2013 MS us stock market outlook

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November 26, 2012
US Equity Strategy
The 2013 Playbook
We are launching our 2013 US equity outlook today.
We have been cautious on US equities for much of the last two years. Our concerns around US deficit / debt and the obvious borrowing from the future that occurs from unconventional policy, the European sovereign crisis, and slower growth in emerging markets generally remain, but the acuteness of these issues appears for now to be less sharp. Our 2013 year-end target calls for low-to-mid single digit upside (Exhibit 1) predicated on our view that 2014 corporate earnings are likely to modestly recover from our 2013 forecasted level, perhaps with profits troughing during the April 2013 earnings season.
Our year-end 2013 S&P500 price target is 1434, and our bull and bear targets are 1733 and 1135 (Exhibit 1). Our EPS outlook for 2014 is $110.21, up from our 2013 forecast of $98.71, both well below consensus.
Improving Michigan Confidence and tightening corporate spreads drive the relative improvement in our earnings outlook. Please see our Interactive Model: S&P500: 2013 Year-End Forecast, also published today, to play with key assumptions and change assumptions for EPS, S&P price-to-earnings multiples and the year-end price target.
3 Themes - China, Yield and Mega Cap Quality: We recommend increasing China exposure, as China-centric US equities have lagged (Exhibit 22) and are cheap (Exhibit 24) vs. US-centric equities. Our Global Economics Team forecasts 1H 2013 China GDP growth will be improving, something not assumed in either the US or Europe. We believe a combination of dividend and dividend growth will outperform in 2013. Fears about dividend tax rates persist, but the cohort looks compelling given low payout ratios, attractive yields vs. bonds, and record cash balances that could benefit from tax reform or repatriation in a grand bargain. Mega caps remain attractively valued (Exhibit 37) and generally are higher quality with better estimate achievability than the broader market. We are not making a strong growth / value bet given that revenue results have been muted of late (Exhibit 39).
M O R G A N S T A N L E Y R E S E A R C H N O R T H A M E R I C A
Morgan Stanley & Co. LLC
Adam S. Parker, Ph.D
Adam.Parker@morganstanley.com
+1 212 761 1755
Brian T. Hayes, Ph.D
Brian.T.Hayes@morganstanley.com
Antonio Ortega
Antonio.Ortega@morganstanley.com
Adam J. Gould, CFA
Adam.Gould@morganstanley.com
Phillip Neuhart
Phillip.Neuhart@morganstanley.com
Yaye Aida Ba
Yaye.Ba@morganstanley.com
We made a number of sector changes for this 2013 outlook. Our new sector recommendations are shown in Exhibit 43 with details beginning on pg. 18.
1)We have upgraded industrials from market-weight to overweight and downgraded technology from overweight to market-weight.
2)We have downgraded financials from market-weight to underweight.
3)We have downgraded staples from market-weight to underweight, remaining overweight health care.
4)We have upgraded energy from underweight to market-weight.
Our portfolio changes are generally skewed toward the three themes we identify in the second part of this note
– more China, more cash and dividend growth exposure, and a continued bias toward mega caps and quality where possible.
Our overweight sectors are now health care and industrials. We are recommending underweights in consumer discretionary, staples, and financials (Exhibit 43). Today, we are removing LO, TFM, and
WU from our portfolio, while adding GM, KMI, MWE, DHR, CCI, DUK, and A.
Morgan Stanley does and seeks to do business with companies covered in Morgan Stanley Research. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of Morgan Stanley Research. Investors should consider Morgan Stanley Research as only a single factor in making their investment decision.
For analyst certification and other important disclosures, refer to the Disclosure Section, located at the end of this report.
2013 US Equity Outlook
Our year-ahead outlook is broken into 3 parts –
Part I: Earnings, Multiples and a Framework for the S&P Target
Part II: Themes and Microstructure
Part III: Sector Bets and Stock Selection
_________________________________________________
Part I: S&P Price Target – Earnings, Multiples and a
Framework for the S&P Target
In this section, we discuss our methodology and logic for the year-end 2013 S&P 500 price target.
We wish we didn’t have to set a year-end target. Having had a very accurate one in 2011 and a pretty bad one in 2012, we are living proof that there is a negative asymmetry. We felt little joy in 2011 and lots of pain in 2012 related to the target, and find few credible investors really care where we think the market is going to be on a particular day one year in the future. What they more often care about is the logic and thought process, and the empirical evidence that support it. In that light, our view of the price target, multiples and earnings are strongly influenced by two proprietary quantitative models: SWEEP (our Sector-Weighted Equity Earnings Predictor), which predicts the S&P500 earnings 13-24 months in the future; and a forward price-to-earnings multiple model for estimating the multiple 12 months ahead. While these models were rigorously tested, it is difficult to replicate the extreme market conditions currently in place (such as QE, sovereign debt risk, strife across the Middle East, etc.); consequently, we tweak the quantitative forecasts based on our judgment of the impact of unique circumstances for the coming year. Because both the earnings and multiple models incorporate parameters (such as yields) that have yet to be determined - since they are either year-end 2012 or 2013 values, we introduce an interactive tool for readers to explore the impact of parameter changes on the earnings multiple and price target (see our Interactive Model: S&P 500: 2013 Year-End Forecast, also published today). The key results for our price target are shown here in Exhibit 1.
Our 2013 year-end target is 1434, offering low-to-mid single digit upside in our base case. Importantly, we see 2014 earnings growing 11.7% from our 2013 forecast in our base case. While both of these figures are well below the
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
bottom-up consensus outlooks and the consensus top-down views, the actual growth, which likely picks up in the second half of 2013, makes us more constructive on corporate profits than we have been in recent quarters. Our bear case is 1135 and our bull case is 1733 on the S&P500 by year-end 2013.
Exhibit 1
Our Year-End 2013 S&P 500 Price Target Is…
Morgan Stanley Year-End 2013 S&P 500 Price Target Methodology
Probability
Scenario
Upside /
EPS Landscape
of Scenario
2012E
2013E
2014E
Multiple
Target
(Downside)
Bull Case
20%
105.0
116.3
129.5
13.4x
1733
22.9%
Growth
8%
11%
11%
Base Case
60%
100.0
98.7
110.2
13.0x
1434
1.8%
Growth
2%
(1%)
12%
Bear Case
20%
95.0
81.1
90.9
12.5x
1135
(19.4%)
Growth
(3%)
(15%)
12%
Probability Weighted S&P 500 Price Target
1434
1.8%
Current S&P 500 Price
1409
Source: Factset, Morgan Stanley Research
Earnings Forecast: SWEEP and Some Guess Work
Our task of computing a year-ahead price target requires us to estimate earnings and the equity multiple well in advance. Equity markets are forward looking, so at the end of 2013, the equity market will begin trading on views about a distribution of possible estimates for 2014 earnings. We therefore need an estimate of S&P earnings 13-24 months ahead. In addition, we need to estimate the multiple that the market will assign to 2014 earnings one year hence. As of late 2012, many analysts have not yet released 2014 forecasts and few companies have released 2014 earnings guidance. Since 2014 EPS cannot yet reliably be “looked up”, we must estimate it based on better-established values, such as current consensus earnings.
Our approach (Exhibit 2) is to compute a growth rate from 2013 consensus S&P EPS, as of the end of 2012. We compute S&P earnings growth at the sector level with a proprietary model called SWEEP (see US Equity Strategy: Introducing SWEEP, May 7, 2012).
2
Exhibit 2
We Estimate 2014 S&P EPS by Computing a Growth Rate from the 2013 Consensus EPS Forecast
2013 Year-End Forecast
Forward Earnings Growth Approach
NTM Forecast Available
Model Growth YoY in NTM
Mar Jun Sep Dec Mar Jun Sep Dec
Mar Jun Sep Dec
2012
2013
2014
Source: Morgan Stanley Research
SWEEP was designed to use only currently available data in its forecast. A logistical complication of producing our 2013 year-end target in November 2012 is that final values for many parameters are not yet available. Recent increases in market volatility compound the difficulty of assigning values to many of the parameters. An additional quantity that is still uncertain is the year-end consensus for 2013 S&P earnings; we must give an approximate value as a base for our 2014 growth rates.
Consensus estimates for 2013 S&P earnings have fallen by $2.02 since October 19 and currently stand at $113.66 (Exhibit 3). Given the recent (and longer-run) estimated earnings trajectory for 2013, as well as SWEEP’s 2013 forecast of $99, we estimate that as of December 31, 2012, consensus 2013 S&P EPS will be $110.02. This is essentially an extrapolation of recent trends (the 2013 earnings estimate was around $121 at the beginning of this year), with incremental declines due to anticipated negative guidance near the end of Q4. We will use this estimated value of 2013 earnings as our base for 2014 SWEEP estimates. That is, the growth rate in earnings computed by SWEEP will be applied to this anticipated 2013 level.
Another factor that leads us to be bearish on the trajectory of 2013 consensus earnings for the rest of 2012 is that guidance trends have continued to be negative (Exhibit 4).
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 3
2013 Earnings Estimates Have Declined but Likely Have Further to Fall
Annual S&P 500 Consensus EPS
As of November 2012
$125
2013E
$120
$115
$113.66
$110
2012E
nbsp;
$105
$103.00
$100
2011
$97.57
$95
$90
Jan-10
May-10
Sep-10 Jan-11
May-11
Sep-11
Jan-12
May-12
Sep-12
Source: Factset, Morgan Stanley Research
Exhibit 4
Companies Are Continuing to Guide Lower
Ratio of Negative-to-Positive At T-5
S&P 500 Guidance Relative to Consensus Expectations
3.5
Average = 2.3
T=0 is end of Quarter
2.83
3.04
3.0
(Since 1Q05)
2.60
2.28
2.32
2.5
2.09
2.0
1.78
1.76
1.74
1.5
1.11
1.02
1.0
0.97
0.5
0.0
1Q10
2Q10
3Q10
4Q10
1Q11
2Q11
3Q11
4Q11
1Q12
2Q12
3Q12
4Q12
Source: Factset, Morgan Stanley Research
Why does any of this matter to us? SWEEP forecasts earnings growth in each sector, based on a range of factors: yields, commodities, currencies, credit spreads, macro variables and technical factors (such as momentum or mean reversion of earnings by sector or the market) relative to the consensus outlook for earnings the prior year. By sector, SWEEP is parsimonious, with just 3-5 factors; when aggregated across the 10 sectors, however, a total of 19 factors appear (see Exhibit 5). The SWEEP forecasts require 2012 year-end inputs for the levels of most of these factors (the only exceptions are lagged variables on earnings). With over a month remaining before year-end, it is necessary for us to estimate year-end values to form our price target.
3
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 5
SWEEP Is a Diversified Earnings Model Comprised of 19 Factors in Five Categories
Earnings Analysis: Weight of Factors Tested, 1987-2011
TD class="tr7 td119">
1.3%
Factors Tested
Factor Weight Within:
Weight of
Factor in
Energy
Materials
Industrials
Discretionary
Staples
Health Care
Financials
Technology
Telecom
Utilities
Overall Model
Commodities
10.2%
Gold YoY%
31.5%
24.1%
3.7%
Crude Oil YoY%
25.2%
30.3%
21.7%
17.1%
6.5%
Rates/Fixed Income/Currency
35.1%
Fed Funds Rate YoY Diff, %
42.1%
17.7%
6.5%
10-Yr. Treas, 2-Yr Treas. Level YoY Diff, %
37.6%
13.0%
2.0%
10-Yr. Treas, 2-Yr Treas. Slope YoY Diff, %
15.4%
0.5%
Baa-10-Yr. Treas. Spread, QoQ Diff, BPS
27.1%
29.2%
14.3%
Baa-10-Yr. Treas. Spread, YoY Diff, BPS
27.5%
51.4%
6.9%
Dollar Index YoY%
32.7%
19.3%
26.9%
4.9%
Macroeconomic
40.9%
Real GDP YoY%
41.3%
10.6%
Nonfarm Payroll, As First Reported (SA, Thous) YoY Diff
19.3%
54.3%
28.6%
9.5%
ISM: First Reported Post-1990; Final Pre-1990 YoY%
29.5%
7.6%
Michigan Sentiment, Final YoY%
21.7%
25.0%
15.4%
25.7%
13.2%
Size/Style Residuals

12-Mo Trailing Mid-Large Residual, %




38.3%





1.2%
12-Mo Trailing Value-Growth Residual, %








34.7%
22.9%
0.1%












Market/Sector Level Earnings










12.5%
Market NTM EPS Growth - 4Q Lag








24.3%
17.7%
1.2%
Sector NTM EPS Growth - 4Q Lag











Health Care





39.1%




2.3%
Sector NTM EPS Growth - 8Q Lag











Industrials


23.6%







2.0%
Financials






25.5%



6.4%
Sector Temporal Identifiers











Energy*
0.0%









0.0%
Technology*







0.0%


0.0%
Telecom








23.3%

0.6%
Total
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
Number of Factors
4
4
3
3
3
4
4
4
4
5

Sector Earnings Weight
13.6%
4.0%
9.9%
9.9%
9.9%
11.8%
16.8%
19.0%
2.1%
2.9%









Total Factors:
19









Effective Factors:
11.5


*These factors were included in the historical model but are no longer active.
Source: Factset, Morgan Stanley Research
We are launching a new interactive tool to enable clients to alter key assumptions in our earnings and multiple models, so they can assess the sensitivities of our 2013 year-end price target. For this interactive price target module, we selected five variables for readers to toggle. In each case, the factors can be set over predetermined year-end ranges; the initial slider locations represent our parameter choices. Using these five variables, nine of ten 2014 sector EPS estimates can be computed. Only telecom, whose earnings drivers are either pegged by the Fed or are technical in nature, is invariant under changes in the five sliders. Fortunately, telecom represents a small weight within aggregate S&P earnings (see our
Interactive Model: S&P 500: 2013 Year-End Forecast, also published today).
Based on our parameter choices, we obtain a 0.2% earnings growth rate for 2014 from SWEEP using the adjusted 2013 consensus outlook. When applied to our estimate for year-end consensus 2013 S&P earnings, we obtain a 2014 earnings estimate of $110.21 (Exhibit 6). Our bull and bear case earnings estimates are chosen to be +/- 1 standard
deviation outcomes. From SWEEP historical errors, we compute the forecast standard deviation of 17.5%. The results are a $129.50 bull-case and a $90.93 bear-case EPS.
Exhibit 6
We Forecast 2014 S&P500 EPS of $110, With Bull-Bear Ranges of Roughly $20 on Each Side
S&P 500 EPS Estimates



SWEEP 2014 EPS
Scenario
Estimate
Bull Case
$129.50
Base Case
$110.21
Bear Case
$90.93
Source: Factset, Morgan Stanley Research
In Exhibit 7, we summarize our earnings estimates versus consensus for 2012 – 2014. In the last case, we have included a current 2014 consensus estimate of $125. Given the paucity of 2014 data at this early stage, we highlight its tentative nature with a question mark. While we are more constructive (knowing what we know now) on 2014 EPS than 2013, we remain well
4
below consensus for 2013, and well below an early marker for 2014 consensus earnings. Hence, the primary debate surrounding market performance will likely surround investor reaction (i.e., fear) as the earnings outlook declines, not whether earnings will decline. (That is a conversation about the multiple, however, and we will get to that.)
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 7
Our Estimates Compared to Consensus…

Morgan Stanley and Consensus S&P 500 Earnings Estimates


As of November 2012
?



Consensus

$125


MS Estimates
$114



$110



$103
$100
$99






2012E
2013E
2014E
Source: Factset, Morgan Stanley Research
We can decompose SWEEP’s overall earnings growth rate forecast of 0.2% for 2014 (based on adjusted consensus estimates) into its contributions from each of the underlying factors. The cumulative factor contributions, obtained by scaling sector coefficients by sector earnings weights and summing across sectors, is shown in Exhibit 8. Unlike the 2013 SWEEP estimate where 13 of 19 factors contributed negatively, the contributions are quite mixed in 2014. The main drivers are macro factors: positive for Michigan Sentiment Index increases, and negative for increases in real GDP and nonfarm payrolls (recall these latter variables occur with negative signs at periods 13-24 months ahead). Tightening credit spreads also benefit estimated earnings growth. Another big difference from 2013 to 2014 in SWEEP is that some extreme post-Crisis earnings growth has rolled off, and mean reversion is no longer as strong of a negative factor. Falling crude oil prices over the last year are a net positive for 2014 earnings, as falling crude benefits discretionary sector earnings more than it detracts from energy earnings 13-24 months out. Hence, relative to our own earnings estimate for 2013, we expect 2014 earnings to recover 11.7%.
5
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 8
Michigan Sentiment and Corporate Spreads Drive EPS Growth; GDP and Nonfarm Payrolls Are Offsets
<![if ! IE]>
<![endif]>Contribution to the Change in NTM EPS
Decomposition of Model Result: Change in NTM EPS
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
(0.5%)
(1.0%)
<![if ! IE]>
<![endif]>WTI YoY%
<![if ! IE]>
<![endif]>Nonfarm Payroll
<![if ! IE]>
<![endif]>Mich Sentiment
<![if ! IE]>
<![endif]>ISM
<![if ! IE]>
<![endif]>Gold YoY%
<![if ! IE]>
<![endif]>Real GDP YoY%
<![if ! IE]>
<![endif]>Dollar Index YoY%
<![if ! IE]>
<![endif]>Baa-10Y ,YoY Diff
<![if ! IE]>
<![endif]>10s,2s Slope YoY Diff
<![if ! IE]>
<![endif]>10s,2s Level YoY Diff
<![if ! IE]>
<![endif]>Baa-10Y, QoQ Diff
<![if ! IE]>
<![endif]>Value-Growth Residual
<![if ! IE]>
<![endif]>Trailing Mid-Large Residual
<![if ! IE]>
<![endif]>Telecom Indicator
<![if ! IE]>
<![endif]>Market NTM EPS - 4Q Lag
<![if ! IE]>
<![endif]>Industrials NTM EPS - 8Q Lag
<![if ! IE]>
<![endif]>Health Care NTM EPS - 4Q Lag
<![if ! IE]>
<![endif]>Financials NTM EPS - 8Q Lag
<![if ! IE]>
<![endif]>Bias-Adj Intercept
<![if ! IE]>
<![endif]>Overall Change
Source: Factset, Morgan Stanley Research
In Exhibit 9, we compare our 2014 SWEEP sector earnings estimates with the current 2013 consensus estimates. In this case, we use the most recent consensus values, rather than our year-end estimates that formed the basis for SWEEP. Financials, discretionary and materials are up relative to 2013 consensus, while telecom and energy have the largest forecast declines among the seven sectors that are down.
Exhibit 9
Most of Our New 2014 Sector EPS Estimates Are Less Than 2013 Consensus Values
Sector Contribution to EPS Estimate ($)

2013E
2014 MS Est
Diff 2014 vs. 2013
Sector
Consensus
(SWEEP)
$
%
Telecom
2.59
2.19
(0.40)
(15.4)%
Energy
14.24
12.72
(1.52)
(10.7)%
Utilities
3.41
3.19
(0.22)
(6.5)%
Technology
23.27
21.80
(1.47)
(6.3)%
Industrials
11.19
10.69
(0.50)
(4.5)%
Healthcare
13.61
13.06
(0.55)
(4.0)%
Staples
10.13
9.76
(0.37)
(3.7)%
Financials
20.36
20.80
0.44
2.2%
Discretionary
10.86
11.36
0.50
4.6%
Materials
3.99
4.64
0.65
16.3%
Source: Factset, Morgan Stanley Research
6
Multiple Forecasting: A Sisyphean Task?
Our recent note (see US Equity Strategy: Forecasting the Forward Multiple: A Hubristic Statistic? October 29, 2012), brought home just how difficult it is to forecast the forward earnings multiple. Not only is it difficult to forecast year-ahead changes in the multiple using information available at the start of the period, but even knowing how important macro variables evolve during the period provides little insight into the direction of the change. It is truly a Sisyphean task. For example, even if you knew how Treasury yields would evolve or real GDP would grow, you would still be flipping an almost-unbiased coin in predicting the sign of multiple changes.
Nevertheless, a weak model is better than no model – and we would argue that it is MUCH better, simply because it compels you to be modest in your predicted deviations from current multiples. Without such a model, investors may (and often do) forecast large changes in multiples without sufficient basis in data or macro information.
Exhibit 10 shows the price-to-forward earnings of the S&P500 over time. These data have existed since 1976, and the median price-to-forward earnings level since then is 13.7x. Admittedly, however, the market has rarely traded at that level for any sustained period.
Exhibit 10
Multiples Rarely Trade at the Average Level
Top 500: Price-to-Forward Earnings
Through October 2012
35x


















30x


















25x


















20x

Median = 13.7x






























15x


















10x


















5x


















76
78
80
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
12
Source: Factset, Morgan Stanley Research
Historically, interest rates and growth have mattered for market multiples. We argued in 2012 (Exhibit 11) that extreme rates (not just high rates) were historically bad for multiples, as shown by the “P/E Frown”, a phrase we borrowed from our colleague Marty Leibowitz. In the third quarter of 2012, we saw the lowest (basically most extreme) nominal 10-year yield in the history of the United States of America, and no growth in
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
earnings, yet multiples expanded during that period. Why is that?
Exhibit 11
Extreme Real Yields Mean Low Multiples
P/E Ratio vs. Real Long-Term Treasury Yield
Since 1930
20x







18x
At Present






16x













14x







<![if ! IE]>
<![endif]>Ratio







12x







<![if ! IE]>
<![endif]>P/E







10x







8x







6x







4x







< 0%
0-1%
1-2%
2-3%
3-4%
4-5%
5-6%
> 6%
Real Long-Term Treasury Yield
Source: Factset, Morgan Stanley Research
Our guess is that a number of things were responsible, but perhaps a major contributor was quantitative easing, which encompasses Fed and ECB policy (Exhibit 12). We are about to share our “weak” model for forecasting market multiples, but we can see that substantial deviations from this framework over the past few years were driven by QE.
Exhibit 12
Periods of Quantitative Easing Were Associated with Higher than Expected Multiple Increases
Top 500 Stocks: Forward P/E Multiple Model Residuals
3x
+2 St. Dev.

TD class="tr1 td15">
Sep-11
2x





QE2
Twist, ECB,
+1 St. Dev.




QE3 Start








1x


QE1, QE1





0x


Extension













(1x)
-1 St. Dev.













(2x)








(3x)
-2 St. Dev.














(4x)








Sep-09
Jan-10
May-10 Sep-10
Jan-11
May-11

Jan-12 May-12
Sep-12

Source: Factset, Morgan Stanley Research
This is not to say that QE was the only reason multiples deviated from our framework of low growth and extreme rates, as hedge fund positioning earlier in the year (low net exposure in June), improving fundamentals in housing, Draghi’s bumblebee speech, and other factors likely caused multiple expansion above our 2012 forecast.
7
Exhibit 13 shows the factors we considered in building our model to forecast market multiples. Few of these were statistically significant predictors, causing us to dub the multiple forecast a “hubristic statistic”. Either you have to be arrogant or unaware of its difficulty to do it. We are aware.
Exhibit 13
Very Few Factors Have Statistically Significant Predictive Power for Changes in the Market Multiple
Factors Tested: + or - Significance at 10%-Level


Ex Tech
Factor
Filtered
Bubble
Growth


Change in Average IBES Long-Term Growth Rate Forecast


Year-Ahead Change in Average IBES Long-Term Growth Rate Forecast


YoY Change in QoQ GDP
-
-
Year Ahead YoY Change in YoY GDP
-
-
Growth Rate in Forecast Earnings


Equity Market
-
-
Year Ahead YoY Equity Market
+
+
Large-Mega


Year-Ahead Large-Mega


Mid-Large
-
-
Year-Ahead Mid-Large

-
Value-Growth


Year-Ahead Value-Growth


YoY % Change in Housing Starts


Year Ahead YoY % Change in Housing Starts


YoY % Change in Industrials Metals


Year Ahead YoY % Change in Industrials Metals


YoY % Change in Non-farm payrolls


Year Ahead YoY % Change in Non-farm payrolls
-
-
YoY Change in YoY GDP


Year Ahead YoY Change in QoQ GDP


YoY Change in Consumer Confidence
-
-
Year Ahead YoY Change in Consumer Confidence


YoY Change in ISM
-
-
Year Ahead YoY Change in ISM
+
+
YoY Change in Unemployment Rate
+
+
Year Ahead YoY Change in Unemployment Rate
YoY % Change in Crude Oil (WTI)


Year Ahead YoY % Change in Crude Oil (WTI)


Interest Rates


YoY Change in 2s,10s Avg. Level


Year Ahead YoY Change in 2s,10s Avg. Level
-
-
YoY Change in 2s,10s Slope


Year Ahead YoY Change in 2s,10s Slope

+
YoY Change in Target Funds Rate


Year Ahead YoY Change in Target Funds Rate
-
-
Both Growth & Interest Rates


Headline Inflation (YoY % Change in CPI)


Year Ahead Headline Inflation (YoY % Change in CPI)


YoY % Change in Gold


Year Ahead YoY % Change in Gold


YoY % Change in Dollar Index


Year Ahead YoY % Change in Dollar Index


YoY % Change in M2


Year Ahead YoY % Change in M2


YoY Change in Baa-10Y Treasury Spread (Basis Pts)
+
+
Year Ahead YoY Change in Baa-10Y Treasury Spread (Basis Pts)


Year-Ahead Change in Forward P/E (4Qtr Lag)
-
-
Neither Growth nor Interest Rates


YoY Change in Dividend Tax Rate


Year Ahead YoY Change in Dividend Tax Rate


YoY Change in Cap Gains Tax Rate


Year Ahead YoY Change in Cap Gains Tax Rate


YoY Change in Top Marginal Corp. Tax Rate


Year Ahead YoY Change in Top Marginal Corp. Tax Rate


YoY Change in Top Marginal Income Tax Rate


Year Ahead YoY Change in Top Marginal Income Tax Rate


Source: Factset, Morgan Stanley Research
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 14 shows the four-factor model with modest statistical significance that we ultimately built. The factors include the performance of mid-cap stocks versus large-cap stocks, the overall market return, ISM manufacturing (a growth proxy) and the year-ahead year-over-year change in 2-year vs. 10-year yield levels. The forecast calls for a multiple of 13.0x at the end of 2013. Our bias would be to lower this, given we forecast rates are likely to stay low and given EPS growth will likely remain stagnant for the next couple of quarters), but the specter of more (unlimited) quantitative easing (with more-dovish Janet Yellen possibly succeeding Ben Bernanke) keeps us from doing that in the near term. If it becomes increasingly clear that further QE doesn’t make the actual economy better (i.e., lower unemployment and higher GDP), it would likely cause material multiple contraction below our base case assumption – closer to where we forecasted multiples to be last year.
Exhibit 14
We Built a 4-Factor Model from the 11 Individually Significant Factors
S&P 500 Forward P/E Model
Filtered Tech Bubble/Collapse


Coefficient


Factor
Sign


Trailing 12m Beta-Adjusted Mid-Large-Cap Spread
-


Trailing 12m Equity Market Return
-


Year Ahead YoY Change in ISM
+


Year Ahead YoY Change in 2s,10s Avg. Level
-




Source: Factset, Morgan Stanley Research


While changes in macro variables do not unconditionally correlate to changes in forward multiples, there are times when markets are focused on certain variables and improvements or when positive surprises can lead to multiple gains. Housing starts, for example, have become a key metric of economic health and consumer confidence; recent improvements in this metric have been associated with market rallies (i.e., multiple expansion). Generally, economic data in the last few months has exceeded expectations, and this has likely contributed to the effects of QE on raising the multiple in 2012.
When we combine our earnings forecast and multiple forecast, we arrive at our price target. To get our bull and bear cases, we vary our earnings algorithm one standard deviation in each direction. In the end, including dividends, we expect low-to-mid single digit returns from the S&P500 in 2013.
8
Exhibit 15
Our Year-End 2013 S&P 500 Price Target Is 1434
Morgan Stanley Year-End 2013 S&P 500 Price Target Methodology

Probability




Scenario
Upside /
EPS Landscape
of Scenario
2012E
2013E
2014E
Multiple
Target
(Downside)








Bull Case
20%
105.0
116.3
129.5
13.4x
1733
22.9%
Growth

8%
11%
11%



Base Case
60%
100.0
98.7
110.2
13.0x
1434
1.8%
Growth

2%
(1%)
12%



Bear Case
20%
95.0
81.1
90.9
12.5x
1135
(19.4%)
Growth

(3%)
(15%)
12%



Probability Weighted S&P 500 Price Target



1434
1.8%
Current S&P 500 Price




1409

Source: Factset, Morgan Stanley Research
Overall, growth expectations in 2013 are expected to be more diversified than what we saw in 2012. The top 10 stocks in the S&P500 contributed nearly 88% of earnings growth this year (Exhibit 16).
Exhibit 16
In 2012, Ten Stocks Are Driving about 88% of the Entire S&P500’s Earnings Growth
Contribution to 2012 S&P 500 YoY Earnings Growth,

As of November 23, 2012
WDC
100%
GE
90%
C
80%
IBM
70%
JPM
60%
WFC
50%
GS
AIG
40%
BAC
30%
AAPL
20%

10%

0%

Top 10 Contributors
Rest
Source: Factset, Morgan Stanley Research
In 2013, the current EPS forecasts call for far less concentrated growth (Exhibit 17), with the top 10 names driving only 34% of total growth.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 17
But in 2013, the Top 10 Names Should Drive Just 34% of Total Growth

Contribution to 2013 S&P 500 YoY Earnings Growth,
70%
As of November 23, 2012
C

WFC


60%

S

FCX


50%

IBM
40%

GOOG

GE


30%

MSFT
20%

BAC

AAPL


10%


0%



Top 10 Contributors
Rest
Source: Factset, Morgan Stanley Research
Furthermore, the top 15 companies now account for roughly 40% of the forecast S&P 500 earnings growth for 2013 (Exhibit 18). Notably, Apple, Bank of America, Microsoft, GE, and
Google are forecasted to be one-quarter of the entire S&P500’s earnings growth in 2013.
Exhibit 18
AAPL, BAC, MSFT, GE, and GOOG Are Forecasted to be One-Quarter of the Entire S&P500’s EPS Growth in 2013
Top 15 Contributors to S&P 500 2013 YoY Earnings Growth,
As of November 23, 2012



% Growth



Contribution To
Ticker
Company
Sector
S&P 500 (2013E)
AAPL
Apple Inc.
Technology
9.0%
BAC
Bank of America Corp.
Financials
7.5%
MSFT
Microsoft Corp.
Technology
5.3%
GE
General Electric Co.
Industrials
2.3%
GOOG
Google Inc. Cl A
Technology
1.8%
IBM
International Business Machines Corp.
Technology
1.8%
FCX
Freeport-McMoRan Copper & Gold Inc.
Materials
1.7%
S
Sprint Nextel Corp.
Telecom Services
1.6%
WFC
Wells Fargo & Co.
Financials
1.6%
C
Citigroup Inc.
Financials
1.4%
VZ
Verizon Communications Inc.
Telecom Services
1.3%
MU
Micron Technology Inc.
Technology
1.2%
JNJ
Johnson & Johnson
Health Care
1.1%
JPM
JPMorgan Chase & Co.
Financials
1.1%
PM
Philip Morris International Inc.
Consumer Staples
1.1%
Source: Factset, Morgan Stanley Research
There are more companies forecasted to have positive growth in 2013 compared to 2012 (Exhibit 19). We struggle with whether this is plausible. On the one hand, although there is essentially no EPS growth for the S&P500 right now on a year-over-year or sequential basis, by the second half of 2013 that may change. On the other hand, we see it as unlikely that nearly 90% of the companies will grow their earnings in 2013.
9
Exhibit 19
90% of the Companies in the S&P500 Are Forecasted to Grow Their EPS in 2013

% Of S&P 500 Companies with Expected Positive or
100%
Negative Earnings Growth,
As of November 23, 2012

90%

80%

70%

60%
+ ive Growth
50%
- ive Growth

40%

30%

20%

10%

0%

2012E
2013E
Source: Factset, Morgan Stanley Research
Financials are a huge wild-card for the earnings outlook, as the sector, at 14% of total market capitalization today, drove nearly 97% of the year-over-year earnings growth in 2012 (Exhibit 20). Expectations for the sector today are for only a 20% share of S&P500 growth next year, owing to less reserve releases, NIM compression, and other factors.
Exhibit 20
The Financial Sector Drove Much of the S&P500
Earnings Growth in 2012

% Contribution to S&P 500 YoY Earnings Growth,
120%
As of November 23, 2012

100%

80%
Financials
Non Financials
60%

40%

20%

0%

2012E
2013E
Source: Factset, Morgan Stanley Research
One way to assess where a reversal in fortunes is expected is to assess companies that are expected to grow 2013 earnings at a faster pace than in 2012 (Exhibit 21). It appears on the surface that the materials stocks (FCX, NEM, DOW) are among those where analysts are embedding a substantial rebound.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 21
Select Stocks Where 2013 Estimates Embed a Big Reversal from 2012 Include FCX, NEM, and DOW, Among Others
S&P 500 Companies Growing Earnings Faster in 2013 vs. 2012
As of November 23, 2012



Consenus YoY
Ticker
Company
Sector
Earnings Growth
2012E
2013E
MSFT
Microsoft Corp.
Technology
(6%)
24%
GE
General Electric Co.
Industrials
11%
13%
GOOG
Google Inc. Cl A
Technology
11%
16%
FCX
Freeport-McMoRan Copper & Gold Inc.
Materials
(33%)
48%
VZ
Verizon Communications Inc.
Telecom Services
14%
16%
JNJ
Johnson & Johnson
Health Care
2%
7%
PM
Philip Morris International Inc.
Staples
7%
11%
PRU
Prudential Financial Inc.
Financials
(4%)
28%
WMT
Wal-Mart Stores Inc.
Staples
9%
10%
DOW
Dow Chemical Co.
Materials
(25%)
34%
NEM
Newmont Mining Corp.
Materials
(15%)
38%
KO
Coca-Cola Co.
Staples
4%
9%
UTX
United Technologies Corp.
Industrials
0%
15%
F
Ford Motor Co.
Discretionary
(10%)
12%
WAG
Walgreen Co.
Staples
0%
27%
PG
Procter & Gamble Co.
Staples
(0%)
5%
DTV
DIRECTV
Discretionary
20%
22%
PEP
PepsiCo Inc.
Staples
(8%)
8%
NE
Noble Corp.
Energy
71%
91%
APA
Apache Corp.
Energy
(20%)
14%
Source: Factset, Morgan Stanley Research
In summary, we see 2014 EPS rising from 2013 levels in our base case, but are concerned that the consensus bottom-up numbers still need substantial downward revisions.
Part II: Themes and Microstructure
There are 3 major themes embodied in our 2013 year-ahead outlook. One is more China exposure, two is a bigger bet on dividend yield, dividend growth, and rewards for high cash balances, and three is a bet on mega cap stocks continuing to perform strongly as they did for an extended period in 2012.
Theme 1: Is China Exposure a Positive? For now, we think so.
We are increasing our China exposure within the US portfolio. The performance of US-centric retailers and industrials (particularly those with US housing exposure) has vastly exceeded performance of China-centric US equities; compare, for example, home builders vs. machinery (CAT) or low-end discounters vs. China-centric retailers (say RL) – see Exhibit 22. Recent data points, including export numbers for China, Korea, and Taiwan, point to a potential GDP bottoming. Our best guess is that US institutional investors will view the risk-reward of China-centric companies as increasingly
10
attractive. Even if estimates ultimately prove to be 10-15% too optimistic, our suspicion is that stock price action will not be that severe, based on trading behavior for CMI, CAT, and other companies providing negative news recently. With more bandwidth for Chinese fiscal policy, perhaps beginning in March of next year when new leadership can act, we are increasingly optimistic that China exposure will be seen as a positive again by US-based portfolio managers.
Exhibit 22
US-Centric Equities Have Outperformed
China-Exposed Stocks in 2012

Un-adjusted Cumulative Daily Returns

25%
US-Centric Less China-Exposed Stocks






20%





15%
US-Centric









10%
Outperforms









5%





0%





(5%)





(10%)





Jan-12
Mar-12
May-12
Jul-12
Sep-12
Nov-12
Source: Factset, Morgan Stanley Research
Our Global Economics Team, which produced its year ahead economic outlooks last week (Exhibit 23), forecasts positive and increasing GDP growth in the first half of 2013 for China, but doesn’t forecast this for either the US or Europe. To the extent that investors start believing China has bottomed, we think increasing China exposure will be deemed important.
Exhibit 23
China’s GDP Growth Is Expected to Accelerate in the First Half of 2013

Morgan Stanley GDP Growth Estimates
10%
Average Growth

2H 2012E


8%
1H 2013E


6%



4%



2%



0%



(2%)




US
Euro Area
China
Source: Factset, Morgan Stanley Research
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
The price-to-forward earnings of China-exposed US equities is near a five-year low vs. US-centric stocks, making the entry point compelling for adding China exposure (Exhibit 24).
Exhibit 24
China-Exposed US Equities Are Cheap vs. US-Centric Stocks


Relative Price-to-Forward Earnings

1.4x

China-Exposed Stocks / US-Centric Stocks






1.3x





1.2x





1.1x





1.0x





0.9x





0.8x





07
08
09
10
11
12
Source: Factset, Morgan Stanley Research
US equities with China exposure that also screen well in our quantitative models include GM and EMR, among others (Exhibit 25).
Exhibit 25
US Stocks with China Exposure that Screen Well in our Models Include GM and EMR, Among Others
China-Sensitive Stocks Ranked Q1 or Q2 of Alpha Models
Ticker
Company
MOST
BEST
APA
Apache Corp.
Q1
Q1
HES
Hess Corp.
Q1
Q1
JLL
Jones Lang LaSalle Inc.
Q1
Q2
GM
General Motors Co.
Q2
Q1
EMR
Emerson Electric Co.
Q2
Q1
FDX
FedEx Corp.
Q2
Q1
SLB
Schlumberger Ltd.
Q2
Q1
CMI
Cummins Inc.
Q2
Q2
JCI
Johnson Controls Inc.
Q2
Q2
Source: Factset, Morgan Stanley Research. For important disclosures regarding companies that are the subject of this screen, please see the Morgan Stanley Research Disclosure Website at www.morganstanley.com/researchdisclosures.
Theme 2: Dividend / Dividend Growth and Cash on the Balance Sheet
What do we make of all the cash on company balance sheets? This has been on the bull-case list for some time, as non-financial US equities have over $1.5 trillion at their disposal (Exhibit 26).
11
Exhibit 26
US Corporate Balance Sheets Hold $1.5 Trillion in
Cash
$1.6
Cash Balances
Top 1,500 Stocks (Ex-Financials, $T)
$1.4
Through Q2 2012

$1.2

$1.0

$0.8

$0.6

$0.4

$0.2

$0.0


61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11
Source: Factset, Morgan Stanley Research
With much of that cash in technology, health care, and industrials (Exhibit 27) a key debate always centers around the capital uses and consequences among US corporations.
Exhibit 27
Technology Has, by Far, the Largest Cash Holdings
35%
Share of Cash Balances by Sector (Ex-Financials)
32%
As of Q2 2012
30%







25%







20%



16%
16%
16%

15%











10%
6%
7%
7%











5%







0%
<![if ! IE]>
<![endif]>Staples
<![if ! IE]>
<![endif]>Energy
<![if ! IE]>
<![endif]>Other
<![if ! IE]>
<![endif]>Discretionary
<![if ! IE]>
<![endif]>Industrials
<![if ! IE]>
<![endif]>Health Care
<![if ! IE]>
<![endif]>Technology

Source: Factset, Morgan Stanley Research
Our Firm’s view is that corporate tax reform and a grand bargain including repatriation of foreign cash are more likely than not to gain traction among investors, putting companies with high cash balance in the spotlight. Our preferred way to play this right now is to own stocks with high, sustainable and growing dividends in some combination (for further details please see May 29th, 2012: US Equity Strategy: The Definitive Case for Dividend Yield).
So what’s the case for yield?
Exhibit 28 is one way of showing that there are just not as many compelling opportunities in the bond market, and owning
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
equities with reasonable secure growth outlooks and high yields likely makes sense. The S&P earnings yield is now above the high-yield market for the first time in well over 20 years (Exhibit 28). We think investors want income and will continue to be forced to look for it within the US equity market.
Exhibit 28
S&P 500 Earnings Yield Is Now Above US High Yield for the First Time in the History of the HY Market
US HY Yield and S&P Earnings Yield
14%











12%











10%











8%











6%











4%











2%
HY Yield - S&P Yield















0%











(2%)











1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
Source: Bloomberg, the Yield Book, Morgan Stanley Research
Dividends have accounted for a huge percentage of total equity returns over time (Exhibit 29), and we have no doubts this will be the case over any extended period of time going forward.
Exhibit 29
Dividends Have Accounted for Over 40% of Total Return Since 1930
S&P 500 Total Return: Price and Dividend Contribution


Total
Price
Income
As a Share of Total Return



Return
Appreciation
Return
Price App.
Div. Income


1930's
0.1%
(5.3%)
5.7%
na
na


1940's
8.9%
3.0%
5.7%
33.6%
64.5%


1950's
18.9%
13.6%
4.7%
72.0%
24.7%


1960's
7.7%
4.4%
3.1%
57.2%
41.0%


1970's
5.8%
1.6%
4.1%
27.8%
71.1%


1980's
17.2%
12.6%
4.1%
73.2%
23.8%


1990's
18.0%
15.3%
2.3%
85.1%
12.9%


2000's
(0.9%)
(2.7%)
1.8%
na
na


2011
2.1%
(0.0%)
2.1%
0.0%
100%


2003-2011
6.2%
4.0%
2.0%
65.8%
32.9%


1930-2011
9.2%
5.1%
3.9%
55.5%
42.4%









Source: Factset, Morgan Stanley Research
Dividend payouts remain low versus history (Exhibit 30), and as we have written in the past, managements are paying themselves more and more in restricted stock units (RSUs) vs. options, which this likely augurs more dividend payout increases over time.
12
Exhibit 30
Dividend Payout Ratios Are Near an All-Time Low






Top 500: Payout Ratio








140%






Through Q2 2012



























120%



















100%



















80%



















60%











Average = 45.5%






















40%



















20%



















0%



















74
76
78
80
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
12
Source: Factset, Morgan Stanley Research
We built a quantitative model to forecast returns within the highest yielding cohort of stocks, dubbed Diva, for Dividend Alpha, and found that we could generate substantial excess return using a disciplined approach (Exhibit 31). To be clear, a high level of yield isn’t what you should exclusively be after. It’s a combination of yield and the prospect of more yield.
Exhibit 31
High Yield Stocks Produce 6% Alpha per Year Net of Beta, Size, Style and Quality
Q1 Dividend Yield Alpha

60%

















50%
















<![if ! IE]>
<![endif]>Alpha
40%
















30%
















<![if ! IE]>
<![endif]>12-Month
















20%
















10%








Average






<![if ! IE]>
<![endif]>Rolling
0%
















(10%)


































(20%)

















(30%)

















79
81
83
85
87
89
91
93
95
97
99
01
03
05
07
09
11
Source: Factset, Morgan Stanley Research
Exhibit 32 shows stocks that are in the top quartile of our Diva model today.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 32
Top-Quartile High Yield Stocks in our Diva Model Include PFE, BMY, and LMT, Among Others
High Yield Alpha Model: Largest Q1 Stocks
As of October 2012



Market Cap
Ticker
Company
Sector
(US$ Bil.)
CVX
Chevron Corp.
Energy
207.2
T
AT&T Inc.
Telecommunication Services
189.5
PFE
Pfizer Inc.
Health Care
180.5
COP
ConocoPhillips
Energy
67.8
BMY
Bristol-Myers Squibb Co.
Health Care
53.0
LLY
Eli Lilly & Co.
Health Care
52.6
LMT
Lockheed Martin Corp.
Industrials
29.1
HPQ
Hewlett-Packard Co.
Information Technology
27.2
EXC
Exelon Corp.
Utilities
27.1
RTN
Raytheon Co.
Industrials
18.2
Source: Factset, Morgan Stanley Research. For important disclosures regarding companies that are the subject of this screen, please see the Morgan Stanley Research Disclosure Website at www.morganstanley.com/researchdisclosures.
Exhibit 33 shows high yielders that screen in the bottom quartile of our outlook today.
Exhibit 33
While the Bottom Quartile Includes MSFT, GE, and
VZ
High Yield Alpha Model: Largest Q4 Stocks
As of October 2012



Market Cap
Ticker
Company
Sector
(US$ Bil.)
MSFT
Microsoft Corp.
Information Technology
242.6
GE
General Electric Co.
Industrials
219.1
VZ
Verizon Communications Inc.
Telecommunication Services
121.6
MCD
McDonald's Corp.
Consumer Discretionary
85.5
SCCO
Southern Copper Corp.
Materials
29.3
WMB
Williams Companies Inc
Energy
20.2
CME
CME Group Inc. Cl A
Financials
18.1
PCAR
Paccar Inc.
Industrials
15.3
NUE
Nucor Corp.
Materials
12.7
TYC
Tyco International Ltd.
Industrials
12.7
Source: Factset, Morgan Stanley Research. For important disclosures regarding companies that are the subject of this screen, please see the Morgan Stanley Research Disclosure Website at www.morganstanley.com/researchdisclosures.
If investors want to create their own custom dividend growth screens please don’t hesitate to contact us, as we can create the screen and back-test it for historical efficacy. One such example of a screen of stocks with potential to grow dividends is shown in Exhibit 34. Here is a list of stocks with:
-Market Cap $2 Billion or Greater
-Dividend Yield Between 1.5% and 6%
-Earnings Retention Ratio 60% or Greater
-EPS Has Grown over the Past Year
-High Cash on the Balance Sheet or High Free Cash Flow
13
Exhibit 34
Our Dividend Growth Screen Includes Stocks With Potential to Grow Their Dividend
Dividend Growth Screen



Market Cap
Ticker
Company
Sector
(US$ Bil.)
IBM
International Business Machines Corp. Information Technology
211.2
QCOM
QUALCOMM Inc.
Information Technology
105.5
UTX
United Technologies Corp.
Industrials
69.0
BA
Boeing Co.
Industrials
53.4
MDT
Medtronic Inc.
Health Care
41.9
TWC
Time Warner Cable Inc.
Consumer Discretionary
27.3
MPC
Marathon Petroleum Corp.
Energy
18.4
RTN
Raytheon Co.
Industrials
18.0
NOC
Northrop Grumman Corp.
Industrials
15.6
MSI
Motorola Solutions Inc.
Information Technology
14.8
CAH
Cardinal Health Inc.
Health Care
13.4
ATVI
Activision Blizzard Inc.
Information Technology
12.3
EMN
Eastman Chemical Co.
Materials
8.5
XRX
Xerox Corp.
Information Technology
7.9
SPLS
Staples Inc.
Consumer Discretionary
7.9
LLL
L-3 Communications Holdings Inc.
Industrials
7.0
FL
Foot Locker Inc
Consumer Discretionary
5.0
HUB.B
Hubbell Inc. Cl B
Industrials
4.2
DNB
Dun & Bradstreet Corp.
Industrials
3.3
LECO
Lincoln Electric Holdings Inc.
Industrials
3.6
HUN
Huntsman Corp.
Materials
3.8
JBL
Jabil Circuit Inc.
Information Technology
3.6
ROC
Rockwood Holdings Inc.
Materials
3.3
IEX
IDEX Corp.
Industrials
3.5
Source: Factset, Morgan Stanley Research. For important disclosures regarding companies that are the subject of this screen, please see the Morgan Stanley Research Disclosure Website at www.morganstanley.com/researchdisclosures.
Theme 3: Microstructure and Mega Caps
We have built a framework to break out the exposure of individual stock returns into systematic (macro) and idiosyncratic (stock-specific) sources of risk (see US Equity Strategy: It’s OK to Admit You’re a Macro Investor, June 19, 2011). Our research shows that for the typical stock, about half of its risk can be explained by a handful of systematic risk exposures: equity beta, size, style and quality exposures (Exhibit 35).
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 35
Macro Factors Explain as Much as Bottom-Up
Fundamentals

Explanatory Power of Equity Characteristic Factor Model for


Stocks: Lowest Quartile, Median and Highest Quartile Cutoffs

70%


1986 Through October 2012











60%








50%








40%








30%








20%

Lowest Quartile





10%

Median







Highest Quartile





0%














86
89
92
95
98
01
04
07
10
Source: Factset, Morgan Stanley Research
Given the outsized effect these “macro” factors have had on individual stock returns, it is not surprising that hedge fund alpha has declined in the past few years, recently turning negative (Exhibit 36).
Exhibit 36
Alpha Generation Has Fallen


Annualized Excess Return of HFRI Equity Hedge Index after




S&P 500, Size, Quality, and Style Factors (Rolling 60 Months)



18%





Jan 1990 - Oct 2012


























16%


















14%


















12%

















<![if ! IE]>
<![endif]>Alpha
10%

















8%

















6%


















4%


















2%


















0%


















(2%)


















(4%)


















95
96
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12








End of 60-Month Period






Source: Factset, Morgan Stanley Research
We wanted to briefly describe our approach for assessing market microstructure and potential disconnects. Please note that we assess the market in detail every month on these factors, the latest report was November 12th, 2012: US Quant Research: Multiple Personality Disorder). The following paragraphs describe how we quantify the size, style and quality macro factors.
Size: We like mega cap stocks. We divide stocks into four cohorts (see US Equity Strategy: Will Mega and Large Caps Remain an Inferior Asset Class, March 20, 2011): mega-, large-, mid- and small-cap, and compute their cap-weighted returns. Larger stocks generally have lower sensitivity to
14
overall market returns; we therefore adjust market-cap cohort returns for their equity market betas. The most recent period has been the best since the Tech Bubble for mega caps, though this faded over the past ten weeks. Mega-caps continue to remain attractively valued (Exhibit 37), and we continue to prefer mega caps as a cohort due to higher cash balances that could benefit from new legislation and generally more achievable estimates. Further, many have higher exposure to faster growing economies, which should make them perform better in a slow growth environment.
Exhibit 37
Mega Caps Remain Attractively Valued vs. the Broader Market





Mega Caps vs. Rest of the Market





2.0x




Median Price-to-Forward Earnings










Through October 2012




















1.8x

















1.6x

















1.4x

















1.2x

















1.0x

















0.8x

















0.6x

















77
79
81
83
85
87
89
91
93
95
97
99
01
03
05
07
09
11
Source: Factset, Morgan Stanley Research
Style: We are no longer making a big growth vs. value bet. We use a proprietary style model that classifies stocks into value, growth and neither buckets (see US Equity Strategy: Do You Have Style? April 23, 2012). Although this model was designed to anticipate Russell style changes, we do not classify stocks as both value and growth; instead, we record performance of this third category separately. We also use equal-weight performance by style class and adjust for market beta and two size risk factors.
Net of beta and market-cap contributions, value stocks recovered nearly an entire year’s worth of performance versus growth stocks during October (Exhibit 38). Over the last few years, risk-adjusted value performance has been more volatile than that of growth or neither.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 38
In October, Value Stocks Erased Almost an Entire
Year of Underperformance




Rolling 12-Month Cumulative Residual Returns



50%

Net of Beta and Two Size Residuals, Through October 2012


40%


Growth














30%


Neither
















Value































20%


















10%


















0%


















(10%)


















(20%)


















(30%)


















75
77
79
81
83
85
87
89
91
93
95
97
99
01
03
05
07
09
11
Source: Factset, Morgan Stanley Research
While we recommended growth over value for 2012, we are more neutral on style heading into 2013, as the penalty for missing on revenue remains harsh and the revenue growth relative to expectations has been weakening over the past six months (Exhibit 39).
Exhibit 39
Revenue Growth Has Been Quite Weak vs. Expectations Over the Past 6 Months
S&P 500 Ex-Fin Quarterly Revenue Surprise (%)
5%









4%









3%









2%









1%









0%









(1)%









(2)%









1Q08
3Q08
1Q09
3Q09
1Q10
3Q10
1Q11
3Q11
1Q12
3Q12
Source: Factset, Morgan Stanley Research
Substance: We prefer quality. We utilize a proprietary model to assign stocks to one of four quality buckets: high quality, moderate quality, low quality and junk (see US Equity Strategy: The Quality / Junk Debate, Jan. 17, 2011). We then compute a quality-junk spread that represents the performance of the high quality stocks over the junk stocks, net of market, size and style exposures (see Exhibit 40). Over 12-month periods, quality usually beats junk, but there are times when junk outperforms by a large margin. Despite the positive market return in 2012, quality has maintained its edge over junk for the past year.
15
What makes junk stocks typically outperform is when cost of capital is high and sharply declines. We are not in this environment today, as few stocks are discounting a high probability of bankruptcy today. Therefore, few low quality stocks should massively rally (as many did in March 2009) as a result of capital-related market changes. In this case, junk equities likely only work as a cohort if the economy accelerates dramatically, and that is certainly not the forecast of our global economics team, which has GDP growing at just a 3.1% pace in 2013, well below the 3.7% long-term trend and flat versus 2012 growth, which was the lowest rate in five years.
Exhibit 40
Quality Has Outperformed Junk – We Remain Positively Biased toward Quality


Rolling 12-Month Annualized Residual Return Spread


50%



Between Q1 (Quality) and Q4 (Junk),








Through Oct 2012





40%






















30%


Quality Outperforms







20%













10%













0%













(10%)













(20%)



Junk Outperforms







(30%)























(40%)













86
88
90
92
94
96
98
00
02
04
06
08
10
12
Source: Factset, Morgan Stanley Research
Cyclicals: We are recommending a barbell. We classify industries as cyclical, defensive or neither using a proprietary, dynamic model (see US Equity Strategy: Cyclicals or Defensives? February 26, 2012). We compute cap-weighted returns of stocks within these industries and adjust for beta (as cyclicals are higher-beta).
Cyclicals had lagged so thoroughly that October was their best beta-adjusted performance since October 2011 (Exhibit 41) and this was during a month where the stock market was down! Our view is that while many cyclicals have weak fundamentals now, the dream of improvement is alluring to PMs, who are more wary of owning expensive defensives or faltering growth. (Please see October 22nd, 2012: US Equity Strategy: Door No. 3 for our forecast of this cyclical rotation). We are recommending some balance here, wanting some exposure to China and therefore some cyclical exposure. But we also want yield and growth of yield, which argues for some defensives.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 41
Cyclicals Had their Best Beta-Adjusted Performance Relative to Defensives since October 2011

Cyclicals vs Defensives Return Residuals,
4.0%
As of October 2012

3.0%








2.0%








1.0%








0.0%








(1.0%)








(2.0%)








(3.0%)








May-11
Jul-11
Sep-11
Nov-11
Jan-12
Mar-12
May-12
Jul-12
Sep-12
Source: Factset, Morgan Stanley Research
Morgan Stanley Alpha Models
The skeleton of our strategy product is a set of quantitative models that forecast subsequent stock performance. We have published many times that we have ample empirical evidence that fundamental research combined with quantitative models produces superior return. 2012 has been no exception.
Our three-month alpha model (MOST) and our 2-year relative return model (BEST) continued to perform strongly in October (Exhibit 42) despite the diverse and differing group of factors that were effective last month. Although BEST has a value bias due to its long horizon, we have stripped off last month’s value outperformance in presenting alpha model results. In our judgment, this highlights why using a balanced or “optimal” alpha model is consistently more effective than making a single factor bet as a portfolio manager. Why would you make a single bet, e.g., on free cash flow or dividend growth, when an optimal framework consistently generates superior results over any meaningful period of time? We continue to believe portfolio management that uses a combination of fundamental research and quantitative tools offers superior results.
16
Exhibit 42
Morgan Stanley’s Alpha Models Produced Positive Alpha in October – and Over the Last Year
Alpha Models Return Residuals,
As of October 2012
9%
8%
MOST



7%



BEST



6%



Synergy



5%







4%




3%




2%




1%




0%




(1%)





Last Month
Last 3 Months
Last 6 Months
Last 12 Months
Source: Factset, Morgan Stanley Research
Part III: Sector Bets and Stock Selection
In this year-ahead outlook, we have made several sector and portfolio changes.
Our new sector recommendations are shown below in Exhibit 43.
1)We have upgraded industrials from market-weight to overweight and downgraded technology from overweight to market-weight.
2)We have downgraded financials from market-weight to underweight.
3)We have downgraded staples from market-weight to underweight, remaining overweight health care.
4)We have upgraded energy from underweight to market-weight.
Our portfolio changes are generally skewed toward the three themes we identified in the second part of this note – more China, more cash and dividend growth exposure, and a retained bias toward mega caps and quality where possible.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 43
We Are Overweight Health Care and Industrials, and
Underweight Discretionary, Staples, and Financials
4%


Morgan Stanley Sector Recommendations


3%



As of November 2012














2%










1%










0%










(1%)










(2%)
Overweights - Health Care, Industrials






(3%)
Market-Weights - Utilities, Technology, Materials, Telecoms, Energy


Underweights - Discretionary, Staples, Financials




(4%)
<![if ! IE]>
<![endif]>Health Care
<![if ! IE]>
<![endif]>Industrials
<![if ! IE]>
<![endif]>Utilities
<![if ! IE]>
<![endif]>Technology
<![if ! IE]>
<![endif]>Materials
<![if ! IE]>
<![endif]>Telecoms
<![if ! IE]>
<![endif]>Energy
<![if ! IE]>
<![endif]>Discretionary
<![if ! IE]>
<![endif]>Staples
<![if ! IE]>
<![endif]>Financials

Source: Factset, Morgan Stanley Research
Exhibit 44 shows the current sector decomposition of the S&P500. Many investors are surprised that financials are 15% of the S&P500 and remain the second largest sector by market capitalization, assuming it had become smaller than other sectors in the recent crisis. We think over the next few years it is likely that industrials and energy gain share of the total pie within the S&P500, and we have less confidence that financials will, and so our recent sector changes are more in-line with this structural view.
Exhibit 44
Technology, Financials, and Health Care Account for Nearly Half of the S&P 500’s Market Cap

S&P 500 Sector Weights
25%
As of November 2012

20%
19.1%



















15%

15.1%










12.2%
11.2%
11.1%
10.9%




10%


10.1%













5%







3.5%
3.5%
3.1%
0%
<![if ! IE]>
<![endif]>Technology
<![if ! IE]>
<![endif]>Financials
<![if ! IE]>
<![endif]>Health Care
<![if ! IE]>
<![endif]>Discretionary
<![if ! IE]>
<![endif]>Energy
<![if ! IE]>
<![endif]>Staples
<![if ! IE]>
<![endif]>Industrials
<![if ! IE]>
<![endif]>Materials
<![if ! IE]>
<![endif]>Utilities
<![if ! IE]>
<![endif]>Telecom

Source: Factset, Morgan Stanley Research
17
Change 1: Upgrading Industrials and Downgrading
Technology
For much of the past decade, machinery and technology hardware have both exhibited a rising sensitivity to the Chinese stock market (Exhibit 45). In recent months, machinery stocks’ sensitivity to China has inched higher than that of tech hardware, and thus machinery names would appear to be better positioned than technology hardware, for example, to benefit from a rebound in the Chinese economy. This is consistent with increasing industrials exposure relative to technology.
Exhibit 45
Machinery’s Sensitivity to Chinese Equities Has Recently Surpassed Tech Hardware
Sensitivity of Returns to Shanghai Composite Index (Ex. AAPL), Rolling 36-Month Periods
Through October 2012
1.0












0.8












0.6

Machinery
Tech Hardware






0.4












0.2












0.0












(0.2)












(0.4)












00
01
02
03
04
05
06
07
08
09
10
11
12
Source: Factset, Morgan Stanley Research
Since the collapse of the technology bubble a decade ago, there have been multiple periods where technology has outperformed industrials, and vice versa. For much of the past year, technology has outperformed industrials, but the relative performance has recently started to swing back in the favor of the industrials (Exhibit 46). Typically when this occurs, it lasts for several months, and it appears we are in the beginning phase of this now.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 46
It Appears Industrials Have Started a Multi-Month Period of Outperformance vs. Technology








Relative Returns - Industrials vs Technology













80%



(Ex. AAPL, GE and defense stocks), Rolling 12-Month Periods























Through October 2012



























































































60%































Industrials Outperform




40%





















































































20%


















































0%


















































(20%)




































































































(40%)


















































































Technology Outperforms
































(60%)




































































































01
02
03
04
05
06
07
08
09

10


11

12

Source: Factset, Morgan Stanley Research
During the Q3 earnings season, technology stocks were punished for earnings misses more dramatically than capital goods were punished (Exhibit 47). Our upgrade of industrials from underweight to market-weight in mid-October was in part predicated on anticipating this asymmetry would unfold. We want to own stocks that don’t go down very much when they miss but could go up a lot if news gets better, and many names in the multi-industry conglomerates and machinery industry fit that bill.
Exhibit 47
Capital Goods Stocks Didn’t Go Down Much When They Missed During EPS Season, and Likely Go Up If Fundamentals Begin to Improve
Reporting Day Median Relative Perf Post 3Q12 Earnings Miss
Tech Hardware vs. Cap Goods Ex Defense
Tech H/W
Cap Goods Ex
Defense
(3.8)%
(3.7)%
(3.6)%
(3.5)%
(3.4)%
(3.3)%
(3.2)%
(3.1)%
Source: Factset, Morgan Stanley Research
We have added DHR and increased our position in HON to achieve this overweight. We now hold HON, DHR, CAT, EMR, UTX, URS, and GD as our industrial positions, with a 13% portfolio weight vs. the benchmark of 10%.
18
We do not view our downgrade of technology as a structurally bearish stance. We have toggled between market-weight and overweight technology for much of the past two years, and this generally positive bias has by and large been correct.
Strategists generally like technology because many of the stocks are cheaper than the market, grow faster than the market, and have better balance sheets. Moreover, under tax reform or repatriation this group will likely be the primary beneficiary. The challenge we have is that in the aggregate the sector looks attractive, but there are many individual names that appear to be in businesses in structural decline. Our SWEEP algorithm indicates that the consensus technology earnings estimates for 2013 are among the most optimistic of any sector. PC hardware and PC semiconductors, printing, servers, big box retailing, fixed line telephony are among the many businesses that appear structurally challenged. So certain stocks like HPQ appear super cheap and make the aggregate technology sector look more attractive than it might be without the huge company-specific risk and obsolescence, which seem even more important than normal in the technology sector. For the time being, we think the beta in industrials is more attractive than the beta in technology (Exhibit 48).
Exhibit 48
Industrials Sector Beta Is Cheap Compared to the Beta in Technology
Price-to-Forward Earnings
High Beta of Industrials vs. High BetaTechnology

1.20


















<![if ! IE]>
<![endif]>Earnings
1.00


















0.80





































<![if ! IE]>
<![endif]>Price-to-Fwd.
0.60


















0.40


















0.20






































0.00



















76
78
80
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
12
Source: Factset, Morgan Stanley Research
In the end, our technology exposure remains skewed toward high-quality mega caps with large cash balances that would benefit from tax reform or repatriation (19% out of the 20% in our portfolio is in MSFT, AAPL, ORCL, ACN, CSCO, EMC, and MA). We removed the single worst performing stock from our portfolio, WU, this week, to reduce our technology exposure.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Change 2: Downgrading Financials to Underweight
A bottom-up assessment of the financial sector in 2013 (Exhibit 49) shows that BAC is expected to provide over one-third of the sector’s growth by itself. This may prove to be correct given ongoing expense reductions, and BAC was able to massively expand its operating profit growth in 2012 vs. 2011. The reason we mention it is because, in large part, estimate achievability for the sector becomes a call on BAC’s performance.
Exhibit 49
BAC Is Forecasted to be 33% of the Financial Sector’s EPS Growth in 2013
Top Contributors to Financials 2013 YoY Earnings Growth,
As of November 23, 2012



% Growth



Contribution To
Ticker
Company
Sector
Financials (2013E)
BAC
Bank of America Corp.
Diversified Financials
33.3%
WFC
Wells Fargo & Co.
Banks
7.1%
C
Citigroup Inc.
Diversified Financials
6.3%
JPM
JPMorgan Chase & Co.
Diversified Financials
5.0%
PRU
Prudential Financial Inc.
Insurance
4.1%
BRK.B
Berkshire Hathaway Inc. Cl B
Insurance
3.6%
GS
Goldman Sachs Group Inc.
Diversified Financials
2.4%
PNC
PNC Financial Services Group Inc.
Banks
1.9%
AXP
American Express Co.
Diversified Financials
1.9%
L
Loews Corp.
Insurance
1.8%
Source: Factset, Morgan Stanley Research
Our SWEEP algorithm for EPS shows the sector EPS might be achievable, but obviously it is difficult to factor in loan growth, mortgage origination, net interest margin (NIM) expansion from the slope and level of the curve, and other micro variables that impact the sector’s profitability. We have been market-weight financials this year, preferring P&C insurers and more recently asset managers to mid-cap banks, and essentially neutral large-cap banks with positions in JPM and PNC. We should have been more optimistic on the sector, as financials, up over 21% year-to-date, have been the best performing sector in the market this year. Recently, there has been a trend where investors sell the previous year’s winners for the previous laggards early in the year, and this could set up financials for underperformance early in 2013. Over the past three years, the best performing sector ended up being on average the second worst over the first month and third worst after three months in the new year (Exhibit 50).
19
Exhibit 50
The Best Performing Sector in a Given Year Tends to Be Among the Worst Sectors the First Three Months of the Next Year
Rank out of 10 Sectors of Best Performing Sector During Calendar
Year in Subsequent 1 and 3-Months
Last 3 Years

0



1


<![if ! IE]>
<![endif]>10
2


<![if ! IE]>
<![endif]>of
3


<![if ! IE]>
<![endif]>Out
4


<![if ! IE]>
<![endif]>Rank
5


6


<![if ! IE]>
<![endif]>Sector


7


8

7.3

9
9.0


10






1-Month
3-Month
Source: Factset, Morgan Stanley Research
Generally, we have a bias toward owning quality stocks, as we outlined in the second section of this note. However, the percentage of high-quality financial stocks remains at incredibly low levels (Exhibit 51). This is to say, investors who want stable and growing ROEs and earnings can find this in other sectors much more than they can in financials.
Exhibit 51
The Percentage of High-Quality Financial Stocks
Has Fallen Since the Financial Crisis
Top 1500 US Stocks: Financials Percentage of
High Quality Stocks, Through October 2012
45%
















40%
















35%
















30%
















25%
















20%
















15%
















10%
















5%
















0%
















80
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
12
Source: Factset, Morgan Stanley Research
It is difficult to gauge fundamentals, but it does appear, at least in the near term, that the year-over-year growth in loans and leases (Exhibit 52) is moderating.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 52
Loan Growth Appears to Be Decelerating


Total Loans & Leases Y/Y Growth


15%


Through October 2012



10%







5%







0%







(5%)







(10%)







(15%)







05
06
07
08
09
10
11
12
Source: Factset, Morgan Stanley Research
Matthew Hornbach, Morgan Stanley’s US Interest Rate Strategist, expects US Treasury yields to rise and the yield curve to steepen next year. This yield combination has historically been a headwind to financial sector performance (Exhibit 53), though we admit that any historical equity market playbooks for rates are likely completely messed up by unconventional policy. Our view is actually that there will be more quantitative easing, and that NIMs will stay under pressure for some time with the 10-year yield remaining at quite low levels.
Exhibit 53
A Rising and Steepening Yield Curve Was Historically a Negative for Financials

Performance of Financials During Different Interest Rate

Environments: 12-Month Return Spread
3%
1969 - October 2012
2%
1%
0%
(1%)
(2%)
(3%)
Falling & Flattening
Falling &
Rising & Flattening
Rising &

Steepening

Steepening
Source: Factset, Morgan Stanley Research
Multiples for the sector typically exponentially expand when ROEs expand (Exhibit 54).
20
Exhibit 54
In Financials, ROE Expanders Are Multiple
Expanders


Financials Quarterly ROE and Price-to-Book Value:


3.0x

1984 Through Q2 2012








2.5x




<![if ! IE]>
<![endif]>-to-Book
2.0x




1.5x









<![if ! IE]>
<![endif]>Price
1.0x





0.5x





0.0x





0%
5%
10%
15%
20%



Return on Equity


Source: Factset, Morgan Stanley Research
But, most analysts are cautious on ROE expansion over the next few quarters. ROEs remain quite low (Exhibit 55) and headlines from major banks continue to show massive headcount reductions and management shake-ups, typical signs that current fundamentals are not particularly strong. The specter of more regulation is also a clear negative. One positive we have observed, however, following strong performance of banks this year, is that the investor debate has shifted in general from balance sheets to income statements. We think this is what caused the re-rating in the group from the middle of the year over the summer. The bad news is that focus on the income statements isn’t likely to generate massive incremental optimism.
Exhibit 55
Financials’ ROE Is At Historical Lows
Financials (ex Real Estate) Valuation & Profitability

3.5x

















25%


3.0x

















20%





















<![if ! IE]>
<![endif]>Price-to-Book
2.5x



















2.0x











nbsp;





15%
<![if ! IE]>
<![endif]>Fwd ROE


















1.5x

















10%






































1.0x




















0.5x









Price-to-Book (LHA)


5%

























ROE (RHA)
























0.0x

















0%


76
78
80
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
12

Source: Factset, Morgan Stanley Research
Estimate dispersion among financials has come down significantly since the financial crisis but it remains elevated, higher than at any time between 2000 and 2008 (Exhibit 56). Analysts just don’t really know what the sector is going to earn,
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
and historically wide dispersion in forecasted earnings estimates is a subsequent negative. The trend is clearly better, but it does seem from talking to investors that they are getting increasingly less confident about the medium-term trajectory of earnings for the group.
Exhibit 56
Dispersion Has Come Down Sharply from the Peak, But Remains Elevated by Historical Standards
Financials (ex Real Estate) Estimate Dispersion

0.10


Financials































0.08


Banks & Diversified Financials









<![if ! IE]>
<![endif]>Dispersion


Insurance





























0.06





































<![if ! IE]>
<![endif]>Estimate
0.04


















0.02






































0.00



















76
78
80
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
12
Source: Factset, Morgan Stanley Research
Some investors have recently said to us that they think financials should be a fertile sector for long-short investing, believing that there should be some clear winners and losers over the coming few years. That may well be true, but within the financials sector, the explanatory power of macro factors is historically high (Exhibit 57), meaning that alpha opportunities will have to come from a smaller piece of pie than ever, as the market and major macro calls will explain more and more of total return.
Exhibit 57
Alpha Opportunities among Financials Are at an All Time Low


Explanatory Power for Equity Factor Model






Financials Stocks



60%


1986 Through Oct 2012



55%








50%








45%








40%








35%








30%








25%








20%








86
89
92
95
98
01
04
07
10
Source: Factset, Morgan Stanley Research
21
Our portfolio exposure to financials is now 12%, versus the S&P500 benchmark of 15.2%. We remain overweight P&C insurers, but have modestly reduced exposure to TRV based on strong price performance. Our portfolio consists of ACE, RNR, CB, and TRV. We trimmed our positions in JPM and PNC. We own BEN for dividend (see unsurprising recent one-time dividend announcement) and solid near-term fundamentals.
Change 3: Downgrading Consumer Staples to Underweight, Remaining Overweight Health Care
Normally when someone is somewhat cautious on the market outlook, consumer staples becomes a preferred sector. However, in discussing sectors with our equity strategy colleagues in both Europe and Asia, there is a consistent view that the consumer staples have become relatively unattractive on valuation (Exhibit 58).
Exhibit 58
The Consumer Staples Sector Trades at a Premium to the Market



Top 1500 Staples Price-to-Forward Earnings





1.4x





Relative to the Market







1.3x





Through October 2012

























1.2x


















1.1x











Average




1.0x


















0.9x


















0.8x


















0.7x


















0.6x


















76
78
80
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
12
Source: Factset, Morgan Stanley Research
On the defensive side of the barbell, we continue to prefer health care to consumer staples. First, estimates in health care appear to be more achievable than those in staples (Exhibit 59). Many investors have commented to us over the last two earnings seasons that they are frustrated owning expensive defensive stocks that somehow are still missing estimates.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 59
Staples Estimate Achievability Appears Worse than Health Care - A Potential Problem with Valuation Relatively Unattractive

Actual vs Expected Total Earnings
12%
Through Q3 2012

Consumer Staples
10%
Health Care
8%
6%
4%
2%
0%
(2%)
(4%)
04
05
06
07
08
09
10
11
12
Source: Factset, Morgan Stanley Research
Furthermore, staples trades at a premium to health care on forward earnings (Exhibit 60) and generates less free cash flow than do the health care names (Exhibit 61).
Exhibit 60
Staples Is Expensive Compared to Health Care



Price-to-Forward Earnings: Health Care vs Staples




1.8x





Through October 2012

























1.6x







Staples Cheap






















1.4x


















1.2x













Average




















1.0x


















0.8x











Health Care Cheap
















0.6x


















76
78
80
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
12
Source: Factset, Morgan Stanley Research
22
Exhibit 61
Health Care Generates More Free Cash Flow Compared to Staples


Relative Free Cash Flow Yield: Health Care Less Staples


5%



P class="p9 ft11"> 

Through October 2012



















4%














3%














2%














1%














0%














(1%)














(2%)














(3%)














(4%)














83
85
87
89
91
93
95
97
99
01
03
05
07
09
11

Source: Factset, Morgan Stanley Research
Lastly, the stocks in the health care space carry more cash on their balance sheets (as a fraction of market cap, see Exhibit 62) than do staples names, indicating the potential for higher yields in health care and perhaps more benefit from tax reform or a grand bargain that includes repatriation.
Exhibit 62
Consumer Staples Have Less Cash to Distribute Than Health Care
Cash-to-Market Capitalization
Through Q2 2012
20%














18%

Consumer Staples










16%

Health Care











14%














12%














10%














8%














6%














4%














2%














0%














69
72
75
78
81
84
87
90
93
96
99
02
05
08
11
Source: Factset, Morgan Stanley Research
We removed LO and TFM from our staples holdings, and now have remaining positions in COST, KRFT / MDLZ, PM, and CL. Health care is our largest overweight. Stocks in our portfolio include pharmaceuticals and distribution. ABC, MCK, CAH, BMY, PFE, SYK, and COV are the health care names we have held. We have added A to the portfolio to increase China exposure.
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Change 4: Upgrading Energy to Market-weight from Underweight
Energy has been the 2nd worst performing sector over the last month, and we now think it is time to move back toward a neutral bet on the group. We are adding KMI and MWE, to increase our dividend yield and exposure to laggards. The consensus view among investors appears to be to prefer natural gas to oil in the near term. We don’t see why oil will materially rise from improving demand, so supply fear is the biggest potential driver of higher oil. Historically, as in the Arab Spring, this was accompanied by risk-off trading and a crowding into the integrateds. But CVX and XOM have performed well, and we don’t see generalist PMs moving aggressively into stocks they think discount a higher oil price than nearly any other part of the sector. As such, we don’t want to make an aggressive bet on energy today.
Other: We made a few other tweaks to the portfolio consistent with our big three themes for the year. We added GM to consumer discretionary (China), DUK to utilities (big Latin American property has created non-US domiciled cash), and CCI to play the wireless infrastructure theme.
Portfolio
Our overweight sectors are health care and industrials. We are recommending underweights in consumer discretionary, staples, and financials (Exhibit 43). Today, we are removing
LO, TFM, and WU from our portfolio, while adding GM, KMI, MWE, DHR, CCI, DUK, and A.
Since inception in early 2011, our portfolio has outperformed the S&P 500 by 360 basis points (Exhibit 63).
We view the portfolio as “Core” more than “Growth or Value” as our analyst recommendations and quantitative frameworks are ostensibly style neutral.
23
Exhibit 63
The MOST Strategic Portfolio Outperformed the S&P 500 (Total Return) by 360 bps Since Inception
MOST Strategic Portfolio Performance
December 31, 2010 to November 23, 2012
25.0%


20.0%
19.9%



16.3%


15.0%


10.0%


5.0%

3.6%
0.0%


S&P
Portfolio
Relative Performance
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Our portfolio is slightly cheaper than the market on book value and forward earnings and has a low beta and higher market cap bias compared to the market (Exhibit 64). Our sector changes and stock additions / deletions did not change our portfolio beta, which remains exactly at 1.0.
Source: Morgan Stanley Research. Past performance is no guarantee of future returns.
Performance includes dividends but excludes transaction costs.
Exhibit 64
Our Portfolio Has a Large-Cap Bias, And Our Changes Did NOT Change the Portfolio Beta
Updated and Existing MOST Strategic Portfolios vs S&P 500 as of End-October, 2012






Updated vs.
Updated




Existing
Updated

Existing
Portfolio vs.



Factor
Portfolio
Portfolio
Benchmark
Portfolio
Benchmark



Price-to-Book
2.0x
2.1x
2.1x
1.0x
1.0x



Price-to-Fwd. Earnings
11.7x
12.0x
12.8x
1.0x
0.9x



Price-to-Sales
0.8x
0.7x
1.3x
0.9x
0.6x



Price-to-Oper. Cash flow
9.5x
9.4x
9.1x
1.0x
1.0x


Valuation
EV-to-EBIT
9.9x
10.0x
11.0x
1.0x
0.9x



EV-to-Free Cash Flow
22.4x
23.6x
26.1x
1.1x
0.9x



Dividend Yield
2.5%
2.4%
2.4%
(0.1%)
(0.0%)



Total Yield
4.3%
5.3%
4.9%
1.0%
0.4%



Free Cash Flow Yield
4.2%
3.8%
3.6%
(0.3%)
0.2%



Total Cash-to-Market Capitalization
11.7%
13.1%
11.2%
1.3%
1.9%



Capex-to-Sales
5.7%
6.3%
8.2%
0.6%
(1.9%)


Capital Use
Accruals
3.4%
4.5%
36.2%
1.1%
(31.7%)


and
Incremental Margin
12.0%
12.2%
14.0%
0.2%
(1.8%)


Profitability
Asset Turnover
1.2x
1.2x
0.9x
1.0x
1.3x



Gross Margin
37.3%
36.0%
41.6%
(1.3%)
(5.6%)



Changes in Shares Outstanding
(1.1%)
(1.3%)
1.6%
(0.1%)
(2.9%)



9-Month Price Momentum
8.9%
9.4%
12.3%
0.5%
(2.9%)


Growth and
3-Month Smoothed Earnings Revisions
0.6%
0.4%
0.5%
(0.2%)
(0.1%)


Investor
Up-to-Down Revisions
(6.6%)
(6.4%)
(0.1%)
0.1%
(6.4%)


Sentiment
Sales Stability
11.9%
12.4%
106.9%
0.5%
(94.4%)



Beta
1.00
1.00
1.02
1.0x
1.0x


Size
Market Cap
64,371
63,526
26,841
1.0x
2.4x










Source: Factset, Morgan Stanley Research
24
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Our sector bets in the health care and energy sectors have contributed to performance (Exhibit 65). Stock selection in materials, discretionary, and staples has also helped offset poor industrials, financials, and energy stock picks. The full portfolio is shown in Exhibit 66. For those interested in our quantitative output, please go to www.morganstanley.com/equitystrategy and use the alpha
Exhibit 65
screener product for output from our 3-month model (MOST) and our 24-month model (BEST). A video tutorial is available there, or we or your Morgan Stanley salesperson can give you a brief demonstration.
Our Sector Bet in Health Care Has Helped Drive Outperformance
MOST Strategic Portfolio Performance Attribution December 31, 2010 to November 23, 2012



Portfolio




S&P 500

Sector
Stock



Relative
Sector
Sector
Relative


Sector
Sector
Relative


Sector
Weight
Weight
Return
Return


Weight
Return
Return
Allocation
Selection
Total

Overweight
6.7%
29.0%
19.4%
(1.9%)
22.3%
21.3%
5.0%
0.8%
(0.3%)
0.5%

Health Care
3.7%
16.0%
34.4%
5.0%
12.3%
29.4%
13.1%
0.5%
0.6%
1.2%

Industrials
3.0%
13.0%
0.8%
(10.5%)
10.0%
11.4%
(4.9%)
0.3%
(0.9%)
(0.7%)















Market-Weights
1.8%
42.0%
27.3%
6.5%
40.2%
20.8%
4.5%
0.7%
1.1%
1.8%

Utilities
1.5%
5.0%
32.2%
16.2%
3.5%
16.1%
(0.2%)
0.2%
0.9%
1.1%

Information Technology
1.0%
20.0%
14.5%
(2.1%)
19.0%
16.6%
0.3%
(0.1%)
(0.4%)
(0.5%)

Materials
0.5%
4.0%
86.5%
86.7%
3.5%
(0.2%)
(16.5%)
0.0%
2.2%
2.2%

Telecommunication Services
(0.1%)
3.0%
(4.6%)
(25.6%)
3.1%
21.0%
4.7%
(0.3%)
(0.4%)
(0.7%)

Energy
(1.1%)
10.0%
1.6%
(9.4%)
11.1%
11.0%
(5.3%)
0.7%
(1.1%)
(0.4%)















Underweights
(8.4%)
29.0%
13.5%
3.2%
37.4%
10.3%
(6.0%)
(0.6%)
1.9%
1.3%

Consumer Discretionary
(2.3%)
9.0%
44.8%
15.4%
11.3%
29.4%
13.1%
(0.4%)
1.0%
0.6%

Consumer Staples
(3.0%)
8.0%
43.3%
18.1%
11.0%
25.2%
9.0%
(0.1%)
1.6%
1.5%

Financials
(3.1%)
12.0%
(1.1%)
(4.5%)
15.1%
3.5%
(12.8%)
(0.1%)
(0.8%)
(0.8%)















Total
0.0%
100.0%
19.9%

100.0%
16.3%

0.8%
2.7%
3.6%
Source: Factset, Morgan Stanley Research












--------------------------------------------------------------------------------
Morgan Stanley is acting as a financial advisor to Pfizer Inc. ("Pfizer") in relation to its review of strategic alternatives for its Nutrition business. Pfizer will pay fees to Morgan Stanley for its services, including transaction fees that will be subject to the consummation of any resulting transaction. Please refer to the notes at the end of the report.
Morgan Stanley is acting as sole financial adviser to PSA Peugeot Citroen SA ("Peugeot") in relation to their strategic alliance with General Motors Co., as announced on February 29, 2012. The proposed acquisition is subject to requisite regulatory approvals and other customary closing conditions. Peugeot has agreed to pay fees to Morgan Stanley for its financial services that are contingent upon the consummation of the proposed transaction. Please refer to the notes at the end of the report.
Morgan Stanley is acting as financial advisor to General Motors Co. ("GM") in connection with the offer to provide select GM U.S salaried retirees a lump-sum payment and other retirees with a continued monthly payment securely administered and paid by The Prudential Insurance Company of America, a Prudential Financial Inc. company, as announced June 1, 2012.
The transactions are subject to regulatory review. GM has agreed to pay fees to Morgan Stanley for its financial services. Please refer to the notes at the end of the report.
25
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Exhibit 66
The MOST Strategic Portfolio With Fundamental Analyst Recommendations and MOST Alpha Rankings



Weight


Price
Inclusion
MOST
MS Analyst

Ticker
Company
S&P 500
Portfolio

Latest
Inclusion
Date
Quintile
Rating











Consumer Discretionary


11.4%
9.0%






Hotels Restaurants & Leisure
YUM
Yum! Brands Inc.

2.00%
74.00
49.05
12/31/2010
Q1
Overweight
Media
CBS
CBS Corp (Cl B)

2.00%
35.85
19.05
12/31/2010
Q2
Overweight
Hotels Restaurants & Leisure
MCD
McDonald's Corp.

2.00%
87.05
76.76
1/1/2011
Q2
Equal-Weight
Automobiles
GM
General Motors Co.

2.00%
25.21
25.21
11/23/2012
Q2
Overweight
Multiline Retail
TGT
Target Corp.

1.00%
64.48
51.22
12/30/2011
Q1
Overweight
Consumer Staples


11.0%
8.0%





Food & Staples Retailing
COST
Costco Wholesale Corp.

3.00%
97.92
72.21
12/31/2010
Q1
Overweight
Food Products
KRFT
Kraft Foods Group Inc.

0.70%
45.28
-
12/31/2010
NA
Equal-Weight
Food Products
MDLZ
Mondelez International Inc. Cl A

1.30%
25.62
20.62
12/31/2010
NA
Overweight
Tobacco
PM
Philip Morris International Inc.

2.00%
90.41
58.53
12/31/2010
Q2
Overweight
Household Products
CL
Colgate-Palmolive Co.

1.00%
108.00
88.92
9/23/2011
Q3
Overweight
Energy


11.1%
10.0%





Integrated Oil & Gas
HES
Hess Corp.

1.00%
51.12
43.29
7/13/2012
Q1
Overweight
Integrated Oil & Gas
CVX
Chevron Corp.

3.00%
105.47
91.25
12/31/2010
Q4
Overweight
Oil & Gas Storage & Transportation
KMI
Kinder Morgan Inc.

1.00%
33.72
33.72
11/23/2012
Q1
Overweight
Oil & Gas Storage & Transportation
MWE
MarkWest Energy Partners L.P.

1.00%
50.84
50.84
11/23/2012
NA
Overweight
Oil & Gas Equipment & Services
SLB
Schlumberger Ltd.

2.00%
71.18
83.50
12/31/2010
Q2
Overweight
Oil & Gas Storage & Transportation
WMB
Williams Companies Inc

2.00%
33.44
32.70
5/4/2012
Q2
Overweight
Financials


15.1%
12.0%





Insurance
ACE
ACE Ltd.

1.00%
79.80
64.31
6/17/2011
Q4
Overweight
Commercial Banks
PNC
PNC Financial Services Group Inc.

1.00%
55.75
60.83
1/21/2011
Q1
Overweight
Insurance
RNR
RenaissanceRe Holdings Ltd.

2.00%
81.32
71.25
7/8/2011
Q3
Overweight
Insurance
CB
Chubb Corp.

2.00%
77.23
57.89
9/23/2011
Q5
Overweight
Insurance
TRV
Travelers Cos. Inc.

1.00%
71.27
59.80
4/15/2011
Q5
Equal-Weight
Diversified Financial Services
JPM
JPMorgan Chase & Co.

3.00%
41.09
42.42
12/31/2010
Q1
Overweight
Capital Markets
BEN
Franklin Resources Inc.

2.00%
133.18
117.57
5/4/2012
Q1
Equal-Weight
Health Care


12.2%
16.0%





Health Care Providers & Services
ABC
AmerisourceBergen Corp.

3.00%
41.38
34.12
12/31/2010
Q2
Equal-Weight
Pharmaceuticals
BMY
Bristol-Myers Squibb Co.

2.00%
32.62
29.12
7/8/2011
Q2
Equal-Weight
Health Care Providers & Services
MCK
McKesson Corp.

2.00%
94.11
77.74
2/4/2011
Q2
Equal-Weight
Life Sciences Tools & Services
A
Agilent Technologies Inc.

1.00%
36.88
36.88
11/23/2012
Q2
Overweight
Health Care Providers & Services
CAH
Cardinal Health Inc.

3.00%
39.99
38.31
12/31/2010
Q1
Overweight
Health Care Equipment & Supplies
COV
Covidien PLC

1.00%
57.42
52.50
6/17/2011
Q3
Overweight
Health Care Equipment & Supplies
SYK
Stryker Corp.

1.00%
54.52
56.29
9/21/2012
Q2
Overweight
Pharmaceuticals
PFE
Pfizer Inc.

3.00%
24.53
18.15
9/16/2011
Q2
Overweight
Industrials


10.0%
13.0%





Construction & Engineering
URS
URS Corp.

2.00%
35.49
41.61
12/31/2010
Q1
NC
Aerospace & Defense
HON
Honeywell International Inc.

3.00%
61.26
61.72
9/17/2012
Q2
Overweight
Aerospace & Defense
GD
General Dynamics Corp.

2.00%
65.41
60.60
9/16/2011
Q1
Equal-Weight
Industrial Conglomerates
DHR
Danaher Corp.

1.00%
53.49
53.49
11/23/2012
Q3
Overweight
Machinery
CAT
Caterpillar Inc.

1.00%
84.16
83.86
10/19/2012
Q5
Overweight
Electrical Equipment
EMR
Emerson Electric Co.

1.00%
49.12
48.25
10/19/2012
Q3
Overweight
Aerospace & Defense
UTX
United Technologies Corp.

3.00%
78.61
78.85
12/30/2010
Q3
Overweight
Information Technology


19.1%
20.0%





Software
MSFT
Microsoft Corp.

2.00%
27.70
27.91
12/31/2010
Q2
Overweight
Computers & Peripherals
AAPL
Apple Inc.

4.00%
571.50
422.40
1/6/2012
Q5
Overweight
Software
ORCL
Oracle Corp.

2.00%
30.92
31.19
6/17/2011
Q2
Overweight
IT Services
ACN
Accenture PLC

1.00%
68.18
65.60
9/17/2012
Q1
Overweight
Computers & Peripherals
EMC
EMC Corp.

3.00%
24.81
22.90
12/31/2010
Q4
Overweight
Communications Equipment
CSCO
Cisco Systems Inc.

4.00%
18.84
19.31
1/17/2012
Q3
Overweight
IT Services
MA
MasterCard Inc. Cl A

3.00%
481.24
345.97
1/17/2012
Q3
NA
Semiconductors
CAVM
Cavium Inc.

1.00%
32.56
32.14
1/17/2012
Q5
NA
Materials


3.5%
4.0%





Chemicals
LYB
LyondellBasell Industries N.V. Cl A

1.00%
48.62
34.50
10/28/2011
Q2
Overweight
Chemicals
CHMT
Chemtura Corp.

1.00%
19.62
15.70
10/12/2012
Q5
NA
Chemicals
DOW
Dow Chemical Co.

1.00%
29.38
33.42
4/5/2012
Q2
Equal-Weight
Chemicals
MON
Monsanto Co.

1.00%
90.58
79.02
4/5/2012
Q2
Overweight

Telecommunication Services

3.1%
3.0%







Diversified Telecommunication Services
T
AT&T Inc.
2.00%
34.36
29.38
12/31/2010
Q3
Overweight


Wireless Telecommunication Services
CCI
Crown Castle International Corp.
1.00%
67.55
67.55
11/23/2012
Q2
Overweight













Utilities

3.3%
5.0%







Electric Utilities
AEP
American Electric Power Co. Inc.
2.00%
41.03
35.98
12/31/2010
Q4
Overweight


Electric Utilities
DUK
Duke Energy Corp.
1.00%
60.45
60.45
11/23/2012
Q2
NA


Multi-Utilities
SRE
Sempra Energy
2.00%
66.05
56.30
1/20/2012
Q3
Overweight















100.0%
100.0%

















Source: Morgan Stanley Research. Past performance is no guarantee of future results. Price performance does not take transaction costs into account. For companies included in the portfolio, all important disclosures including personal holdings disclosures and Morgan Stanley disclosures appear on the Morgan Stanley public website at www.morganstanley.com/researchdisclosures. ++Rating for this company has been removed from consideration in this report because, under applicable law and/or Morgan Stanley policy, Morgan Stanley may be precluded from issuing such information with respect to this company at this time. NC = Not covered.
26
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
History of Portfolio Changes





Price When








Removed or Latest

S&P 500 Total
Relative
Ticker
Company
Date Added
Date Removed
Price When Added
Price
Total Return
Return
Performance
ABT
Abbott Laboratories
12/31/2010
2/4/2011
47.91
46.12
-2.8%
4.2%
-7.1%
ACE
ACE Ltd.
6/17/2011

64.31
79.80
28.2%
10.8%
17.3%
ACN
Accenture PLC
12/31/2010
1/6/2012
48.49
51.83
9.2%
1.6%
7.6%
ACN
Accenture PLC
9/17/2012

65.60
68.18
5.2%
-3.6%
8.7%
AFL
AFLAC Inc.
12/31/2010
6/17/2011
56.43
45.02
-19.2%
1.1%
-20.3%
A
Agilent Technologies Inc.
11/23/2012

36.88
36.88
0.0%
0.0%
0.0%
ALB
Albemarle Corp.
12/31/2010
10/28/2011
55.78
55.13
-0.3%
2.2%
-2.5%
AGN
Allergan Inc.
12/31/2010
6/17/2011
68.67
80.84
17.9%
1.1%
16.8%
AEE
Ameren Corp.
9/16/2011
1/20/2012
30.42
31.64
5.3%
8.2%
-2.8%
AEP
American Electric Power Co. Inc.
12/31/2010

35.98
41.03
24.4%
12.0%
12.4%
AXP
American Express Co.
12/31/2010
1/21/2011
42.92
46.00
7.6%
2.0%
5.6%
ABC
AmerisourceBergen Corp.
12/31/2010

34.12
41.38
24.4%
12.0%
12.3%
AMR
AMR Corp.
7/8/2011
9/16/2011
5.50
3.54
-35.6%
-9.5%
-26.1%
ANN
Ann Inc.
12/2/2011
9/17/2012
24.43
38.69
58.4%
17.4%
40.9%
AAPL
Apple Inc.
1/6/2012

422.40
571.50
36.6%
10.3%
26.3%
ACI
Arch Coal Inc.
12/31/2010
9/23/2011
35.06
15.26
-55.6%
-9.6%
-45.9%
T
AT&T Inc.
5/25/2012

33.69
34.36
4.6%
6.9%
-2.3%
AVP
Avon Products Inc.
12/31/2010
2/4/2011
29.06
29.25
0.7%
4.2%
-3.6%
AXS
AXIS Capital Holdings Ltd.
9/23/2011
5/4/2012
25.43
34.38
38.0%
20.5%
17.5%
BHI
Baker Hughes Inc.
12/31/2010
12/30/2011
57.17
48.64
-13.9%
0.0%
-13.9%
BAC
Bank of America Corp.
12/31/2010
7/8/2011
13.34
10.70
-19.6%
6.9%
-26.5%
BEN
Franklin Resources Inc.
5/4/2012

117.57
133.18
13.7%
2.9%
10.8%
BK
Bank of New York Mellon Corp.
12/31/2010
9/23/2011
30.20
18.52
-37.5%
-9.6%
-27.9%
BMY
Bristol-Myers Squibb Co.
7/8/2011

29.12
32.62
17.8%
4.9%
13.0%
CAT
Caterpillar Inc.
10/19/2012

83.86
84.16
0.4%
-1.7%
2.0%
CAM
Cameron International Corp.
12/31/2010
1/28/2011
50.73
52.48
3.4%
1.5%
2.0%
CAH
Cardinal Health Inc.
12/31/2010

38.31
39.99
8.4%
12.0%
-3.7%
CAVM
Cavium Inc.
2/17/2012

36.01
32.56
-9.6%
3.5%
-13.1%
CBS
CBS Corp (Cl B)
12/31/2010

19.05
35.85
91.7%
12.0%
79.7%
CTL
CenturyLink Inc.
12/31/2010
4/5/2012
46.17
38.52
-8.7%
11.2%
-19.9%
CF
CF Industries Holdings Inc.
7/8/2011
10/4/2011
149.01
124.10
-16.4%
-16.4%
-0.1%
CVX
Chevron Corp.
12/31/2010

91.25
105.47
22.8%
12.0%
10.8%
CB
Chubb Corp.
9/23/2011

57.89
77.23
36.2%
24.0%
12.2%
CCI
Crown Castle International Corp.
11/23/2012

67.55
67.55
0.0%
0.0%
0.0%
CHMT
Chemtura Corp.
10/12/2012

15.70
19.62
25.0%
-1.4%
26.3%
CSCO
Cisco Systems Inc.
2/17/2012

20.29
18.84
-5.7%
3.5%
-9.2%
COH
Coach Inc.
12/31/2010
12/2/2011
55.31
62.20
13.9%
-1.1%
15.0%
CL
Colgate-Palmolive Co.
9/23/2011

88.92
108.00
24.9%
24.0%
0.9%
CMA
Comerica Inc.
12/31/2010
9/23/2011
42.24
22.49
-46.0%
-9.6%
-36.4%
COST
Costco Wholesale Corp.
12/31/2010

72.21
97.92
38.4%
12.0%
26.3%
COV
Covidien PLC
6/17/2011

52.50
57.42
12.0%
10.8%
1.1%
DHR
Danaher Corp.
12/31/2010
9/16/2011
47.17
45.94
-2.5%
-3.3%
0.8%
DHR
Danaher Corp.
11/23/2012

53.49
53.49
0.0%
0.0%
0.0%
DAL
Delta Air Lines Inc.
12/31/2010
7/8/2011
12.60
9.35
-25.8%
6.9%
-32.6%
DOW
Dow Chemical Co.
4/5/2012

33.42
29.38
-10.2%
0.8%
-11.0%
DVN
Devon Energy Corp.
12/31/2010
4/15/2011
78.51
87.82
12.1%
4.9%
7.1%
DIS
Walt Disney Co.
1/28/2011
10/4/2011
38.85
29.86
-23.1%
-11.9%
-11.2%
DUK
Duke Energy Corp.
11/23/2012

60.45
60.45
0.0%
0.0%
0.0%
EP
El Paso Corp.
12/31/2010
7/13/2012
13.76
#N/A
#N/A
7.9%
#N/A
EMC
EMC Corp.
12/31/2010

22.90
24.81
8.3%
12.0%
-3.7%
EMR
Emerson Electric Co.
10/19/2012

48.25
49.12
2.7%
-1.7%
4.3%
ETR
Entergy Corp.
9/16/2011
1/20/2012
65.60
69.93
7.9%
8.2%
-0.3%
ESRX
Express Scripts Holding Co
12/31/2010
2/4/2011
54.05
57.13
5.7%
4.2%
1.5%
F
Ford Motor Co.
12/31/2010
3/11/2011
16.79
14.36
-14.5%
3.7%
-18.2%
GD
General Dynamics Corp.
9/16/2011

60.60
65.41
12.0%
15.9%
-3.9%
GE
General Electric Co.
4/15/2011
7/8/2011
20.04
18.99
-4.5%
1.8%
-6.3%
GM
General Motors Co.
11/23/2012

25.21
25.21
0.0%
0.0%
0.0%
GOOG
Google Inc. Cl A
12/31/2010
9/16/2011
593.97
546.68
-8.0%
-3.3%
-4.7%
GSIC
GSI Commerce Inc.
12/31/2010
7/22/2011
23.23
NA
NA
6.9%
NA
HAL
Halliburton Co.
10/28/2011
5/4/2012
39.13
32.53
-16.4%
6.5%
-22.9%
HES
Hess Corp.
7/13/2012

43.29
51.12
18.3%
3.9%
14.5%
HON
Honeywell International Inc.
9/17/2012

61.72
61.26
-0.1%
-3.6%
3.5%
HPQ
Hewlett-Packard Co.
12/31/2010
6/17/2011
42.10
35.00
-16.4%
1.1%
-17.5%
INTC
Intel Corp.
12/31/2010
2/18/2011
21.03
22.14
6.1%
6.8%
-0.6%
IBM
International Business Machines Corp.
12/31/2010
7/8/2011
146.76
176.49
21.2%
6.9%
14.4%
INTU
Intuit Inc.
12/31/2010
2/17/2012
49.30
57.38
17.0%
8.2%
8.8%
JPM
JPMorgan Chase & Co.
12/31/2010

42.42
41.09
1.5%
12.0%
-10.6%
KFT
Mondelez International Inc. Cl A
12/31/2010

31.51
25.62
34.1%
12.0%
22.1%
KMI
Kinder Morgan Inc.
11/23/2012

33.72
33.72
0.0%
0.0%
0.0%
LRCX
Lam Research Corp.
2/18/2011
7/22/2011
56.10
44.26
-21.1%
0.1%
-21.3%
LO
Lorillard Inc.
5/13/2011
11/23/2012
111.51
123.27
18.2%
5.3%
12.9%
LYB
LyondellBasell Industries N.V. Cl A
10/28/2011

34.50
48.62
66.9%
9.7%
57.2%
MA
MasterCard Inc. Cl A
2/17/2012

396.00
481.24
21.8%
3.5%
18.2%
MON
Monsanto Co.
4/5/2012

79.02
90.58
15.5%
0.8%
14.7%
MCD
McDonald's Corp.
9/23/2011

87.37
87.05
2.8%
24.0%
-21.2%
MCK
McKesson Corp.
2/4/2011

77.74
94.11
22.8%
7.5%
15.3%
MHS
Medco Health Solutions
12/31/2010
7/8/2011
61.27
55.26
-9.8%
6.9%
-16.7%
MSFT
Microsoft Corp.
12/31/2010

27.91
27.70
4.7%
12.0%
-7.4%
MSI
Motorola Solutions Inc.
7/8/2011
2/17/2012
45.08
50.63
13.3%
1.3%
12.0%
MWE
MarkWest Energy Partners L.P.
11/23/2012

50.84
50.84
0.0%
0.0%
0.0%
NBR
Nabors Industries Ltd.
12/31/2010
4/8/2011
23.46
31.56
34.5%
5.6%
28.9%
NTRS
Northern Trust Corp.
12/31/2010
4/15/2011
55.41
51.78
-6.0%
4.9%
-11.0%
NOC
Northrop Grumman Corp.
9/16/2011
9/17/2012
54.82
66.48
25.1%
20.2%
4.9%
NVE
NV Energy Inc.
12/31/2010
9/16/2011
14.05
14.74
7.5%
-3.3%
10.8%
OXY
Occidental Petroleum Corp.
12/31/2010
9/17/2012
98.10
90.06
-4.7%
16.2%
-20.9%
ORCL
Oracle Corp.
6/17/2011

31.19
30.92
0.3%
10.8%
-10.5%
PFE
Pfizer Inc.
12/31/2010
2/4/2011
17.51
19.30
11.4%
4.2%
7.1%
PFE
Pfizer Inc.
9/16/2011

18.15
24.53
41.1%
15.9%
25.2%
PM
Philip Morris International Inc.
12/31/2010

58.53
90.41
63.4%
12.0%
51.3%
PNC
PNC Financial Services Group Inc.
1/21/2011

60.83
55.75
-4.1%
9.8%
-13.9%
PNW
Pinnacle West Capital Corp.
3/11/2011
9/16/2011
43.56
44.21
3.9%
-6.8%
10.7%
PNW
Pinnacle West Capital Corp.
1/20/2012
7/13/2012
47.75
53.05
13.3%
3.1%
10.2%
PG
Procter & Gamble Co.
4/8/2011
1/6/2012
61.90
66.36
9.7%
-3.8%
13.5%
QCOM
QUALCOMM Inc.
12/31/2010
4/15/2011
49.49
53.14
7.8%
4.9%
2.8%
RNR
RenaissanceRe Holdings Ltd.
12/31/2010
4/15/2011
63.69
69.08
8.9%
4.9%
3.9%
RNR
RenaissanceRe Holdings Ltd.
7/8/2011

71.25
81.32
16.0%
4.9%
11.1%
COL
Rockwell Collins Inc.
12/31/2010
1/6/2012
58.26
56.55
-1.3%
1.6%
-2.9%
SLB
Schlumberger Ltd.
12/31/2010

83.50
71.18
-12.6%
12.0%
-24.6%
SRE
Sempra Energy
1/20/2012

56.30
66.05
20.5%
7.1%
13.4%
SYK
Stryker Corp.
2/4/2011
7/22/2011
58.51
56.88
-2.2%
2.6%
-4.8%
SYK
Stryker Corp.
9/21/2012

56.29
54.52
-2.8%
-3.5%
0.7%
TFM
Fresh Market Inc.
12/30/2011
11/23/2012
39.90
62.38
56.3%
12.1%
44.3%
TGT
Target Corp.
12/30/2011

51.22
64.48
28.5%
12.1%
16.4%
TYC
Tyco International Ltd.
12/31/2010
4/15/2011
41.44
51.70
25.3%
4.9%
20.4%
TRV
Travelers Cos. Inc.
4/15/2011

59.80
71.27
23.5%
6.8%
16.7%
UNP
Union Pacific Corp.
12/31/2010
5/25/2012
92.66
111.88
23.5%
4.8%
18.7%
UNH
UnitedHealth Group Inc.
12/31/2010
9/17/2012
36.11
54.48
54.2%
16.2%
38.0%
URS
URS Corp.
12/31/2010

41.61
35.49
-13.3%
12.0%
-25.3%
UTX
United Technologies Corp.
12/30/2011

73.09
78.61
10.3%
12.1%
-1.7%
WAG
Walgreen Co.
7/8/2011
12/30/2011
44.07
33.06
-24.0%
-6.4%
-17.5%
WPI
Watson Pharmaceuticals Inc.
12/31/2010
7/8/2011
51.65
69.85
35.2%
6.9%
28.4%
WLP
WellPoint Inc.
2/4/2011
9/16/2011
65.07
67.70
5.2%
-7.2%
12.4%
WMB
Williams Companies Inc
5/4/2012

32.70
33.44
4.1%
2.9%
1.2%
WU
Western Union Co.
2/18/2011
11/23/2012
21.66
12.80
-38.1%
4.9%
-43.0%
XOM
Exxon Mobil Corp.
7/22/2011
5/25/2012
85.22
82.08
-1.4%
-2.0%
0.7%
XOM
Exxon Mobil Corp.
7/13/2012
9/17/2012
85.47
91.91
8.2%
7.7%
0.5%
YUM
Yum! Brands Inc.
12/31/2010

49.05
74.00
55.4%
12.0%
43.4%
Source: Factset, Morgan Stanley Research
27
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Disclosure Section
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Within the last 12 months, Morgan Stanley managed or co-managed a public offering (or 144A offering) of securities of Crown Castle Corp., Duke Energy Corporation, Fresh Market Inc, General Motors Company, MarkWest Energy Partners L P.
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Global Stock Ratings Distribution
(as of October 31, 2012)
For disclosure purposes only (in accordance with NASD and NYSE requirements), we include the category headings of Buy, Hold, and Sell alongside our ratings of Overweight, Equal-weight, Not-Rated and Underweight. Morgan Stanley does not assign ratings of Buy, Hold or Sell to the stocks we cover. Overweight, Equal-weight, Not-Rated and Underweight are not the equivalent of buy, hold, and sell but represent recommended relative weightings (see definitions below). To satisfy regulatory requirements, we correspond Overweight, our most positive stock rating, with a buy recommendation; we correspond Equal-weight and Not-Rated to hold and Underweight to sell recommendations, respectively.

Coverage Universe
Investment Banking Clients (IBC)


% of

% of % of Rating

Stock Rating Category
Count
Total
Count
Total IBC
Category








Overweight/Buy
1085
37%
446
40%
41%
Equal-weight/Hold
1288
43%
504
46%
39%
Not-Rated/Hold
109
4%
31
3%
28%
Underweight/Sell
481
16%
121
11%
25%
Total
2,963


1102



28
M O R G A N S T A N L E Y R E S E A R C H
November 26, 2012
US Equity Strategy
Data include common stock and ADRs currently assigned ratings. An investor's decision to buy or sell a stock should depend on individual circumstances (such as the investor's existing holdings) and other considerations. Investment Banking Clients are companies from whom Morgan Stanley received investment banking compensation in the last 12 months.
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Benchmarks for each region are as follows: North America - S&P 500; Latin America - relevant MSCI country index or MSCI Latin America Index; Europe - MSCI Europe; Japan - TOPIX; Asia - relevant MSCI country index.
.
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November 26, 2012
US Equity Strategy
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