fsa-lec 3(financial distress)

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    FINANCIAL DISTRESS

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    Topic: Financial DistressInstructor: M. Jibran [email protected]

    FINANCIAL STATEMENT ANALYSIS

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    What is Financial Distress? A situation where a firms operating cash flows are not

    sufficient to satisfy current obligations and the firm isforced to take corrective action.

    Financial distress may lead a firm to default on a contract,and it may involve financial restructuring between the firm,its creditors, and its equity investors.

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    Definition of Terms

    Default Failure to meet an

    interest payment, or

    Violation of debtagreement

    Bankruptcy Formal procedure for

    working out default Does not automatically

    follow from default.

    Financial Distress Includes default and

    bankruptcy, but also

    Threat of default orbankruptcy and its effecton the company

    Defined to capture the

    costs and benefits ofusing large amounts ofdebt finance

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    Financial DistressA company that is not generating enough cash flow to make acontractually required payment will experience financial distress.

    May result in:

    Dividend reductions

    Plant closures

    Losses

    Layoffs

    Management resignations

    Plummeting stock prices

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    Insolvency Stock- base insolvency; the value of the firms

    assets is less than the value of the debt.

    AssetsDebt

    Equity

    Solvent firm

    Debt

    Assets Equity

    Insolvent firm

    Debt

    Note the negative equity

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    Insolvency Flow-base insolvency occurs when the firms cash flows

    are insufficient to cover contractually required payments.

    Contractualobligations

    Insolvency

    $

    Firm cash flow

    Cash flowshortfall

    time

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    What Happens in Financial Distress?

    Financial distress does not usually result in the firmsdeath.

    Firms deal with distress by Selling major assets. Merging with another firm. Reducing capital spending and research and

    development. Issuing new securities. Negotiating with banks and other creditors. Exchanging debt for equity. Filing for bankruptcy.

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    Reorganizeand emerge

    Merge withanother firm

    Liquidation

    83%

    10%

    7%

    What Happens in Financial Distress

    Financialdistress

    Financialrestructuring

    No financialrestructuring

    49%

    51%

    Legal bankruptcyChapter 11

    Privateworkout

    47%

    53%

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    Responses to Financial Distress Think of the two sides of the balance sheet. Asset Restructuring:

    Selling major assets.

    Merging with another firm. Reducing capital spending and R&D spending.

    Financial Restructuring: Issuing new securities. Negotiating with banks and other creditors. Exchanging debt for equity. Filing for bankruptcy.

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    OPTIONS IN FINANCIAL DISTRESS

    For a company in financial distress various procedures can be followed: If a creditor has made a loan secured on assets of thecompany then it can appoint a receiver to recover the debt if the

    company defaults on interest or capital repayments. The receiver may sell the business, or parts of it, as a goingconcern. However, the duty of the receiver is to the creditors and oncesufficient funds have been obtained he is under no duty to maximizevalue of remaining assets. He may even choose to liquidate all assets,

    pay creditors and pass any residue to shareholders. Another procedure, called administration , attempts to rescuefailing companies and protect workforce. Appointed by a court at therequest of the directors, the Administrator attempts to reorganize thecompanys finances and its operating structure,

    protecting the company from its creditors.

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    Bond Corporation In 1990, the Bond Corporation, an Australian media group,was seeking to realize assets to repay huge debts,estimated at A$8 billion. The chairman, Alan Bond, was obliged to sell Australias Channel Nine TV network for only A$88 million to Kerry Packer, who had sold it to the Bond Corporation for A$490 million only two years earlier.

    Empirical studies (e.g. van Horne 1975; Sharpe 1981)have suggested that liquidation costs, including legal andadministrative charges, may lower the resale value ofdistressed companies by 50% or more.

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    THE PREDICTION OF FINANCIAL DISTRESS

    The use of financial ratios to try to predict the financialdistress of companies has always been attractive. Two of the types of model developed to predict

    financial distress using financial ratios are: models that use single ratios to predict distress(univariate models )and

    models that "add up" many ratios and come up with atype of credit rating score ( multivariate models ).The basis of models is that financial ratios of companiesfacing financial distress differ from the ratios of morefinancially "sound" companies.

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    Groups with interest in distress prediction models

    Management

    Investors

    Lenders

    Auditors

    Society

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    Univariate models of distress prediction

    A univariate approach to distress prediction involves theuse of a single ratio in the model.

    This is based on the following assumptions: That the mean of a ratio for distressed companies

    will differ from the mean of the same ratio

    of non-distressed companies. That this difference can be used for prediction

    purposes.

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    Univariate models of distress prediction

    There are four steps to develop the model Step 1 : take two large samples of companies that are of similar size inthe same industry - 50% non-distressed, 50% distressed. S tep 2:decide which ratio to calculate for all companies. Forexample you may think that the ratio which is most likely toindicate financial distress is the gearing ratio. Step 3 : calculate the mean of the ratios for each sample.

    Distressed Non Distressed Gearing ratio 78.5% 47.6%--Step 4 : d ecide where the cut -off point should be. e.g. one could say

    that a company with a gearing ratio of less than 47.6% is likely to be"safe" and that a company with a gearing ratio of more than 78.5% islikely to suffer financial distress.

    But, what could you say about a company with agearing ratio of 60%?

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    You can make two types of error, as follows: Type I error Distressed company is predicted to benon- distressed

    Type II error A non-distressed company is predictedto be distressedThe "cut-off' point should minimize the total number oferrors.

    To achieve this a table should be set up like the one below.The figures in this table are "made-up" to illustrate thetechnique.

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    Univariate model studies

    Cut-off point

    Number of type 1errors

    Number of type IIerrors

    Total number oferrors

    Gearing ratio:

    >50% 0 4 4 >55% 0 3 3 >60% 1 1 2 >65% 2 1 3 >70% 3 0 3

    The cut-off point that minimizes the total number of errors is a gearing ratio ofgreater than 60%. One could deduce that companies with gearing ratios ofgreater than 60% are likely to become financially distressed.

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    Univariate model studies Beaver (1966) compared patterns of 29 ratios in the 5years preceding bankruptcy. The purpose was to see whichratios could forecast bankruptcy and how many years inadvance the forecast could be made. Cash flow/total liabilities proved to be the best

    predictor overall. In the year prior to bankruptcy this model had a 13%

    misclassification rate. There was a greater frequency of Type I errors

    relative to Type II errors. The difficulty increaseddramatically with the time horizon.

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    Univariate models of distress prediction

    A summary of all the Univariate prediction studiespublished over 20 years was carried out in 1983. Thissummary found that three financial ratios consistentlyoutperformed all the rest in predicting financial distress.These were: Rate of return Gearing ratio Times interest covered ratio.Univariate prediction models can end up giving different

    predictions for the same company depending on the ratiosused.

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    Multivariate models of distress prediction

    Multivariate prediction models add several ratios togetherto come up with a score.As with univariate models a cut-off point is chosen. Scoresabove this point are normally considered to indicate afinancially safe company and scores below, a potentialfinancially distressed company.Altman, an American academic, was one of the first peopleto produce a multivariate model. His Z-score model (1968)is the best known. (Altman E. 1968. Financial ratios,discriminant analysis and the prediction of corporatebankruptcy. The Journal of Finance 23 (4): 589-609)

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    The cut-off points Altman reported were:-

    Assign to non-bankrupt group if Z>2.99

    Assign to bankrupt group if Z

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    Caution The Z score has had some success in the real world. Itcorrectly predicted 72% of bankruptcies two years prior tothe event. Z score profiles for failing businesses oftenindicate a consistent downward trend as they approachbankruptcy.Some Cautions

    The Z-score has been demonstrated to have some use ina variety of contexts and countries. It is NOT designed tobe used in every situation and certainly not alone. Before using a Z score to make predictions, one mustensure the firm being examined is comparable to thedatabase.

    Two major issues are discussed below.

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    Privately Held Firms If a firm's stock is not publicly traded, the X4 term (MarketValue of Equity/Book Value of Debt) cannot be calculated.To correct for this problem, the Z score can be re-estimatedusing book values of equity. This provides the followingscore:Z = 0.7A + 0.8B + 3.1C + 0.4D + 1.0EThe predetermined cutoffs for the Z-score are as follows:

    Bankrupt less than 1.23 Zone of ignorance 1.23-2.90 Non-bankrupt greater than 2.90

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    Non-manufacturing Firms The final (Sales/Total Assets) ratio is believed to vary significantly byindustry. It is likely to be higher for merchandising and service firmsthan for manufacturers, since the former are typically less capitalintensive.Consequently, non -manufacturers would have significantly higherasset turnover and Z scores.The model is thus likely to under predict certain sorts of bankruptcy. Tocorrect for this potential defect, Altman recommends the followingcorrection that eliminates the final ratio:

    Z = 6.6A + 3.3B + 6.7C + 1.0D The predetermined cutoffs for the Z score are as follows: Bankrupt less than 1.1 Zone of ignorance 1.1-2.6 Non-bankrupt greater than 2.6

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    Small Firms Altman's original data sample consisted of large firms withassets in excess of $1 million. The most recent model hadbusinesses with assets averaging approximately $100million.If it is believed that smaller firms have significantly differentratios from larger entities, then the use of Z scores may notbe appropriate.QuiScore:

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    Qui Credit Assessment LtdQui Credit Assessment Ltd have extensive experience in the credit industry. The work reflects currenteconomic conditions and includes post mortems on failed companies. The credit rating on fame

    comprises the QuiScore and the QuiRating . The QuiScore is given as a number in the range 0 to100. The range may be considered as comprising five distinct bands.81-100 The Secure Band : Companies tend to be large & successful public companies. Failure is veryunusual and normally occurs only as a result of exceptional changes within company or its market.61-80 The Stable Band : Company failure rare and will only occur if major company/market changes.41-60 The Normal Band : The sector contains many companies that do not fail, but some that do.21-40 The Unstable Band: Significant risk of company failure: companies in this band are on averagefour times more likely to fail that those in the Normal Band0-20 The High Risk Band: C ompanies in the High Risk sector are unlikely to be able to be able tocontinue trading unless significant remedial action is undertaken. Low score does not mean that failureis inevitable.Interpreting the QuiScore QuiScore based on statistical analysis of a random selection of companies. To ensure that the modelis not distorted, three categories are screened out from the initial selection: major public companies,companies that have sort insignificant amounts of unsecured trade credit and liquidated companiesthat have a surplus of assets over liabilities.The QuiScore is intended to be an aid to the financial part of the overall assessment, and has to beconsidered in conjunction with other information such as seasonal trends, product life cycles,competition, interest rates and other micro and macro-economic factors. The stability of manycompanies is reliant of that of holding companies or other associates on which separate enquiriesshould be made.

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    MYTRAVELAs at 30/9/04, MyTravel had a QuiScore of 10 HIGHRISK.

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    The Independent (London) January 15, 2005, SaturdaySECTION: First Edition; FEATURES; Pg. 17HEADLINE: THE WEEK IN REVIEW: MYTRAVEL FACES UNCERTAIN FUTURE

    When MyTravel's 800m debt-for-shares swap was signed and sealed before Christmas, there wasa temptation to cry that the UK's biggest tour operator was "back from the brink". Certainly, the threatof bankruptcy has receded, but restructuring is just the start.

    Management has to hack its way through a thicket of costs before it can be certain of reaching afinancially viable business. MyTravel could still find that it does not have the cash to pay for the vitalcuts. Profits have been restored in MyTravel's Scandinavian and North Americanbusinesses, so the management is establishing its credentials. If everything goes according to the planagreed with the creditors-turned-shareholders, the current share price could well be

    justified.

    But UK consumer spending looks to have peaked and MyTravel could be looking to reverse losses inits core UK market just as demand turns down. The future of the package holiday itself is still beingredefined by budget airlines and internet booking. Terror attacks continue to be a threat.Though the possibility that you might be getting in at the bottom is tempting, MyTravel shares cannot,at this stage, be responsibly recommended.

    LOAD-DATE: January 15, 2005

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    Red Flags for Stoddard International

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    Weaknesses of distress prediction models

    The problem of "self-fulfilling prophecies." It could be that companies become distressed financiallybecause investors perceive companies with certaincharacteristics as being more risky and therefore bydemanding higher returns (in the form of higher interestrates) cause the companies to become distressed. They are not based on any theoretical model of distress.

    It is not as yet clear, if they do work, how they work. However, they could have a function as a "legitimating

    device . Bankruptcy is a legal, not an economic phenomenon.All models are based on the past, when macroeconomicconditions were different from the present.

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    SummarySince the ultimate objective in forecasting failure should be to providean "early warning system," practitioners should adapt a multivariatemodel that is compatible with their abilities and available data sources.Each of the methods developed for forecasting financial failure willprovide indicator scores or cut-off points. However, as with anystatistical method, it is necessary to remember that judgement is still animportant determinant. A number of business failures may not bepredictable from financial data, such as those arising from large productliability judgments or catastrophic natural calamities. Further, somefinancially healthy firms have sought the protection of bankruptcy to

    achieve other purposes, including the avoidance of burdensomecollective bargaining agreements or extensive litigation. Therefore, theforecasting techniques should be used as they were intended--as atool--and not as a final decision point.