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Earnings Estimates, Predictor Specification, and Measurement Error 203 TAELE 6-3 Consensus versus Flash Trend Portfolios Consensus Trend Flash Trend z CHV Tx XON AXP Top Five Stocks AA IBM CHV XON UTX Bottom Rve Stocks UK GM BS wx IP IP BS BA UK GM z CHV Tx XON AXP CAT T S DD KO ' Top 10 Stocks AA IBM CHV UTX XON CAT MRK Tx MO MMM Bottom 10 Stocks UK GM BS wx IP AA MCD GT IBM 7 tied for tenth IP BS BA JPM wx Z EK UK GM GT
204 selecting securities of 70 percent for the top 100,300, and 500 stock portfolios and 67 percent for the bottom 100,300, and 500 stock portfolios. These findings suggest that, in screening, the precise specifica tion of the E/P predictor (at least as between 6-week flash and consensus data) may not have much effect on portfolio results, especially when the investment universe consists of well-known, widely followed stocks. For forecast earnings trend, however, different specifications of the predictor may lead to very different por folios and very different investment results. Alternative Specifications of E/P and Trend for Modeling Returns Does the relationship between stock returns and their possible predictors depend on the specification of the predictors? To examine this, we fit the model: Return = U + b (consensus predictor) consensus predictor) c (flash- d (controversy) + e (neglect) (6.3) Here "return" is the excess return for the subsequent month (relative to the Treasury bill rate). The "consensus" and "flash predictors'' used are based on fiscal year 1 earnings estimates. Controversy is defined as the standard deviation of fiscal year 1 earnings estimates, where the estimates are based on flash data if available or otherwise on consensus data. Neglect is defined as -log (1 + number of fiscal year 1 analysts) Controversy and neglect are included to control for some important expectational-related return effects? We estimate two separate modekne for the forecast E/P predictor and the other for the forecast earnings trend predictorusing the 3000-stock universe and monthly data from April 1990 through December 1996.1° The analysis includes only those stocks for which at least Consensus data are available. All explanatory variables are standardized with winsorimtion set at f 5 standard deviations from the mean in order to truncate outliers. Methods of
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EQUITY MANAGEMENT.
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EQUITY MANAGEMENT Quantitative Anal
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To Ilene, Lauren, Julie, Sam, and E
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CONTENTS Foreword by Harry M. Marko
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Contents ix Chapter 4 Calendar Anom
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Contents xi Implications 272 High-D
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FOREWORD by Harry M. Markowitz, Nob
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Foreword xv In practice, of course,
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Foreword xvii that an RDM would con
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xix
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INTRODUCTION Life on the Leading Ed
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Life on the Leading Edge 3 tion abo
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Life on the Leading Edge 5 clude th
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Life on the Edge Leading 7 stocks t
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Life on the Leading Edge 9 . Quanti
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Life on the Leading Edge 11 By the
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Life on the Leading Edge 13 ple, st
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Life on the Leading Edge 15 find be
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Life on the Leading Edge 17 equal t
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P A R T ONE Selecting Securities A
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Selectine Securities 21 stocks. Suc
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selecting secunties 23 unmoved by s
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CHAPTER 1 The Complexity of the Sto
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The Complexity of the Stock Market
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The Complexity of the St& Market 31
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The Complexity of the St& Market 37
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The of the Complexity Stock Market
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The Comdexitv of the Stock Market 4
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V 7
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Disentangling Equity Return Regular
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Disentangling Equity Rehun Regulari
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Disentangling Equity Rehun Regulari
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64 selecting securities aged 59 bas
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66 selecting Securities FIGURE 2-2
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68 selecting securities FIGURE 2-3
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70 selecting securities tic of 17.8
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72 selecting securities Some Implic
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74 selecting securities Table 2-2 d
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I l
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82 Seleaine Securities these time-s
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84 selecting securities of 9.7. The
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86 selecting securities 2. There ar
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and deferring gains [as per Constan
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90 selecting securities 35. For exa
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92 selecting securities 49. Before
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94 selecting securities Ball, R. 19
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96 selecting securities Iowa, Ames.
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98 Seleaine securities James, W. an
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100 selecting securities Nicholson,
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102 selecting securities Tinic, S.
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104 selecting securities VALUE AND
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106 selecting securities Street Jou
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108 Selectine Securities This is no
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110 selecting securities plaining s
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112
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114 selecting securities transient
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116 selecting securities Na'ive Exp
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118 selecting securities (1988c)l.
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l20 selecting securities average of
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124 selecting securities We have de
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126 selecting securities movements
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l28 selecting securities 34. Pensio
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130 selecting securities Einhom, S.
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132 Selectine securities Poterba, J
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136 selecting securities The availa
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138 selecting securities subsequent
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142 Selectine securities FIGURE 4-2
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144 selecting securities others usi
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146 Selectine Securities FIGURE 4-3
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l48 SelectirlE securities a market
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150 . selecringsecurities There is
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Page 175 and 176: 154 seleding securities Chari,V., R
Page 177 and 178: 156 Selectine securities McNichols,
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Page 199 and 200: 178 Seledine securities multivariat
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Page 203 and 204: 182 selecting securities rate produ
Page 205 and 206: 184 Seledine Securities 11. Further
Page 207 and 208: 186 Seleaine securities REFERENCES
Page 209 and 210: 188 selecting securities Fama, E. a
Page 211 and 212: 190 selecting securities Miller, E.
Page 215 and 216: 194 Selectine Securities modeling p
Page 217 and 218: 196 selecting securities surement e
Page 220: Earnings Estimates, Predictor Speaf
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Page 243 and 244: 222 Seleaine Securitiff ings data f
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Page 251 and 252: 230 Managing Portfolios have concen
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Page 271 and 272: 250 Managing Portfolios REFERENCE J
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254 Managing Portfolios FIGURE S-l
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256 Managing Portfolios manager‘s
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258 Managing Portfolios FIGURE S 4
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260 Managing Portfolios Imposition
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264 Managing Portfolios Recent stud
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High-Definition Style Rotation 267
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0 N
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272 Managing Portfolios TABLE 10-2
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274 Managing Portfolios ing pure re
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276 Managing Portfolios HIGH-DEFINI
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278 Managing Portfolios - FIGURE 10
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280 Managing Portfolios FIGURE 10-S
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282 Managing Portfolios REFERENCES
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284 Expanding Opportunities and “
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286 Expanding Opportunities such as
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290 ExpandingOpprtunities vided sho
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292 Expandingoppo~ties F I G U R E
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294 Expanding Opportunities F I G U
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2% ExpandingOpportunities FIGURE 11
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298 Expanding Opportunities Typical
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300 Expandingopportunities F I G U
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302 Expanding Opportunities news st
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304 ExpandingOpportunities dinate l
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306 ExpandingOpportunities Also, ma
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308 Expanding Opportunities FIGURE
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310 Expanding oppo~ties -and- . 199
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312 ExpandingOpportunities applied
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314 Expanding Opportunities A secur
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316 ExpandingOpportunities in 1987,
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318 Expanding Opportunities the $4.
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320 Expanding Opportunities portfol
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322 Expanding Opportunities managem
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324 Expanding Opportunities The sec
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326 Expanding Opportunities Overall
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328 Expanding Opportunities risen o
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330 Expanding Opportunities lio and
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332 Expanding Opportunities FIGURE
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334 Expanding Opportunities , use o
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The Long and Short on Long-Short 33
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340
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Uptick rules can delay, or in some
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344 Expanding Opportunities expecte
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Nonsymmetrical distributions of sec
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11. We assume a futures margin of 4
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350 Expanding Opportunities see, lo
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352 Expanding Opportunities case, t
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Trading Costs Some other costs of l
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356 Expanding Opportunities We use
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358 Expanding The optimal portfolio
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360 Expanding Opportunities N H = C
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362 Expanding Opportunities . Consi
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364 Expanding Opportunities mark se
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366 Expanding Opportunities not be
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370 Expanding Opportunities securit
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372 Expanding Opportunities maximiz
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374 ExpandingOpportunities uity ret
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376 Expanding Opportunities may be
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378 Expanding Opportunities from se
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hance good performance, but they ca
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382 Name Index Clarke, Roger G., 25
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384 Name Index Levis, M., 174,175,1
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386 Name Index Swanson, H., 183,188
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388 Subject Index Disentangling equ
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390 Subied Index MAE, 170,182 Marke
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392 Subiect Jndex Security analysis
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