1. Financial Distress: When Bad Things Happen to Good Companies
Turnarounds
Financial Distress:
When Bad Things Happen to Good Companies

2. Financial Distress Risk
View from an outsider’s perspective
investors
creditors
Also useful for evaluating prospects of
customers
suppliers
Useful platform for crafting and insider’s response

3. Focus of All Financial Analysis
Profitability
past and current performance
Risk
will the future results be like the past?

4. What Do Investors Worry About?
A decline in investment value
systematic risk (beta)
impact of changes in macroeconomic circumstances
prices (inflation)
interest rates
economic growth (recession)
employment
how firm compares to market
principle components
variability of sales
operating leverage
financial leverage
nonsystematic risks
risk of casualty, bankruptcy etc.
Investors are interested in return but know that returns are related to risk
Dealing with investment risk
choose beta you are comfortable with (beta is covariance of company returns with market returns)
diversify away nonsystematic risk
Markets respond continuously to risk changes
reduction in economic profitability, means increased risk, means stock price gets bid down
market price of public company is a risked adjusted forecast of future profits
not much value if turnaround is an issue

5. What Do Creditors Worry About?
Inability to collect (principal and/or interest)
in concept quite similar to systematic risk
higher risk → higher interest rate
situation is different post-issue if debt is nonmarketable (e.g., bank loan)
fixed future returns
limited options for dealing with increasing risk
debt covenants
requires careful ex ante analysis
lenders have a fixed return perspective and priority over equity so beta is not a good measure of their risk/return payout
have to do their own analysis—no market prices to consult

6. Understanding the Profit Drivers

7. Basic DuPont Framework
(ROE)
ROA

8. Getting Data
Don’t need to calculate the ratios yourself. Many services available.
For example, Hoovers is available via Library (value added version)
The Container Store

9. Profitability eVal KOHL’s
Longer trend would be useful but it is too difficult to go back because then because the data has to be hand entered. (WOULD DO IT FOR REAL MONEY ANALYSIS)

10. Short-Term Liquidity Risk
Focus on current assets--source of near term cash
current position and trends
liquidity ratios
quantity of current assets (in relation to liabilities)
turnover ratios
quality of current assets
less focused on long-term profits but also useful for investment analysis

11. Short-Term Liquidity Risk
Current Ratio = Total Current Assets
Total Current Liabilities
Quick Ratio =
Cash + Marketable Securities + A/R

12. Current Ratio Benchmarks? eVal KOHL’s
old 2:1 rule of thumb no longer valid--now closer to 1:1
Benchmarks?

13. enables more aggressive working capital management
Why?
IT revolution
enables more aggressive working capital management
just-in-time ●
reasons--enhanced information technology allows more aggressive working capital management; JIT ●

14. Industry Norms (by SIC Code)
Current Ratio: mean
Major Airlines 0.6
Integrated Oil and Gas 1.2
Auto Parts 1.3
Department Stores 1.6
Jewelry Stores 2.8
Need industry benchmarks --substantial variation across industries

15. Receivables Turnover Ratios
Accounts Receivable Turnover =
Sales (Net)
Average Accounts Receivable
Days Sales in Accounts Receivables =
365
Accts Receivable Turnover

16. Inventory Turnover Ratios
Cost of Goods Sold
Average Inventory
Days Sales in Inventory =
365
Inventory Turnover

17. Payables Turnover Ratios
Accounts Payable Turnover =
Purchases*
Average Accounts Payable
Days Purchases in AP =
365
Accounts Payable Turnover
*purchases = CGS + EI - BI

18. Operating Cycle The cash to cash cycle Approximately:
purchase
inventory
sell
inventory
collect
on sale
Approximately:
Days Sales in A/R + Days Sales in Inventory
Including ‘the float’:
‘days financing required’ =
Days Sales in A/R + Days Sales in Inventory – Days Payables Outstanding

19. Operating Cycle for Kohl’s
eVal
Days Rec
Days Inv
Days Pay
Net

20. Long-Term Solvency Risk
Interested in prospective debt paying ability
profitability (ROA, ROE)
and future prospects
amount of debt outstanding
financial leverage

21. Debt Load Long Term Debt to Total Assets Ratio = Total Long-Term Debt
Long Term Debt to Equity =
Total Long-Term Debt
Total Common Equity
omit non debt liabilities because they come for ‘free’--no interest cost

22. Long-Term Solvency Risk
Interest Coverage Ratio =
Earnings Before Interest and Income Taxes
Interest Expense
Operating Cash Flow (OCF) to Cash Interest Cost =
OCF + Cash Paid for Interest + Taxes
Cash Paid for Interest

23. Predicting/Explaining Ratio Results
What if different measures provide conflicting signals?
can use multivariate statistical models
powerful predictive tools
combine signals from individual measures
synergy

24. Prediction Models Altman’s Z score model (MDA)
old (1968) but easy, reliable and robust
Z = 1.2 (WC ÷ Assets) (R/E ÷ Assets)
+ 3.3 (EBIT ÷ Assets) + .6 (MV Equity ÷ Liabilities)
+ 1.0 (Sales ÷ Assets)
Marketed to banks and others
interpretation
above 3.0—low probability of bankruptcy
between 3.0 and 1.81—moderate probability
below 1.81—high probability
developed based on industrial companies
determining appropriate cutoffs depends on risks associated with prediction errors

25. P5.17

26. Easing the Altman Calculation
CreditGuru.com
search for z score calculator
search for z-score calculator

27. Predicting/Explaining Credit Risk
Substantial follow-up research
increasingly ‘proprietary’
Important refinements
cost of misclassification
focus on distress not bankruptcy

28. Cost of Misclassification
Altman’s 1.81 cutoff value?
cutoff probability value ≈ 20%
implied 4:1 cost ratio
Recent estimates range as high as 50:1

29. Defining Failure Bankruptcy the focus in early studies
actually a remedy for default
bankrupt
(TDR)
(Merged)
nonbankrupt
(Default)
alternative remedies
troubled debt restructuring (work out)
merger
choice based on structural issues
merger vs. bankruptcy
size
leverage
management control
distressed
TDR
Merged
nondistressed
Default
Bankrupt
texts typically look at early studies
bankruptcy vs. TDR
creditor concentration
Distress is a better definition of failure

30. Predicting/Explaining Distress
Other issues
statistical sophistication
MDA → LOGIT/PROBIT
greater reliability, easier interpretation

31. Predicting/Explaining Distress
Important variables (dimensions)
profitability (earnings or cash flows)
capital investment spending
short-term solvency
asset turnover (receivables, inventory)
long-term debt capacity
size
capital investment spending is particularly important for companies like “A Better Place”

32. How Reliable are the Financial Statements?
Presumption they are reliable
can be predicted using another model
Potential issue revealed by Enron

33. Predicting Fin. Stmt. Manipulation
Extension of failure prediction methodology
Beneish’s 8 factor (probit) model
days sales in receivables index
gross margin index
asset quality index
sales growth index
depreciation index
selling and administrative expense index
leverage index
total accruals to total assets

34. Beneish’s y distributed as a cumulative normal function

36. P5.19

37. What About Small Business Settings?
Ratio analysis still makes good sense
be careful using previous models on small firms
because they were developed based on large publicly held firms
small firms can experience dramatic fluctuations in profits year-to-year
lack of product/service portfolios
Credit Guru site provides versions of Altman’s model tweaked for nonpublic market place

38. Summary Financial distress
traumatic outcome for investors and creditors
focus of dynamic analyses
lots of tools at their disposal
ratios
statistical models
for companies in trouble
outsiders probably already know
important to solve problems
restore profitable operations
reassure creditors and investors