1 / 11

Financial Statement Analysis Spring 2008

Overview of Financial Ratio Analysis. Valuation and financial ratiosFinancial analysis: Macy's vs. Wal-MartProduct differentiation vs. cost leadershipEliminate non-recurring itemsApply DuPont ratio analysis to disaggregate ROE, RNOA, Operating profit margin, Net operating asset turnover.DuPont analysis provides answers to the key question: What drives differences in ROE over time and across firms?Analyzing footnote assumptions: the case of General Motors Post-employment benefits footnot33969

brygid
Download Presentation

Financial Statement Analysis Spring 2008

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


    1. Financial Statement Analysis Spring 2008 Financial Ratio Analysis Chapter 5 (Also See Test Your Understanding Exercises, Study Questions, and Cases 6 & 7)

    2. Overview of Financial Ratio Analysis Valuation and financial ratios Financial analysis: Macy’s vs. Wal-Mart Product differentiation vs. cost leadership Eliminate non-recurring items Apply DuPont ratio analysis to disaggregate ROE, RNOA, Operating profit margin, Net operating asset turnover. DuPont analysis provides answers to the key question: What drives differences in ROE over time and across firms? Analyzing footnote assumptions: the case of General Motors Post-employment benefits footnote. Predicting default: Delta versus Southwest Airlines

    3. Valuation and Financial Ratios Basic earnings-based valuation model: Pe = CE0 + PV(RI) where Pe is the market value of the common stock, CE0 is the current book value of the common stock, PV(RI) is the discounted present value of all future years’ residual income, and RIt = NIt – re*CEt-1 = (ROEt – re)*CEt-1 So, the equity cost of capital, projected ROE and projected common equity are the key value drivers. Projected common equity depends on projected sales growth, financial leverage and net operating asset turnover. Projected ROE depends on projected profit margins, turnover, leverage and net borrowing costs. ROEt = RNOAt + FLEVt-1*SPREADt RNOAt = (NOIt / SALESt) * (SALESt / NOAt-1) FLEVt-1 = NFOt-1 / CEt-1 SPREADt = RNOAt – NBCt NBCt = NFEt / NFOt Projected sales growth, turnover and profit margin are the key drivers of projected residual income (RI).

    4. Valuation and Financial Ratios (continued) RNOAt = (NOIt / SALESt) * (SALESt / NOAt-1) i.e., RNOA = net operating profit margin times net operating asset turnover Net operating profit margin is further disaggregated into gross margin and other income components as percentages of sales. Net operating asset turnover is further disaggregated into receivables turnover, inventory turnover, PP&E turnover and the inverse of other components of net operating assets as percentages of sales or cost of sales

    5. Financial Ratio Analysis Wal-Mart vs. Macy’s Wal-Mart’s cost leadership strategy outperforms Macy’s product differentiation strategy Drill down from ROE to RNOA to Operating Margin and Net operating asset turnover to Gross Margin to Days in receivables, inventory and payables

    6. Financial Ratio Analysis Wal-Mart vs. Macy’s (continued)

    7. Financial Ratio Analysis Wal-Mart vs. Macy’s (continued)

    8. Post-employment Benefits: The Case of General Motors As shown in case 6, GM’s 2004 balance sheet recorded a net asset for its post-employment benefit plans when the funded status of the plans indicated a $70 billion liability. Pursuant to application of FAS 158, GM’s 2007 balance sheet reflects a $40 billion net liability, equal to the funded status of the plans. The discount rates used to compute plan obligations increased by nearly 100 basis points from 2004 to 2007.

    9. Predicting Default Southwest versus Delta Airlines Let’s pull up Delta Airlines and Southwest Airlines from eVal’s “core data” “data center” worksheet. With reference to the graphs on page 113 of the textbook (and related text explanation), describe how eVal predicts the default risk for these two companies. As noted at the top of page 112, the average odds of default during the ensuing five years is only about 5%. Unfortunately, with hindsight, firms that do actually default during the next five years generally do not attract default estimates much greater than this 5% (i.e., 10% would be considered very large). Thus, predicting which firms will and which will not default is no easy task.

    10. Predicting Default Southwest versus Delta Airlines (continued) Delta Airlines filed for Chapter 11 bankruptcy protection in September, 2005. As of the end of 2004 fiscal year, eVal calculated a probability of default of only 6.7%. Southwest Airlines is a very healthy regional airline. As of the end of 2004, eVal calculated a probability of default of 3.3%. Thus, the default prediction model predicted twice the probability of default for now bankrupt Delta Airlines. However, the odds were only 6.7% that Delta Airlines would default, so you wouldn’t have wanted to bet a lot of money on that outcome which, with 20-20 hindsight now seems obvious.

    12. Predicting Default Southwest versus Delta Airlines (continued) From the above table, DAL’s ratios look much worse than LUV’s, and they double the probability of default score, but still get it only up to 6.7%. For example, DAL’s liabilities exceed its total assets (i.e., negative common equity), while LUV has a more palatable liability to total asset ratio of about 0.5. However, this only increases the probability of default (on this factor alone) from 3.5% for LUV to 10% for DAL. Bottom line: predicting default from historical default experience is a highly uncertain process.

More Related