Chapter 5 Risk Analysis

Financial Statement Analysis of Risk Types of Risk: Financial flexibility Short-term liquidity risk Long-term solvency risk Credit risk Bankruptcy risk Market equity risk Financial reporting manipulation risk Chapter: 05

Framework for Financial Statement Analysis of Risk Chapter: 05

Analyzing Financial Flexibility Financial leverage can enhance the return to common shareholders. Disaggregation of ROCE provides insight about the degree of benefit derived from using leverage. Higher leverage generally suggests greater financial risk. Risk is primarily attributable to the costs of borrowings. Chapter: 05

Analyzing Financial Flexibility (Contd.) An alternative disaggregation of ROCE from the one discussed in the previous chapter is: Chapter: 05

Analyzing Short-Term Liquidity Risk Measures a firm’s ability to generate sufficient cash to supply operating working capital needs and to service debts. Short-term liquidity problems can arise from the following: Untimed cash inflows and outflows. High Degree of long-term leverage. Chapter: 05

Short-Term Liquidity Risk (Contd.) Financial statement ratios: Current ratio: It indicates the amount of cash available and other current assets of the firm, relative to obligations coming due. Quick ratio: Also called as Acid Test Ratio. Includes in only those current assets the firm could convert quickly into the cash (Cash, Marketable securities and Receivables). Chapter: 05

Short-Term Liquidity Risk (Contd.) Operating cash flow to current liabilities: It indicates the amount of cash from operations after funding working capital needs. Working capital activity ratios: Rate of activity measures used to study cash-generating ability of operations and short-term liquidity risk of a firm are: Accounts Receivable Turnover Inventory Turnover Accounts Payable Turnover Chapter: 05

Short-Term Liquidity Risk (Contd.) Revenues to cash ratio: Reflects the net effect of operating, investing, and financing activities on cash and management’s judgments about the desired level of cash. Lenders prefer a smaller revenue to cash ratio and large number of days revenue available as cash on hand. Days revenue held in cash: It measures the number of days sales the firm has on hand as available cash. It will be useful for forecasting financial statements. Chapter: 05

Analyzing Long-Term Solvency Risk Examines a firm’s ability to make interest and principal payments on long-term debt and similar obligations. Three measures used to examining long-term solvency risk are: Debt ratios Interest coverage ratio Operating cash flow to total liabilities ratio Chapter: 05

Long-Term Solvency Risk (contd.) Debt Ratios: It is used to measure the amount of liabilities, particularly long-term debt in a firm’s capital structure. The higher this proportion, the greater the long-term solvency risk. It is the alternative computation of leveraged used in the ROCE, in previous chapter. Chapter: 05

Long-Term Solvency Risk (contd.) Commonly used measures of Debt Ratios: Chapter: 05

Long-Term Liquidity Risk (Contd.) Interest coverage ratio: It indicates the number of times a firm’s income or cash flows could cover interest charges. Operating cash flow to total liabilities ratio: Considers the firms ability to generate cash flow from operations to service debt. Chapter: 05

Analyzing Credit Risk Potential lenders to a firm, assess the likelihood that the firm will pay periodic interest and repay the principal amount. Lenders may use following checklist as factors. Circumstances leading to need for loan. Credit History Has a firm borrowed in past and has it successfully repaid it? Poor credit history can doom a firm to failure. Chapter: 05

Analyzing Credit Risk (contd.) Cash flows Lenders prefer that the firm generates sufficient cash flows to pay interest and repay principal on a loan rather than selling the collateral. Collateral Capacity for debt Contingencies Character of Management Communication Conditions or covenants Chapter: 05

Analyzing Bankruptcy Risk Models for bankruptcy prediction Univariate bankruptcy prediction models: Error types Examines the relation between a particular financial statement ratio and bankruptcy. Chapter: 05

Analyzing Bankruptcy Risk (Contd.) Bankruptcy prediction models using multiple discriminant analysis (MDA): Altman’s Z-score Z less than 1.81 indicates high probability of bankruptcy. Z greater than 3.00 indicates low probability of bankruptcy. Scores between 1.81 and 3.00 are in the gray area. Bankruptcy prediction models using Logit Analysis: Chapter: 05

Bankruptcy Prediction Research It summarizes the factors for bankruptcy most consistently across various studies. Investment Factors: Relative Liquidity of a firm’s Assets Rate of Asset Turnover Chapter: 05

Bankruptcy Prediction Research (Contd.) Financing Factors: Relative Proportion of Debt Relative Proportion of Short-term Debt Operating Factors: Relative level of profitability Variability of operations Other possible explanatory variables: Size Growth Qualified Audit Opinion Chapter: 05

Market Equity Beta Risk Beta coefficient measures the covariability of a firm’s return with the returns of a diversified portfolio of all shares traded on the market. Beta is a measure of the Systematic risk of the firm. Chapter: 05

Market Equity Beta Risk (Contd.) Studies of the determinants have identified three principal explanatory variables: Degree of operating leverage Degree of financial leverage Variability of sales Chapter: 05

Financial reporting manipulation risk Earnings manipulation- Refers to reporting amounts outside the limits of U.S. GAAP or IFRS, i.e. fraudulent reporting. Focus on more flagrant violations of accounting standards and oversight bodies such as FASB, IASB, and SEC. Chapter: 05

Financial reporting manipulation risk Motivations for financial statement manipulation: Influence stock prices positively. Increase management bonuses. Lower cost debt financing. Avoid violation of debt covenants (or technical default). Influence corporate control transactions. Avoid regulatory or political consequences. Chapter: 05

Empirical Research on Earnings Manipulation Beneish developed a probit model to identify the financial characteristics of firms likely to engage in earnings manipulation. Beneish developed both a twelve-factor model36 and an eight-factor model. The twelve-factor model relies on a combination of financial statement items and changes in stock prices for a firm’s shares. The eight-factor model uses only financial statement items. Chapter: 05