaced the z-score” (p. 59). In the article “Avoid the 'next Enron' using Z-Scores” (2002) the ratios using in the z-score are mentioned. The five factors constituting the z-score are ratios based on financial statements and are as following: working capital to total assets, retained earnings to total assets, return on total assets, market value of equity to total liabilities, and sales to total assets. The order and the weight of each ratio as they are placed in the formula are in the order mentioned above:

Z-Score = 1.2 (X1) + 1.4(X2) +3.3(X3) +0.6(X4) + 0.999(X5)The state of distress is determined based on the score. Financially sound companies have

a score of 2.99 and above. The score of 1.81 and below determines a company that its solvency could be in endangered. Those with the score between 1.81 and 2.99 may be facing financial deterioration leading to a financial distress.

Some may argue that the algorithm may not be solely useful in predicting the performance or failure of that matter per se, but it can also provide a picture on the performance based on the changes in score. As of those proponents Nugent (2003) explains in his book “Plan to win”:

While Altman was looking for a means to predict bankruptcy, his algorithm also works extremely well in determining inflection points, and is the basis of the inflection point analysis discussed herein. That is, inflection points as discussed in this work are only used to highlight changes in business condition – positive or negative – not to predict bankruptcy as Altman envisioned (p. 49).


Nugent (2003) farther explains why one can use Altman algorithm to assess the performance as opposed to solely predicting a failure. He explains that the reason one does not have to use the score as prescribed by Altman is because one can also perceives the change in the score as an indication to changes in performance, as opposed to using the absolute score in predicting bankruptcy. As he plainly puts it:

Nevertheless, we are only using Altman’s algorithm to sense improvement or degradation in business condition – an Inflection Point - one period to the next. Hence, in our application of Altman’s model, the degree of change in score is more important than the score itself (Nugent, 2003, p. 50).Thus, as one can realize from the statement above, Altman z-score could be used to

assess the financial direction and hence the performance of a given company in general, as opposed to solely being used as a prediction model of corporate financial crisis.

Like any tool, Z-Scores should not be the only factor used to evaluate a company’s financial health. Indeed, Z-Scores work better for some industries (such as manufacturers) than others. Also, it is impossible for a single tool, even one as robust as a Z-Score, to capture all of the factors that affect corporate solvency (Avoid the ‘next Enron’ using Z-scores, 2002, p. 7).However, one must keep in mind that prediction models such as the Altman's Z-score

may need modifications. This point is mentioned by Bhunia and Mukhuti (2011) and furthermore justified by Ying and Campbell (2010) in their quantitative study done on Chinese publicly listed companies.

Also, the meaningful variable in determining firm’s stability and viability varies from territory to territory as documented in prior researches. In developed economies, most of the users utilized results from the research done in developed economies without making the certain accommodation to regional situations, which will result in misapplication (Bhunia and Mukhuti, 2011, p. 211).In accordance to the above mentioned point, Ying and Campbell (2010) used the data

from Chinese publicly listed companies for the period of September 2000 to September 2008 to test the accuracy of Altman's Z-score model in predicting failure of Chinese companies. In their study they used three different variations of Z-score: Altman's original model, a re-estimated model in which the coefficients were recalculated, and a revised model which used different variables. Though all three models showed a significant predictive ability, but they could be distinguished from one another based on their strengths. The re-estimated model showed stronger prediction accuracy for predicting non-failed firms. Meanwhile, Altman’s model has higher prediction accuracy for predicting failed firms. In comparison the revised Z-score model has a higher prediction accuracy compared with both the reestimated model and Altman’s original model. It is worth mentioning that the delisting of the firm from the stock exchange was taken as financial failure of the given firm unless those firms were taken off due to two reasons: merger or privatization and illegal financial activity. Firms that were taken off due to these two reasons could still be very well in a sound financial position. So, the authors Ying and Campbell (2010) perceived the firm failure from the investors’ standpoint. The stocks of the firm become


worthless since there is no platform for exchange of the stocks any more. "The delisted firm in general will continue operating for a period of time, but shareholders have essentially lost their investment" (p. 79). Table 1 illustrates the Z-score coefficient calculations attained from these firms' financial statements two years prior to the delisting for all firms who were delisted between 2000 to 2008.

Figure 1: Descriptive statistics for estimation subsample and prediction subsamples using the data two years prior to the delisting from 2000 to 2008 (Ying and Campbell, 2010).

The next table (table 2) illustrates that the revised model has a comparatively more accurate prediction capability than both other models, Altman's model as well as the re-estimated model, though all three models are showing strong capability in indication financial distress and ultimately leading to failure and delisting of the company from the stock exchange market.


Figure 2: Comparison of classification accuracies of different models used by (Ying and Campbell, 2010)

The study done by Ying and Campbell (2010) clearly "indicates that the Z-score model is a helpful tool in predicting failure of a publicly listed firm in China" (p. 75).

Potential Sources of Financial Distress and Ways to Eliminate ThemFinancial and non-financial sources could act as major sources of a financial distress, in

which the non-financial sources could have a negative impact on financials of the company, and hence, leading to the state of distress. Pustylnick (2012) mentions that there are various reasons for the project to be in distress which include financial and non-financial factors such as managerial, organizational, and financial reasons. "Projects can suffer from poor performance due to objective conditions such as supply delivery faults, fluctuations in quality and labor force availability. The majority of these reasons have nothing to do with financial elements of the project" (p. 125). Studies have attributed financial distress to a number of factors that include, for example, “economic turbulence, change in demand, high debt, restrictive monetary policy, high interest rates, inadequate capital structure and poor financial management” (Madrid-Guijarro et al., 2011, p. 159).

Nonetheless, they can very much influence the financials and the flow of cash. In his study to recognize the financial distress Pustylnick (2012) discusses two types of distress, "namely negative NPV and negative cash flow" (p. 152). In a way they may seem similar but one may lead to the other one and each have very different scenarios as consequences. In this paper there is more emphasis on the financial sources than non-financial ones. Economic Cycle and Macroeconomic Factors as a Source

Even though fluctuations in cash flow may be cited as a cause leading to financial distress they are not the cause, but solely indicators which are influenced by other factors or real causes. In other words, systematic risk of the market has a major influence of the financial standing of the company or the project. Systematic risk is referred to as the change of the financial standing of the company that is in direct relation with the financial standing of the economy and overall market changes. This change that is led by a change in market cannot be diversified away and will influence all companies and projects operating within that market (McAlister et al., 2007). Tomas and Dimitric (2011) cite a study by Fisher in 1933 explaining


that companies that are highly in debt start to feel financial pressure in times of recession. In order to pay creditors they are to sell their assets and deposits.

This results in the decrease of asset values/prices which in turn reduces the net worth of all companies and consequently increases the probability of bankruptcy. If deposits and loan repayment decrease, they cause further disturbances in money markets and drop of prices. Furthermore, if this is accompanied by the rise in real interest rates it additionally makes the situation of already indebted firms even more difficult” (p. 787). Having mentioned the above points it should be kept in mind that in the meanwhile the

financial standing of the company determines whether it would be granted a loan or credit. On the other hand the macroeconomic conditions determine to a great extend whether banks are willing to grant loans or credits. The deterioration in macroeconomic condition may lead to credit contraction, not solely due to the banks’ unwillingness to extend loans but also due to the unwillingness of the companies to acquire loans in cases of interest rate hike. This condition will only accentuate the financial distress that the company faces. Furthermore, Wadhwani (1986) studies the variables influencing the liquidation rate of companies and discovered that inflation plays a major role. He found out that the increase in interest rates can inversely affect the company solvency. The nominal interest rate will increase the interest expenses of accompany or a given project and if this is not followed by a proportional increase in the company’s revenues the company may find itself in trouble.

The cyclic movement of economy and the changes in macroeconomic conditions that have resulted from a systematic risk of economy influence the volatility of cash flows and thus increase the risk of a failure of businesses. The macroeconomic conditions, or in other words, the variables that have an effect on the failure of a business should therefore be included in the explaining and predicting risks of business failure and insolvency” (Tomas and Dimitric, 2011, p. 793).Pustylnick (2012) mentions the negative NPV as one of the two major types of financial

distress. The negative NPV problem is mostly correlated with the macroeconomic factors as opposed to the negative cash flow issue that is more related to raising operational cost and managerial inefficiency. Pustylnick (2012) explains in vivid terms how the change in economic climate can lead to the change in NPV valuations and hence, provide a picture of a financial distress.

The NPV calculations commonly rely on two major components, namely an initial investment and the cash returns from the construction and maintenance work. The NPV calculations use a discount rate to bring the future values to their present equivalents. This rate represents the best possible estimation effort based on the knowledge and the experience of those, calculating NPV. Since large projects have a large number of lenders in syndication, those lenders must agree on the common discount rate for the calculations of the financial outcome for this particular project….The financial and economic conditions in the country where the project take place and in the financial world change on regular basis. Therefore, the NPV calculations are due for every report period to reflect changing rates of inflation (discount rates) (p. 130-131).


Eliminating the Effect of Macroeconomic FactorsThe source of distress that was discussed above is related to systematic risk in the

economy and may prove hard to prevent or to be eliminated. Although NPV has no immediate effect on the project and whether it will be completed it can still be used as a valid factor in estimating a relative financial position of the project at any time during its life cycle (Pustylnick, 2012). However, there still exist financial tools that managers can utilize in addition to making sound managerial decisions to lessen these effects. The increase in interest expenses may only pressure the firm into a financial distress in case the amount of debt is substantial. Since the interest expense is a portion of the loan itself the interest expense only increases with the amount of debt. To prevent this, companies must act very cautious in acquiring loan and hence try in decreasing their leverage ratio. In case huge amounts of loan must be acquired by the company, managers must utilize financial tools to lessen the effect of those unforeseen events, such as interest rate hikes. One can immunize/hedge himself against the interest rate exposure by means of interest rate swaps which involves the exchange of fixed-rate for a floating rate interest payment and has been used since 1981 (Schroder and Dunbar, 2011). Cherneko and Faulkender (2011) mention that nonfinancial firms must use interest rate derivatives to hedge against interest rate risk and reduce the expected cost of financial distress. In addition they can also avoid costly external financing by better matching internal cash flow with financing needs.

[F]irms can use interest rate swaps to hedge or speculate in interest rate markets, but they can also do so via the choice of the interest rate exposure of their debt. As pointed out by Faulkender (2005), a firm that issues a floating-rate debt security and then swaps that debt security to a fixed rate exposure (using an interest rate swap that matches i) the face value of the debt to the notional value of the interest rate swap, ii) the frequency of interest payments, iii) the index of the floating rate (e.g., 6-month London Interbank Offered Rate (LIBOR)), and iv) the maturity of the debt) has the same interest rate exposure as a firm that issues a fixed rate liability (p. 1732)

Negative Cash Flow as a Potential Source of Distress As Pustylnick (2012) mentions, "[n]egative cash flow or cash deficit can happen in the

project at any time. This phenomenon is usually connected with raising operating cash" (p. 152). The negative cash flow problem that is caused by cost overruns could be divided into three main types as Pustylnick (2012) states that cash flows have an immediate effect on the operation of he project and further explains the following as reasons of changes in cash flows: (1) raising cost of material, machinery, land and labor and in general current expenses. This problem is much likelier to happen in projects with longer durations as the cost is susceptible to the long-term inflation rate. As the project prolongs the cost of input rises with the general inflation rate. This could be especially troubling if this fact was not taken into consideration in the financial planning phase. (2) Increased cost of maintenance due to a new legislation that goes into effect immediately soon after. Changing various safety protocols or regulatory standards may provide examples of this type. If the cost that are brought by these unforeseen events amount to a considerable sum they may cause financial distress. (3) Delay in execution that may be either caused by mismanagement in the schedule execution or by the contractual conflict causing


negative cash flow. Many times lack of availability of a certain resource may delay the project or even brings along additional lease payments for unused equipment. This is a result of inefficiency or ineffectiveness of the management in charge. Eliminating the problem of Negative Cash Flow

One possible solution that crosses the mind in eliminating the problem of a negative cash flow is providing extra cash by the equity holders. However, this solution may have its downfalls as well.

First of all, every equity holder must agree on this cash follow to happen. The additional loan usually carries an effect of decreasing of equity value (very similar to the effect of share split). If the project is perceived as having troubles, then selling additional debt to raise cash may not be easy (Pustylnick, 2012, p. 152). The second approach may be raising additional cash flow from resources within the

project itself. In this regard raising cash may be a tedious task that will materialize solely after various unnecessary or redundant costs are cut. Raising cash in here may also mean prevention of wasting cash. There are usually numerous advisors and consultants involved in the process of project financing of which one of their main tasks is contribution to cut waste and finding the places in which cash is not being used as efficient. Also, in order to eradicate the negative cash flow problem, Pustylnick (2012) also adds the following:

Any project distress caused by negative cash flow is certainly fixable. The project companies and lenders are inclined to negotiate the restructuring of debt rather than to change the project structure. With all things being equal, the restructuring of debt lowers risk and decreases uncertainty better than the change of management. If all parties are honest with each other and attempt to perform to the best of their abilities, the restructuring of debt would be much less taxing on the project company and the lenders, than hanging the project management and the contractors (p. 130). Ward (1994) also mentions that events causing the initial decrease in total cash flow are

often industry related and the options that the management has at his/her disposal may differ depending on the industry and financial structure of the company. His solutions to revive the negative cash flows are as the following:

Management has many strategies for corrective action to regain cash flow equilibrium to avoid financial distress. According to Heath, some of these strategies to avoid financial distress include: (1) borrowing money, either directly by borrowing from banks, selling bonds, etc., or indirectly by delaying payments to creditors, and allowing accounts payable to build, etc.; (2) liquidating assets either directly by selling assets, or indirectly by failing to replace inventory as the inventory is sold or failing to replace fixed assets consumed in operations, etc.; (3) reducing costs; (4) reducing dividends; and (5) issuing capital stock (p. 21). The success of management's attempts to regain cash flow equilibrium dictates whether a firm recovers or progresses toward eventual financial distress (p. 1).

Concluding Remarks


Many researchers have used quantitative analysis in predicting financial distress which is heavily focused on financial ratios that are themselves drawn out of financial statements i.e. balance sheet, income statement, and the statement of cash flows. The quantitative methods base their finding as well as their logic on the assumption that numbers do not lie and one can find all relative information in financial statements. The assumption is not far from the truth as selected ratios calculated from financial statements have had the ability to look into the future of the company and predict disasters. The most notable and at the center of these quantitative methods has been the z-score, a number that provides a reliable assessment of company's financial standing. Another area that the z-score is helpful is the direction it moves, which provides a better picture on the direction of the company rather than where the company stands. However, the quantitative analysis may fall short in presenting a complete picture because these statements are influenced by other factors. High fixed cost, illiquid assets, and cash flows that are sensitive to economic turns are all potential reasons of entering a financial distress. Price index inflation and changes in the interest rates are two of the prominent macroeconomic factors that can hugely influence the finances of a corporation or a project.

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