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    THE “BIG THREE” OF THE AUTO INDUSTRY:

    ANALYZING AND PREDICTING PERFORMANCE

    Robert M. Hull, Professor of Finance

    Washburn University School of Business

    1010 SW College Avenue

    Topeka, Kansas 66621

    Phone: 785-670-1600

    Email: rob.hull@washburn.edu

    Nicholas Avey, MBA Student

    Washburn University School of Business

    1010 SW College Avenue

    Topeka, Kansas 66621

    Phone: 785-312-9094

    Email: nicholas.avey@washburn.edu

    ABSTRACT

    This paper analyzes the financial performance of three leading automobile manufacturers

    (referred to as the “Big Three”). The analysis incorporates the use of (1) traditional and newer

    financial ratio methods and (2) prominent finance websites. The end result of the analysis is to

    assess the future profitability of the “Big Three. From a pedagogical standpoint, the paper offers instructors a skill that will enable them to impart knowledge of an analytical technique for

    evaluating firm performance. This technique can be used by business students and practitioners

    alike. As a byproduct, this paper includes a class exercise that goes beyond just the “X’s and O’s” of financial ratio analysis by requiring students to integrate their financial ratio findings

    with online sources offering economic and industrial analysis and analysts’ predictions.

    I. INTRODUCTION

     This paper analyzes firm performance by using information found in (1) traditional and

    newer methods of financial ratio analysis and (2) major finance websites. Firms analyzed are the

    “Big Three” of the auto industry. These three firms are Ford Motor Company (Ford), General

    Motors Corporation (GM), and DaimlerChrysler Corporation (DC).

     A major focus of the analysis of firm performance involves financial ratio analysis. This

    focus is justified because investors make decisions based on what financial ratios indicate. All

    parties concerned with investment decisions need to know how financial statement data can be

    used to evaluate firm performance. A key tool used in this paper’s financial ratio analysis is the

    DuPont Model. By using this model, analysts can focus on how three areas of management

    (profit margin, asset turnover and leverage) impact a firm’s return on equity separately and interactively. A healthy rate of return is what an investor desires. Even from a book standpoint, if

    returns are not healthy for long periods of time, then an investor’s asset is underperforming.

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     Within the paper is a pedagogical application designed to provide business students with a

    professional tool useful in evaluating firm performance. The significance of the application

    relates to this statement from the National Board for Professional Teaching Standards (1998):

    “Content pedagogy refers to the pedagogical (teaching) skills teachers use to impart

    the specialized knowledge/content of their subject area(s). Effective teachers display

    a wide range of skills and abilities that lead to creating a learning environment where

    all students feel comfortable and are sure that they can succeed both academically

    and personally. This complex combination of skills and abilities is integrated in the

    professional teaching standards that also include essential knowledge, dispositions,

    and commitments that allow educators to practice at a high level.”

    This paper’s application provides a skill that teachers can use to impart knowledge in the context of analyzing a firm’s performance through economic, industrial and financial ratio analyses and

    the use of finance websites. A consequence is that educators can practice their profession at a

    higher level consistent with excellence in university teaching (Johnson, 1991; McKeachie, 1994).

     Teaching outcomes from the application include: (1) students will delve deeper into

    financial ratio analysis by examining and comparing accounting variables drawn from financial

    statements; (2) students will apply the DuPont Model and other valuation metrics in conjunction

    with economic and industrial indicators to assess future investment possibilities; and, (3)

    students will become familiar with prominent finance websites including those that feature

    analysts’ predictions.

     The remainder of this paper is organized as follows. Section II provides an analysis of the

    economic and industrial factors influencing investment in the auto industry. Section III presents

    financial ratio methodologies used to analyze financial data. In particular, this section will

    illustrate how the return on equity is impacted through changes in variables encompassing

    margin management, asset management and debt management. Section IV offers a class exercise

    with questions and solutions. Section V gives summary statements.

    II. ANALYSIS OF THE ECONOMY AND INDUSTRY

     Leading economic indicators help investors forecast the economic outlook. Two leading

    indicators to assess the growth and vitality of the economy are the Consumer Confidence Index

    (CCI) and Gross Domestic Product (GDP). The auto industry is one of the last industries to

    follow the growth of the economy as consumers wait until their incomes have increased from the

    growth. Two leading indicators used to analyze the automotive industry are the Durable Orders

    Index (DOI) and Automotive Sales Index (ASI). Results (as of early April 2006) for the four

    above leading indicators are given below.

     The CCI tends to go up when earnings rise and borrowing rates fall. The CCI peaked during

    August 2005 and then fell about 20 percent before rebounding and reaching a near four-year high

    during March 2006 (http://www.conference-board.org/economics/consumerConfidence.cfm).

    Consumer confidence in the economy’s prospects is tempered by expectations that consumers

    may spend less if gas prices and interest rates continue to rise. Conclusion from CCI: the outlook

    appears above average given the near four-year high in CCI.

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    The GDP is a barometer of economic growth. It has averaged 3.5%4.0% the last two years prior to falling to 1.7% for the last quarter of 2005. The decline in real GDP reflected a fall in

    personal consumption spending, an increase in imports, a downturn in federal government

    expenditures, and a drop in equipment and software as well as in residential fixed investment

    (http://www.bea.gov/bea/newsrel/gdpnewsrelease.htm). Conclusion from GDP: outlook appears

    below average given the recent dip in GDP.

     The DOI reflects the new orders of durable goods placed with domestic manufacturers for

    immediate and future delivery of factory hard goods. The automotive industry contributes over

    30% to the DOI if defense spending is excluded. Orders for durable goods have strengthened as

    of February 2006 (http://money.cnn.com/2006/03/24/news/economy/durables/index.htm). The

    outlook for 2006 is good given strong expectations about durable goods orders and corporate

    profits. Conclusion from DOI: outlook appears above average given recent increase in DOI.

     The ASI is the primary indicator for the auto industry and has shown a bouncy trend the last

    two years (http://www.dailyfx.com/calendar/briefing/auto.html ). High gasoline prices make fuel

    efficient imports and domestic autos better buys. Reduced discounting is helping 2006 sales.

    Improved employment and strong income growth argue for a positive pace for the future auto

    sales especially for firms offering fuel efficient cars. Conclusion from ASI: outlook appears

    above average.

     Except for the recent dip in GDP (which may not be sustained), the conclusion from looking

    at some leading economic and industrial indicators is that there is an above average outlook for

    the auto industry. Thus, investors can be cautiously optimistic about future investment

    possibilities in the auto industry. To decide which particular automotive firms to invest in, one

    needs to make firm specific analyses. For example, consider the Big Three” that compete on a

    global scale with firms that often have lower labor costs, produce more fuel efficient vehicles,

    and obtain lower borrowing costs. While making inroads in reducing labor costs (through recent

    labor cutbacks) and creating more fuel efficient products, the borrowing costs for “Big Three”

    firms are expected to remain high, especially for Ford and GM given the speculative status of

    their bonds. Thus, an optimistic outlook does not necessarily translate into favorable earnings for

    firms that experience greater borrowing costs.

    III. FINANCIAL RATIO ANALYSIS

     Financial ratio analysis consists of various methodologies including (1) long-standing

    traditional methods as epitomized by the DuPont Model and (2) relatively more recent valuation

    methods as represented by economic value added (EVA), return on invested capital (ROI) and

    free cash flow (FCF). These methodologies are discussed below.

Background on Financial Ratio Methodologies

     Traditional financial ratio analysis can be traced to the origins of the DuPont system of

    financial analysis (referred to as the DuPont Model). The DuPont Model was developed in 1919

    by F. Donaldson Brown. Brown was an engineer who entered the treasury department of E.I. du

    Pont de Nemours and Co. in 1914. After DuPont acquired about one quarter of GM, Brown was

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    appointed to cleanup GMs unruly finances. Blumenthal (1998) writes that much of the credit for

    GM's ascension afterward belongs to Brown's systems of planning and control. Such success launched the DuPont Model to widespread use by managers of major U.S. corporations. Even today it remains a dominant form of financial analysis used by consultants and financial executives.

     The DuPont Model remains today a highly preferred system of financial analysis having withstood the challenge of newer valuation methods introduced in the 1990s. Blumenthal (1998) presents both sides of the debate involving traditional financial ratio analysis (namely, the DuPont Model) on one side and newer methods (namely, EVA) on the other side. Blumenthal cites academic and practitioner sources who contend that the DuPont Model still enjoys much success in turning around firms while heightening the focus on accountabilities for different parts of the business. Although newer methods like EVA have been actively promoted to analyze shareholders’ wealth, Firer (1999) indicates that traditional approaches typified by the DuPont

    Model will continue to dominate financial analysis for some time.

     The important role of financial ratio analysis is routinely discussed in finance and accounting texts. Financial ratios are derived from financial statements, in particular, the balance sheet and income statement. These ratios are frequently examined for their power to predict security valuation (Penman, 2004). However, despite their heavy use, one should be aware of their limitations. For example, data for financial ratios are a product of the accounting processes and reflect historical costs disregarding past inflation and future prospects. Also, financial ratios must be compared to some standard or norm to be fully meaningful and it can be difficulty to find norms for all firms. For leading firms, using norms represented by industry averages may not be applicable. In addition, “window dressing” can occur so as to make ratios look good in the

    short run, while international operations can present problems as a different set of accounting regulations may apply.

     Financial ratios must be interpreted properly and cautiously not only because of the above limitations, but because they are also subject to unethical manipulation leading to outright inaccuracies. While these problems are hard to cover up in the long run, they nonetheless can deceive even the most skilled analyst in the short run.

A Description of the DuPont Model

     The focus of the DuPont Model is the return on equity (ROE) where ROE is net profit divided by stockholders’ equity. Net income is commonly used to proxy for net profit. The focus

    on ROE is justified because the return on equity is arguably the preeminent measure of the wealth supplied by a firm to its shareholders. As a system of financial ratio analysis, the DuPont Model ties together income statement and balance sheet items showing how ROE is affected by margin management (Net Profit Margin), asset management (Asset Turnover), and debt management (Financial Leverage or Equity Multiplier). Margin management uses financial ratios derived from the income statement, while asset management utilizes ratios from the balance sheet. Debt management is an area determined by managerial choices about the forms of financing. As can be seen in Exhibit 1, the DuPont Model brings together these three areas of management. (See Ockree and Hull (2006) for other exhibits for the expanded DuPont Model.)

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    Exhibits 2?4 apply the DuPont system of financial analysis to each of the “Big Three” firms.

    The key ratios found in the DuPont exhibits are described below.

    Margin Management (Data from Income Statement):

    Net Profit Margin (NPM) = Net Profit / Sales = NP / S (1)

    Asset Management (Data from Balance Sheet):

    Asset Turnover (AT) = Sales / Total Assets = S / TA (2)

    Debt Management (Data from Balance Sheet):

    Financial Leverage (FL) = Total Assets / Common Equity = TA / CE (3)

    Multiplying out the above three equations and canceling out from the denominators and

    numerators for “S” and “TA” gives:

    ROE = NPM × AT × FL = (NP / S) × (S / TA) × (TA / CE) ? ROE = (NP / CE). (4)

     One can observe from equations (1) through (4) that the DuPont Model allows one to focus

    on the separate (but interlinked) ideas of profitability (NPM), asset utilization (AT), and leverage

    (FL). One can also see how ROE is a function of ROA and FL since ROA = NPM × AT.

    Because FL > 1 always holds, a positive ROA value is magnified when computing ROE.

    Similarly, a negative ROA value leads to an ROE value that is more negative than ROA. A

    negative ROA really becomes problematic when a firm has a large FL value.

     There can be flexibility in defining the variables used in the DuPont Model. For example,

    besides net income, other earning variables could be used in the numerator when defining NPM.

    Similarly, other asset variables besides total assets could be used when defining AT. Firer (1999)

    describes various ratios that can be used when computing ROE using the DuPont Model. Tezel

    and McManus (2003) point out definitional problems when properly accounting for ROE.

Valuation Metrics

     Valuation metrics, like EVA, won support among a contingent of supporters in corporate

    circles during the 1990s. The support stems from the capacity to correlate favorable firm

    performance with decisions that produce returns exceeding the cost of capital. Doing this implies

    value creation. It also shifts costs such as research and development from the expense category to

    capital investment. Critics argue that metrics aimed at creating value involve too much subjective

    guess work requiring numerous calculations and adjustments that can more easily lead to

    distortion of numbers reported to the public. This type of reporting has been a major ethical

    problem in recent years leading to investor mistrust with company financial reports.

     Exhibit 5 supplies valuation metrics for each of the “Big Three” firms. These metrics add to

    the DuPont results found in Exhibits 24. The relevant variables, used in the metrics deployed in

    Exhibit 5, are defined below (with precise definitions sometimes differing among sources).

     NOWC (Net Operating Working Capital) is Cash & Equivalents + Accounts Receivables +

    Inventories Accounts Payables Accrued Expenses.

     OLTA (Operating Long Term Assets) is Net Property, Plant & Equipment.

     TOC (Total Operating Capital or Invested Capital) is NOWC + OLTA.

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     NOPAT (Net Operating Profit after Tax) is Operating Income × (1?T) where Operating Income is EBIT and T is the corporate tax rate.

     ROIC (Return on Invested Capital) is NOPAT divided by the prior year’s TOC.

     EVA (Economic Value Added) is NOPAT minus the quantity consisting of the weighted

    average cost of capital times the prior years TOC.

     FCF (Free Cash Flow) is NOPAT minus the quantity consisting of this year’s TOC minus

    the prior year’s TOC.

Inspecting Analysts’ Assessment

     Internet sites that provide details to inspect analysts’ assessment are abundant enough and can be used in conjunction with financial ratio analysis to make predictions about investment

    possibilities. More details on this are given in the class exercise in the next section.

    IV. CLASS EXERCISE

     In this section, the information presented in the prior two sections will be incorporated into a

    class exercise that will also include analysts’ assessment. This is accomplished in the form of

    five questions. Possible solutions are given after each question. In regards to Questions 2?4,

    students are provided beforehand with the DuPont Model flow chart given in Exhibit 1. If

    requested, the authors can (i) furnish instructors with Excel spreadsheets containing data that

    computes results in Exhibits 2?5, and (ii) supply details on other financial ratios not given in the

    exhibits. The exercise can be done individually by assigning one of the three firms for each

    student. Instructors can also expand the exercise by assigning students to analyze other

    automobile firms such as Toyota or Honda. The exercise can also be done in teams of students.

    (See Hull, Roach and Weigand (2006) for some particulars when conducting a team exercise.)

SUGGESTED STUDENT QUESTIONS AND SOLUTIONS FOR PEDAGOGICAL APPLICATION

QUESTION 1. Type in key search words (such as Leading Indicators, Consumer Confidence,

    Gross Domestic Products, Durable Goods Orders, Auto Sales Index, and so forth) to explore the

    internet for information on the economy and the auto industry. One website that can be found is

    http://www.briefing.com. Click on the free “Investor Index” link and then the “Economic Calendar” link to find dates and forecasts of upcoming economic releases related to consumer confidence, gross domestic products, durable goods orders, and auto sales. After becoming

    accustomed with Internet resource materials, perform an economic and industrial analysis to help

    gain insight on the investment opportunities in the automobile industry. In this analysis, include

    predictions for the auto industry in general. Try to explore if your predictions apply to “Big Three firms.

SOLUTION 1. Student answers will change over time as economic and industry conditions change.

    As of April 2006, the outlook appears to be good but the outlook can also be a function of the

    sources used. A good outlook for an industry does not necessarily hold for those companies with

    firm-specific problems. For additional details as of April 2006, see Section II on the “Analysis of the Economy and Industry.

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    QUESTION 2. Using the DuPont Model flow chart provided, perform a DuPont ratio analysis of

    the Ford Motor Company using financial statement data from one of the many online sources

    that exist. For example, go to http://moneycentral.msn.com/home.asp, http://finance.yahoo.com,

    or http://www.hoovers.com/free and type in the ticker symbol (F, GM, or DCX). If the Money

    Central website is chosen, begin by typing in “F” by “Symbols in the top right hand and then hit the enter key; scroll down and click on “Financial Results” in far left column. The heading “Statements” will pop up three lines under “Financial Results”; after clicking on “Statements”,

    then click by “Financial Statements” in the middle of the page to access either the Income

    Statement or Balance Sheet data for Ford. This data is needed to perform computations for the

    variables given in the DuPont Model flow chart (and later for valuation metrics). Money Central

    will give financial data for five years and that should be long enough to find a trend

    representative of Ford’s ROE. Using the numbers in the DuPont flow chart explain any changes

    in ROE over time in terms of margin management, asset management, and debt management.

SOLUTION 2. See Exhibit 2 for numbers and conclusions based on financial data for Ford Motor

    Company from 2001?2005. Instructors can note that the lower part of Exhibit 2 supplies trend

    information on ROE for the five years from 20012005 and also gives conclusions on the roles of margin management, asset management, and debt management in explaining Ford’s change in

    ROE from 2001 to 2005; similarly, for Exhibit 3 and 4 for Questions 3 and 4 for GM and DC.

QUESTION 3. Repeat Question 2 using General Motors Corporation (“GM” is now the ticker

    symbol used in following the steps given above when using the Money Central website).

SOLUTION 3. See Exhibit 3 for numbers and conclusions based on financial data for General

    Motors Corporation from 2001?2005.

QUESTION 4. Repeat Question 2 using DaimlerChrysler Corporation (“DCX” is now the ticker

    symbol used in the steps given above when using the Money Central website).

SOLUTION 4. See Exhibit 4 for numbers and conclusions based on financial data for Daimler-

    Chrysler Corporation from 2001?2005.

    QUESTION 5. Analyze the trends in ROE for the “Big Three” auto companies using the answers in the three previous questions. Using the same data gathered to generate the DuPont analysis,

    compute trends over time focusing on the following valuation metrics: Return on Invested

    Capital, Economic Value Added and Free Cash Flow. Use T = 20% for all three firms; use WACC

    = 13% for Ford, WACC = 14% for GM and WACC = 10% for DC. What do these metrics

    suggest? Do they support the DuPont findings? Do further internet research to find out what

    analysts are predicting. To illustrate using the Money Central website, type in the ticker symbol

    and then choose such categories as “Stock Rating,” “Earnings Estimates,” “Analyst Ratings” and

    “Insider Trading” to get information. Given all of your previous answers, what are your

    predictions for an investment in the “Big Three”?

    SOLUTION 5. From the DuPont analysis found in Exhibits 24, one finds that the ROE for Ford shows a general positive five-year trend from 2001?2005. However, one also finds high variability in ROE from year to year making it more difficult to label the trend as positive. The

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    ROE trend for GM is discouraging as one can see that it has been downward from 2002 through

    2005. The ROE trend for DC has been steady but low and (like that for GM) it has been

    downward for more recent years. Overall, the DuPont analysis suggests that Ford has the most

    favorable ROE trend. As seen in Exhibit 5, the trend analysis for valuation metrics gives some

    mixed results. In this exhibit, one can find a number of categories that suggests a ranking of “Big

    Three” firms similar to the DuPont analysis. As of April 2006, analysts differ as to which of the

    three firms offers the best investment potential. StockScouter ranks Ford and DM as dead even,

    while Yahoo ranks Ford slightly better than GM with DM last. Somewhat disturbing, one can

    find that analysts often change their minds reversing their rankings weekly. From August 2005 to

    April 2006, it appears that analysts have most often given Ford the highest ranking. (See Exhibit

    5 for more details and possible answers, in regards to valuation metrics and analysts’ predictions,

    based on information provided by Money Central.) Overall, the outlook for the “Big Three” is

    not great and one would tend to predict below average investment results.

    V. SUMMARY STATEMENTS

     This paper has presented an approach to analyze financial performance. The approach has

    been incorporated within a class exercise so that instructors can impart an analytic skill.

    Summary results of the financial analysis for the “Big Three” are given below.

     First, the economic and industrial outlook indicates the auto industry should provide

    investors with sound returns in the future. Second, the DuPont analyses suggest that the best

    ROE trend belongs to Ford, but that DC has less variability. However, trends are not impressive

    and average ROE values are poor for all “Big Three” firms suggesting that it might be better if

    they were called the “Little Three” (at least in terms of market expectations). Third, metric analyses confirm findings of the DuPont analyses by indicating that the performance for Ford

    generally appears superior but DC often has less variability making it less risky from an

    investor’s standpoint. Fourth, while precise forecasts can be a matter of opinion and what aspects

    are being emphasized, analysts currently do not expect “Big Three” firms to be good investments

    (even though the industry outlook is good for its competitors such as Toyota and Honda). If

    expectations for the “Big Three” are poorer, then market efficiency suggests that its stock prices should already reflect this. Thus, if one wants to be more adventuresome (and take on more risk),

    the “Big Three” may yield a chance for greater returns if and when it can overcome its current

    problems in terms of higher costs and more fuel guzzling vehicles.

    Mountain Plains Journal of Business and Economics, Pedagogy, Volume 8, 2007

    _____________________________________________________________________________________ 9 EXHIBIT 1: ROE Flow Chart to Be Used for the DuPont Analysis

    ROE Flow Chart for Expanded DuPont Analysis

    [NOTE. For each box of the firm being evaluation put in its financial statement numbers for beginning

    year in the lower half of the box and for the ending year in the upper half of the box.]

    Sales

    Comparison Key: Gross Profit

    minus

    Net Profit

    Cost of Goods SoldminusNet Profit Other CostsMargin

    divided by

     Sales

    Net Profit12Financial 10.Return on Return on SalesLeverage95AssetsEquity

    multiplied byCashSales=X0

    Asset TurnoverTotal AssetsplusNet ProfitNet ProfitCurrent AssetsEquityTotal AssetsEquityInventorydivided by

    SalesTotal AssetsmmplusplusTotal AssetsAccounts ReceivableFixed Assets

    plus

    Other Current Assets

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    EXHIBIT 2: ROE Flow Chart for Ford Motors Company

    Expanded DuPont Analysis for Ford Motors from 2001 to 2005 (values in billions)

    Sales

    1772005Comparison Key:162 2001Gross Profit

    minus32.2Net Profit 17.0Cost of Goods Sold0.4minusNet Profit 144-5.3Other Costs145Margin

    31.80.23%divided by22.3-3.29Sales

    Net Profit17712Financial 10.Return on Return on Sales162Leverage95AssetsEquity

    multiplied by0.15%3.16%20.8CashSalesX0=3135.5-68.6%-1.93%1777162Asset TurnoverplusNet ProfitNet ProfitTotal AssetsCurrent Assets=Total AssetsEquityEquity0.66Inventory200divided by0.5910366SalesTotal AssetsplusplusTotal AssetsAccounts Receivable269Fixed Assets114277TREND369(ROE relative toplus240YEARROEprior year)

    20053.16%?Other Current Assets200415.74%?442020031.11%?

    20028.39%?

    2001-68.62%?

    200011.65%?

    199921.23%-

    Conclusion for Ford Motors from DuPont Analysis

    The change in sign for Return on Equity (ROE) from a negative percentage in 2001 to a positive percentage in

    2005 is caused by a change in sign for Net Profit. While sales went up from 2001 to 2005, costs did not

    increase as much. The end result was that the Net Profit Margin (NPM) went from being negative to being

    slightly positive. Besides improving its margin management, Ford also improved its asset management (from

    2001 to 2005) as its Asset Turnover increased from 0.59 to 0.66. The large value for financial leverage (FL) in

    2001 caused the negative Return on Assets (ROA) to be magnified. The firm needs to continue to improve its

    margin management through increasing its sales relative to its costs. While the effect from debt management is

    positive for 2005 due to multiplying a very large FL value by a positive ROA, this creates a highly risky

    situation since a negative NPM can cause a severely negative ROE (as occurred in 2001).

    Mountain Plains Journal of Business and Economics, Pedagogy, Volume 8, 2007

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