Guerrilla Approaches to Finding and Evaluating Stocks

Transcription

1 Guerrilla Approaches to Finding and Evaluating Stocks Marc H. Gerstein Portfolio123.com AAII/Better Investing, Washington DC 4/18/2015 1

2 Marc H. Gerstein spent his career analyzing stocks, educating investors, and helping to develop stock screening platforms at Value Line and various web sites. He is presently Director of Research at Portfolio123 and Editor of Forbes Low-Priced Stock Report. His commentary can be found on SeekingAlpha.com, Forbes.com and Harvest (hvst.com). He has authored three books, Screening the Market(Wiley, 2002), The Value Connection(Wiley 2003), Atlas Upgrades: Objectivism 2.0 (Create Space, 2013). He is presently working on a novel with a Wall Street setting, and a book with Stanford s Dr. Charles Lee based on the latter s course in Alphanomics. 2

3 The Agenda Recalibrating the Investment Mindset Case Studies: Developing Strategies Easy-to-Use Excel Valuation Tools Organizing and Summarizing your analysis of a stock consistent with the approach to be discussed today Measuring the relative roles of Noise and Value in a stock price A very simple, practical, usable discounted cash flow type model based on Residual Income 3

4 Recalibrating the Investment Mindset 4

5 The Starting Point Own great companies whose shares can be purchased at great (cheap!) prices Own companies with sustainable competitive advantages Own companies with wide economic moats Own companies with great management teams Don t chase a lot of stocks but be patient and wait to swing at a fat pitch Research the daylights out of prospective investments and put the lion s share of your money into just a few best ideas Etc., etc., etc. 5

6 Oops 6

7 It Sounds Wonderful On Paper, But in the Real World... 7

8 The Problems... Traditional guru advice is so sound and so well disseminated, that today everybody and anybody is a Buffett wannabe, a Graham follower, a Magic Formula devotee, etc. Really, truly, genuinely great companies are scarce and their shares tend to get popular and, hence, expensive 8

9 Act Like an Investor, Not a Foodie Judge If there s a teeny-bit too much seasoning, live with it! 9

10 My Investment Hero: Monroe Milstein (Founder of Burlington Coat Factory) 10

11 The Bloodletting The Milstein Moment On a circa 1990s conference call, Wall Street analyst were taking the Burlington Coat Factory CFO to task, and rather harshly, for disappointing sales numbers The CFO was having trouble articulating a reason that was considered satisfactory by the analysts The Rescue CEO Monroe Milstein, who typically said little during these calls, broke in: Gentlemen, he said. I ve been in this business for many years. We have good months and we have bad months. This was a bad month. The outcome Prolonged silence The analysts were rendered speechless The call then proceeded to an uneventful conclusion Epilogue Milstein cashed in huge when the company was sold to Bain Capital in 2006 for $2.06 billion 11

12 Don t Rush to Judgment 12

13 Life is Harsh: Learn to Accept Corporate Warts Too many investors are devoting too many hours to quests for perfection, and finding themselves disappointed by when Subsequent events reveal that the supposedly great company was more human than they had realized, and/or The price they paid for the great-company shares turned out to be fart less of a bargain than they had originally supposed On the other hand, too few investors appreciate the opportunities available in companies that are plain-vanilla, mundane, ordinary, mediocre or downright lousy The shares can benefit as the companies improve (i.e. from horrendous up to mundane) The shares tend to be cheaper It can be great to buy a company with 25 units of Pathetic if the stock is priced as if the company had 40 units of Pathetic 13

14 Divine Revelation 14

15 On Predictions Disciple (a/k/a John Denver): God, can you predict the future? God (a/k/a George Burns): Of course I can predict the future; as soon as it becomes the past. Source: Oh God! (Warner Bros. 1977) 15

16 Human Insight -Aristotle [T]he habits of perfected Self-Mastery and Courage are spoiled by the excess and defect, but by the mean state are preserved. At all events thus much is plain, that the mean state is in all things praiseworthy, and that practically we must deflect sometimes towards excess sometimes towards defect, because this will be the easiest method of hitting on the mean, that is, on what is right. From Nicomachean Ethics, Book II (D.P. Chase Translation) 16

17 Human Insight Lao Tzu Holding a cup and overfilling it Cannot be as good as stopping short Pounding a blade and sharpening it Cannot be kept for long Gold and jade fill up the room No one is able to protect them Wealth and position bring arrogance And leave disasters upon oneself When achievement is completed, fame is attained Withdraw oneself This is the Tao of Heaven Lao Tzu, Tao TeChing, Ch. 9 (Derek Lin Translation) 17

18 Relevant Buzz Words Buzz Words for Aristotle and Lao Tzu Virtue The Mean Withholding Stopping Short Buzz Word for Us Mean Reversion Corrections Overbought and Oversold Business Cycles Economic Excesses Supply and Demand (market forces correct excesses and deficiencies in pricing and units) Company Transition (as growth companies mature) The overpowering of economic moats 18

19 19

20 The Destination Be an Investor, not a foodie judge Don t obsess over finding perfection What looks to some gurus like a fat pitch is more likely a slow-moving knuckle ball that breaks erratically and flutters frustratingly past your frantic swing Don t be judgmental Accept normal warts Recognize that extremes are not sustainable Embrace the ordinary, or worse Embrace the ordinary Invest like a human Recognize and even embrace our inability to know the future Diversify, diversify an diversify Focused portfolios (most money in a few best ideas) are nonsense. They presume too much about our ability to know the future, and if we could know the future, there d be no reason not to put 1200% of assets into one s single favorite idea Accept that it s better to be vaguely right than precisely wrong British Philosopher-Logician Carveth Read Don t fret about being wrong, just try to be less wrong than others Dr. Aswath Damodaran, NYU Stern School of Business 20

21 Case Study: Developing a Strategy 21

22 Introduction to Strategy Development All of these strategies were developed on Portfolio123 using screens and ranks If you subscribe to Portfolio123, you will be able to replicate tem and modify as you wish If you are not on Portfolio123, you can work with these ideas based on financial data you can find in Stock Investor Proand on several web sites (e.g., Morningstar, MSN Money, Yahoo! Finance) You ll see as we go along that it s not about precise formulas It s about broad ideas regarding what to look for A very important theme will emphasize the generalist idea rather than the specialist i.e., a stock that is decent in a lot of respects (and may or may not be excellent in some and/or dreadful in others); as opposed to a stock that seems excellent under a particular formulation You can apply this approach whether or not you use screeners, etc. 22

23 How We re Going to Implement Our New Mindset We re going to seek adequacy or OK, as opposed to excellence And we ll be open to inadequate, or bad, if we can get indications of improvement We re going to seek fundamental generalist situations rather than specialists Example: Prefer company A (score of 70 of better under, perhaps 8 out of 10 factors and no factor worse than 50) over company B (scores of 90+ in two factors and below 30 in all others) We re going to tolerate redundancy Data oddities are ubiquitous and unavoidable, so we ll use factor diversification to diminish the impact of oddball items, such as: the 643% EPS gain that would have been 3% but for a non-recurring gain or a sales decline of 45% that would have been seen as 12% growth but for a major divestiture We re going to embrace and celebrate stylistic diversification Even if you re a committed value investor, would it pain you to take a big profit by selling to an algorithmic day trader? So why not allow your models strategies to include ideas that might make stocks attractive to the latter? 23

24 An Idea Library We ll start by looking at some ranking systems I created and use on Portfolio123 Unlike a screen, which seeks a small number of companies that pass all of a set of yes/no filters, ranking systems assign best-to-worst scores to all companies A multifactor ranking system is one based on more than one factor, as opposed to a simple sort based on a single factor Other well-known ranking systems: Investors Business Daily (Stock Checkup), Value Line, Morningstar, Schwab, MSN, The Street.com, etc. They re all sensible. It s not about specific formulas but in how you sue the information If you want, especially if you don t use a quant platform, you can make an checklist based on these factors Don t get too precise Sample score for each item Great (5 points), or OK (4 point), or Bad (-2 point) Choose a scoring system that will Allow generalist companies to wind up with good grades Make it hard for specialists to dominate And which won t get carried away by negative unless there are too darn many of them See next slide for sample spreadsheet 24

25 The Portfolio123 Comprehensive: QVGM Ranking System Basic: Quality Ranking System (25%) Basic: Value Ranking System (25%) Basic: Growth Ranking System (25%) Basic: Momentum Ranking System (25%)

26 The Portfolio123 Basic: Quality Ranking System Margins (25%) Trailing 12 Month (TTM) Operating Margin (75% - higher is better) 5 yr. average Operating Margin (25% -higher is better) Turnover (25%) TTM Asset Turnover (100% -higher is better) Returns on Capital (25%) TTM Return on Investment (30% -higher is better) 5 yr. average Return on Investment (40% -higher is better) TTM Return on Equity (10% -higher is better) 5 yr. average Return on Equity (20% -higher is better) Finances (25%) Latest Current Ratio (30% -higher is better) TTM Interest Coverage (45% -higher is better) Latest Total Debt to Capital (25% -higher is better)

27 The Portfolio123 Basic: Value Ranking System Value Based on Income Stream (65%) Based on Earnings (50%) PE based on Trailing 12 months EPS (33.33%) PE based on consensus estimate of Current Yr. EPS (33.33%) PEG ratio with G based on estimate of long-term growth rate (33.33%) Other (50%) Price/Trailing 12 month Sales (50%) Price/Trailing 12 month Free Cash Flow (50%) Value Based on Assets (35%) Price/Book (100%)

28 The Portfolio123 Basic: Growth Ranking System EPS Growth (75%) Basic Growth (50%) YTY growth in latest quarter (higher is better 33%) Trailing 12 Month (TTM) growth (higher is better 33%) 5 year growth rate (higher is better 33%) Acceleration in Growth (50%) Latest qtr. growth compared to TTM (higher is better 50%) TTM growth compared to 5-year growth TTM (higher is better 50%) Sales Growth (25%) Basic Growth (75%) YTY growth in latest quarter (higher is better 33%) Trailing 12 Month (TTM) growth (higher is better 33%) 5 year growth rate (higher is better 33%) Acceleration in Growth (25%) Latest qtr. growth compared to TTM (higher is better 50%) TTM growth compared to 5-year growth TTM (higher is better 50%)

29 The Portfolio123 Basic: Momentum Ranking System Share Price Change (65%) Last 120 days (20% -higher is better) Last 140 days (20% -higher is better) Last 160 days (30% -higher is better) Last 180 days (30% -higher is better) Technical Indicator (35%) 20 Day Up-Down Ratio * (50% -higher is better) 60 Day Up-Down Ratio * (30% -higher is better) 120 Day Up-Down Ratio * (20% -higher is better) * Volume in up days in defined period divided by volume in down days

30 The Portfolio123 Basic: Sentiment Ranking System Estimates (50%) % 4 Week Change in Consensus Current Yr. EPS Est. (higher is better %) % 4 Week Change in Consensus Current Qtr. EPS Est. (higher is better %) Standard Deviation of Current Qtr. EPS estimates/absolute value of consensus estimate (lower is better %) EPS Surprise (30%) Surprise % most recent quarter (higher is better -65%) Surprise % second most recent quarter (lower is better -35%) Analyst Recommendations (20%) 4-week change in consensus recommendation (more bullish is better - 75%) Current consensus recommendation (more bullish is better - 25%)

31 What Works... Gerstein Style Goal: Similar to what James O Shaughnessy did in What Works on Wall Street Difference is that here, we are not looking to articulate universal truths but are instead creating strategies that can be narrowed to the point of selecting manageable (approx. 15 stocks) portfolios 31

32 Testing Value Factors 32

33 Assessing Value Value seems very promising on a multifactor basis Consistent with what we saw above regarding the importance of value But chart is erratic, suggesting we need more in order to have a truly complete strategy It s about not just value per se; it s about value thoughtfully applied 33

34 Testing Growth Factors 34

35 Assessing Growth It s not great enough to stand on its own, but there s enough here to merit consideration Pictorial presentation of multifactor growth ranking system (unimpressive suggesting a definite need for more work): 35

36 Testing Quality Factors Surprisingly lackluster considering the theoretical strength of these metrics ROE is the penultimate measure of a good company 36

37 Testing Sentiment Factors There is something to estimate revision, as theoretically weak as it seems Think about this later, when we discuss noise as distinct from value 37

38 Testing Multifactor Approaches 38

39 Top 15 per QVG Ranking System 39

40 Top 15 per QVGM Ranking System 40

41 QVG vs. QVGM Based purely on overall 10-year backtestresults, QVG looks slightly superior Not clear the difference is especially significant Consideration of the charts, however, suggests a nod to QVGM More consistent performance over longer periods of time These multifactor sorting/ranking approaches, although not perfect, do show promise The key is to do what successful sales people do; prospect from pre-qualified lists (as opposed to, say, the white pages) Screens are a great way to create pre-qualified lists 41

42 A Very Simple Screen Choose stocks from within Russell 3000 universe PE (using estimate of next year s EPS) < 15 ROE trailing 12 months > 25% EPS gain vs. year-ago quarter < 15% 42

43 Testing Performance of All Passing Stocks (usually of them) 43

44 Choose 15 Stocks at Random Decent in spots but erratic; good periods likely due to chance 44

45 Top 15 per Value Ranking System Well that s disappointing! The value ranking system seemed promising on its own. 45

46 Let s Change The Screen There s a dramatic increase in the number of factors being considered (note the addition of two rules using multi-factor ranking systems), and the carryover rules now are much less demanding in terms of excellence Choose stocks from within Russell 3000 universe Forward PE is in the bottom 65% of the universe Trailing 12 month ROE is in the top 25% EPS growth rate vs. year ago quarter in top 25% Score under Sentiment ranking system is above 80 Score under QVGM ranking system is above 80 46

47 Top 15 per Value Ranking System Now we re starting to make progress 47

48 Let s Relax the Screen Even More ROE Rule Old Company in top 25% New Company in top 50% EPS Growth Rule Old Company in top 25% New Company in top 50% 48

49 Top 15 per Value Ranking System Yes! It looks like we ve got something. But I notice way too many Finance stocks in the result set Fine for some, but not my cup of tea 49

50 Tweaking the Screen Again Add a rule eliminating companies in the Financial Sector Tweak the PE rule I still want bottom 65% But instead of bottom 65% relative to all stocks, I now want bottom 65% relative to industry peers The original rule caused the portfolio to tilt heavily toward Financial; stocks, which normally carry relatively low PEs 50

51 Top 15 per Value Ranking System This is usable! 51

52 Easy-to-Use Excel Valuation Tools 52

53 Tool 1: Stock Analysis Excel Template 53

54 The Formulas Formula for G14 =((D14*$F$3)+(E14*$F$4)+(F14*$F$5))*C14 Copy to all other cells in the same column Formula for H14 =IF(F14+E14+D14<>1,"***ERROR -Place 1 in just one, column)","") Copy to all other cells in the same column Formula for G9 =SUM(G14:G29) Its the sum of all columns for which we can have a score Formulas for: M14 =D14*C14*$F$3 N14 =E14*C14*$F$4 O14 =F14*C14*$F$5 Copy Row M14, N14 and O14 down through Row 29 M30 =SUM(M14:M29) Copy M30 to N30 and O30 D30 =M30/$G$9 Copy D30 to E30 and F30 G30 =SUM(D30:F30) D31 =IF(ABS(E30)>0.65,"Company is a generalist","company is a specialsit") 54

55 Tool 1: Noise-Value Calibrator 1. The Idea 2. The Calculations 3. The Excel Spreadsheet 55

56 Noise-Value Calibrator: The Idea 56

57 Starting Point: Beat the Gun Traditional notion Investors buy stocks they believe will deliver good returns John Maynard Keynes [T]he professional investor is forced to concern himself with the anticipation of impending changes, in the news or in the atmosphere, of the kind by which experience shows that the mass psychology of the market is most influenced.... The social object of skilled investment should be to defeat the dark forces of time and ignorance which envelop our future. The actual, private object of the most skilled investment to-day is to beat the gun, as the Americans so well express it, to outwit the crowd, and to pass the bad, or depreciating, half-crown to the other fellow. John Maynard Keynes, The General Theory of Employment, Interest and Money(Signalman Publishing, 2010 Kindle Ed.), p. 101, Emphasis supplied. 57

58 Implications of Beat The Gun We recognize that some will trade on the basis of reasons that aren t right and... That many who do so are knowledgeable investors who really ought to know what s right and what isn t, and... That what they re doing is perfectly rational It s perfectly rational to pay $50 for a stock you know is worth $40 if you expect it to go to $60 58

59 Fisher Black He not only acknowledges the existence of such noise trading but goes further to state that it s essential to the functioning of the market If all traders did only what s right, no trading could ever take place since one party would have to be willing to make a mistake. But... Noise trading provides the essential missing ingredient.... With a lot of noise traders in the market, it now pays for those with information to trade. It even pays for people to seek out costly information which they will then trade on. Fisher Black, NoisePapers and Proceedings of the Forty-Fourth Annual Meeting of the America Finance Association, New York, New York, December 20-30, 1985, Journal of Finance, Vol. 41, Issue 3 (July 1986), p at 531 ) 59

60 Implications of Black Noise trading is not only understandable, but the market can t function without it We can t hope improved investor education or an outbreak of mass rationality will eliminate noise and cause everybody to do the right thing It simply won t happen, not now, not ever 60

61 The Next Step: Robert Shiller The market consists of two types of traders Smart-money investors Make decisions based on information relevant to valuation subject only to wealth constraints Ordinary Investors Everyone else; i.e., those who do not respond to expected returns as optimally forecasted They often over-react to news and follow fads since they have no model or at best a very incomplete model of the behavior of stock prices.... Robert J. Shiller, Stock Prices and Social DynamicsBrookings Papers on Economic Activity, Vol. 2 (1984) p

62 A new theory courtesy of Shiller Note: This is a bona fide theory. We re only seeing how concepts interact. We re not supposed to try to plug in any numbers. P t = Q t + Y t Where P t = Demand for all shares in the market at time t Q t = Demand for shares by Smart Moneyat time t Y t = Demand for shares by Ordinary Investors at time t 62

63 To refine it, we ll add two kinds of discount rates ρ (rho) = the expected real return φ (phi) = the risk premium that compensates for arbitrage costs, which are influenced by Trading costs (brokerage costs, slippage, etc.) Holding costs (the cost of maintaining a position) Information costs (the cost of getting the information needed to acquire and monitor a position) This is the main item! 63

64 The Refined Theory P t = Σ (E t (D t+k ) + φe t (Y t+k )) / (1 + ρ + φ) Gag, gag, retch... RELAX This is just a theoretical framework. We re not going to try to plug in any numbers. Generally, this can be translated to English as stock prices are equal to.... The present value of all expected future dividends Nothing new here; we know all about this Plus the sum of all future ordinary-trader demand multiplied by arbitrage costs This is new 64

65 A Change in Nomenclature Courtesy of Prof. Charles M.C. Lee, Stanford Smart Money Demand = Value Trading Value Trading need not specifically be the Dividend Discount Model It simply refers to a truly rational approach to valuation, which includes sensible fundamental analysis that helps knowledgeable investors derive inputs to valuation models The key is that these investors trade with their head, not their hearts or guts Ordinary Investor Demand = Noise Trading These investor can t or don t apply rational valuation concepts They trade with their emotions or guts, not their heads So now, stocks price = value + noise Or, P = V + N 65

66 Deconstructing the Model Suppose φ, arbitrage costs, approach zero φe t (Y t+k ), the noise component, likewise approaches zero So as arbitrage costs diminish, the role of noiseoriented investors also diminishes and the role of value investors grows and approaches 100% In this case, we approach a truly efficient market, where the price of a stock is equal to what it s really worth

67 Deconstruction -Continued Suppose φ, arbitrage costs, rise and approach infinity φe t (Y t+k ), the noise component, likewise approaches rises and would eventually approach 100% So as arbitrage costs rise, value investors become increasingly drowned out by noise

68 Focusing on the Information-Cost Component of φ (Arbitrage Costs).... As information becomes harder and more expensive to get, the role of value diminishes We see this all the time In some global markets, where information is largely unavailable and/or unreliable, the markets are very much or, in some cases entirely noise based Smaller segments of the U.S. market, where analytic coverage tends to be skimpier, we tend to see less efficient pricing As information becomes more accessible, i.e. as information costs decline), the role of valuation increases Domestically, the S&P 500 stocks, for which information is most readily available, prices tend to be more efficient than in other parts of the market as value plays a bigger role The nature of the business is another aspect As it becomes more feasible to value stocks, value traders become more prominent and noise trading diminishes As conventional valuation becomes more difficult, noise investors find happier hunting ground See, e.g., Tesla, Amazon, many start-ups, many boiotechs 68

69 Practical Implication Since arbitrage costs are not likely to reach zero, we cannot expect stock prices to truly match value Noise is a normal part of the market s equilibrium condition It cannot be dismissed as an unfortunate circumstance We cannot sit back and sneer or hope it will be conquered by investor education We CAN factor it into our approaches to stock finding and analysis P = V + N, or Price = Value + Noise 69

70 Noise-Value Calibrator: The Calculations 70

71 Quantifying the Impacts of Noise and Value Deconstruct a stock s market cap (MC) into two components Value based strictly on present business operation (VPO) This is a very conservative bond-like valuation which assumes the income component never rises We might call it a stand-still valuation Value based on future growth prospects (FGV) Therefore... MC = VPO + FGV 71

72 VPO is easy to calculate VPO = NOPAT / CC Where NOPAT = Net Operating Profit After Tax CC = Cost of Capital NOPAT = Operating profit * (1 tax rate) For this purpose, Operating Profit = EBIT We see many abnormal tax rates in the real world You can simply eliminate such stocks, or just assume all tax rates are normal; i.e. NOPAT = OperProf *.65 CC can be incredibly difficult to calculate For our purposes, it s OK to just pick a simple heuristic assumption, like.07 Therefore, VPO = (OpProf*.65) /.07 72

73 After getting VPO, FGV falls into place FGV = Market Cap VPO, or FGV = Market Cap ((OperProf*.65) /.07) 73

74 Let s jump to Value and Noise V% = VPO / MktCap N% = FGV / MktCap Where V% is the percent of a stock s market cap attributable to Value N% is the percent of a stock s market cap attributable to Noise 74

75 A Simple Back-of-the-Envelope Formula to Calculate the Impact of Noise in a Stock Price N = (MktCap ((OperProf*0.65) / 0.07))/MktCap Recall that OperProf, for this purpose, is the same as EBIT 0.65 is a simplistic across-the-board assumption for 1-TaxRate 0.07 is a shorthand heuristic assumption for cost of capital

76 A Bit of Cheating We assumed that FGV = Noise, based on an assumed standstill valuation In truth, we know that FGV = RG + NG + PN Where RG = realistic growth expectations NG = noise-based growth expectations PN = pure noise To go forward, we ll have to assume that RG is always zero We ll live with that Value gurus often talk about a margin of safety; here it is Unlike with DDM, DCF, etc. etc. etc., we re not going to pretend to be more precise than we can actually be Our estimate of Noise is likely to be a bit overstated, but as long as we understand that and refrain from getting carried away with specifics, we can live with this, and even use it for screening and analysis 76

77 Value as a % or Market Cap Quantified using the previously-described technique sector medians Value is important, but it doesn t stand alone Value tends to be more stable Many near- and intermediate-term stock price are likely to be noise driven Can you see a link between value % and ability to calculate value? 77

78 Some Well Known Stocks 78

79 What it Means Unless we expect arbitrage costs to be zero (which is not the case), we cannot expect stock prices to strictly be equal to value Noise is a normal part of the market s equilibrium condition It cannot be dismissed as an unfortunate circumstance We cannot sit back and sneer or hope it will be conquered by investor education We CAN factor it into our approaches to stock finding and analysis 79

80 Noise-Value Calibrator: The Excel Spreadsheet 80

81 The Spreadsheet Your inputs are highlighted in yellow 81

82 Tool 2: Residual Income Model (RIM) Calculator 1. The Approach 2. The Items 3. The Excel Spreadsheet 82

83 The RIM Approach 83

84 Starting Point: the Dividend Discount Model (DDM) Stock price is equal to present value of all future dividends P = D / (k g) Where P = Stock Price D = Dividend k = required rate of return g = expected dividend growth rate 84

85 Discounted Cash Flow (DCF) Stock price is equal to present value of all cash flows 85

86 Problems with DCF It s hard enough to predict one quarter ahead Do we seriously think it s possible to predict cash flows five, 10 or haven forbid 15 years ahead! I know I talked about being vaguely right or being less wrong than other, but there have to be limits to everything There s a difference between being imprecise or less wrong, versus being just-plain whacky Although we can never eliminate the need to predict, we should, at least, try our best to cope by: Making as smaller number of predictions as possible, and Trying to have as many of those predictions be of items that are less unpredictable DCF doe not mitigate the predictability problem. It maximizes it! 86

87 RIM as an Alternative to DCF Its Much Simpler Only 8 inputs into an Excel spreadsheet (one of which is the current stock price) Its More effective The main driver of this model is return on equity, a metric that s extremely relevant to determining company quality and which tends to be stable over time It minimizes the unpredictability problem 87

88 RIM Calculator: The Items 88

89 Introducing RIM The Residual Income Model Value = Capital + Present Value of Future Enhancements to Wealth Capital = Book Value Present Value of Future Enhancements to Wealth = Present Value of Residual Income Residual Income = Book Value * (Return on Equity Cost of Equity) Residual income formula is analogous to basic net income, which is equity multiplied by return on equity What we re doing here is considering only that portion of equity that is above cost of equity; bona fide enhancements to shareholder wealth 89

90 RIM Calculator: The Spreadsheet 90

91 The Spreadsheet-The Whole Thing! 91

92 The Formulas 92

93 Optional: An Expanded Version 93

94 Expanded Version Formulas (1) 94

95 Expanded Version Formulas (2) 95

96 Thank You! 96