1. ACCOUNTING- AND FINANCE-BASED MEASURES OF RISK

2. Introduction An important objective of the analysis of financial statements in general and that of ratios in particular is an assessment of the risk inherent in a firm’s operations –Credit risk –Equity risk One indicators used to forecast financial risk measures is firm’s earnings variability

3. Earnings Variability and Its Components The variance of a firm’s earnings is a direct measure of the uncertainty (risk) of its earnings stream A smooth earnings stream is assumed to be desirable by firms, their creditors, and the financial markets To the extent that accounting earnings mirror a firm’s economic well-being, the variance in that measure would be expected to measure a firm’s risk

4. Earnings Variability and Its Components Earnings volatility is primarily related o the underlying uncertainty of demand for the firm’s output  the variability of its sales The effect of sales variability on earnings variability is a function of the firm’s operating and financial leverage Earnings variability has a systematic as well as unsystematic component  the systematic component is referred to as the accounting beta (B)

5. Components Operating and Financial Risk –Operating leverage is the percentage of fixed operating costs in a firm’s overall cost structure –Financial leverage is the percentage of fixed financing costs in a firm’s overall cost structure The higher the percentage of fixed costs, the greater the variation in income as a result of variation in sales

6. Components Measures of Financial and Operating Leverage –Financial leverage: use surrogates (times interest earned, debt/equity, debt/assets) –Operating leverage: Using regression analysis: TC = F + vS TC = total cost, S = Sales, F and v = estimates of firm’s fixed costs and variable costs Ratio of fixed assets to total assets

7. Components Accounting Beta –Systematic factor reflects the degree to which the earnings of the firm vary with the earnings of other firms in the economy (accounting beta): E = a + B earnings ME E = firm’s earnings, ME = index of market earnings, B earnings = accounting beta

8. Credit Risk The focus of credit risk is the risk of default, resulting in loss of principal and interest. The ultimate form of default is bankruptcy

9. Credit Risk Bankruptcy prediction –The ability to predict which firms will face insolvency in the near term is important to both potential creditors and investors –Considerable research into the use of ratios and cash flow data to predict bankruptcy

10. Credit Risk Bankruptcy prediction –2 types of misclassification errors: Type 1 error: misclassification of a firm by predicting nonbankruptcy when in reality the firm becomes bankrupt Type 2 error: misclassification of a solvent firm as bankrupt Type 1 error is more costly than Type 2 error

11. Credit Risk Research results –Univariate Models Beaver (1966): cash flow/total liabilities proved to be the best predictor overall –Multivariate Models Altman: Altman’s (1968) Z-score model and ZETA model [Altman et al. (1977)] Ohlson (1980) Gentry et al. (1985b): a model that combined cash flow variables with financial ratios performed better than one based on cash flows or financial ratios alone

12. Credit Risk The Prediction of Bonds Ratings –The ratings attest to the creditworthiness of the firm –The higher the ratings, the lower the probability of default –To compensate for higher default risk, lower- rated bonds are issued with higher yield

13. Credit Risk Impact of ratings: –The higher the rating, the lower the interest rate required –The covenants written into bond offering are often designed to obtain favorable ratings. Some covenants are specifically tied to ratings, and may require a higher interest rate or redemption if the rating fall below a specified level –Many institutional investors are restricted to debt with minimum debt rating

14. Credit Risk Usefulness of Bond Ratings Prediction –Most firms have unrated debt –Ratings are not continuously revised, and there is evidence of considerable lag –Firms sometimes undertake large investment or acquisition program –Independent variables in a predictive model can provide insight into the important factors that determined the (perceived) riskiness of debt –Ratings at the lower end of the spectrum may be inconsistent and rigid

15. Equity Risk: Measurement and Prediction Risk and Return –Risk: Unsystematic risk: factors specific to the firm –Diversification eliminates unsystematic risk Systematic risk: factors common across a wide spectrum of firms –The only risk measure that remains relevant –E(Rt) = a + β e E(Rm)  β is a measure of systematic risk

16. Equity Risk: Measurement and Prediction Importance and Usefulness of Beta –To construct investment portfolios with the desired risk and return characteristics, you must know the beta of individual characteristics –Discounted CF valuation models require an estimate of the firm’s expected rate of return. Beta can be used to estimate that return –Management in making capital budgeting decisions needs to know the firm’s cost of capital.

17. Equity Risk: Measurement and Prediction Empirical Studies –Ball & Brown (1968) found a high degree of association between the accounting beta and market beta –Lev (1973) the lower the variable cost, the higher the total variance of returns and the higher the beta –Beaver et al (1970)  dividend payout, financial leverage, earnings variability, and accounting beta have significant correlations with β e

18. Equity Risk: Measurement and Prediction Fama & French (1992): –Problems for the CAPM (and β): Alternative measures of “risk” tend to be (more) closely related to returns Returns are not related to β