2. Steve Cossettini CFA
FREIMARK BLAIR & CO., INC
Member FINRA & SIPC
One Park Way, Upper Saddle River
New Jersey, NJ 07458
Equity Desk: 201.760.0080
scossettini@freimark.com
Our weekly note analyzes 36 factors inclusive of 13 conditional, which we explain later, and 5 core Freimark Blair (FB) factors. Each chart is explained in the caption
next to it. When we look at the long/short performances of a factor we are only analyzing the extremes and in this case the top and bottom 20% of stocks that are
exposed to that factor. For example, if our factor is PE, a stock with a value of 5 will likely be in the long portfolio (quintile 1), a stock with a PE of 80 in the short
portfolio (quintile 5) and a stock with a PE of 40 ignored, as it is in the mid section of the universe, (quintile 2-4). However, note that all Information Co-Efficient
(IC) calculations do look across all stocks in the universe. The IC reflects how strong the factors signal was for that week. The higher the IC the more robust the
factor was in explaining the stocks performance.
This publication is a general market commentary and does not constitute a research report. Any reference to a research report or a recommendation is not intended to represent the entire report and is
not itself a research report or recommendation. The information included is from public sources that are believed to be reliable and correct, including FactSet/Bloomberg sourced data. The commentary
is for informational purposes only and may be based wholly or partly on market chatter, industry, gossip, or innuendo; it does not contain investment advice and should not be relied upon as such. Charts,
graphs or formulas published have limitations and are not projections to determine future profitability of any security transaction. This information is subject to change at any time. All investments have
risks and there is no guarantee against loss. For Institutional Use Only – Not For Public Distribution.
Weekly Highlights
“What’s In Play” – SP1500
Report Date 11/23/2015
•The week concluding Nov.20 was the tale of two stories; pre Fed minutes (Weds Nov.18) and post, with the minutes revealing a high-probability of a “one-and-done” Fed
•For the most part, growth and momentum plays were preferred over deep-value as aggressive risk-on positions took hold at the backend of the week
•Growth styles; long/short ROA, produced a statistically favorable result in nine of the10-GIC sectors (six significantly), the highest hit ratio of the 34 factors analyzed
•Price momentum has been a volatile strategy the past 12 months, page.8 demonstrates how challenging its been (as we define it), but, the returns have been significant
•Consumer discretionary (as we head into the shopping frenzy season), Industrials and Materials received the largest net EPS downgrades during the week, a clearer picture
on the last two sectors will crystallize as we have a busy economic calendar ahead with preliminary PMI data from; U.S., Euro Zone, Japan, Germany, and, GDP prints for;
U.S. (2nd print), UK, Germany, Singapore, Taiwan and Philippines on the tape this week
•A sea of green on the ETF flows front, Fed minutes fuelling risk-taking with financials leading the charge while utilities dwelt at the other end of the fund-flow spectrum pg.5
•Stock-correlations have abated, falling below the 10-year average, which implies favorable conditions for stock-pickers at the detriment of CTA/Macro funds
•For the week ahead, we favor deep-value over growth strategies as we approach an important first week of December; (IMF/SDR decision, ECB QE, Yellen, OPEC supply
meeting, global PMIs & GDP). Also see an opportunity for a technical trade in XRT (U.S. retailers) on low expectations going into the consumer frenzy (Black Fri – Cyber Mon)
Upcoming fret events:
1. The historic and symbolic date for CNY inclusion for SDR entry – Nov.30 (fully expect inclusion)
2. ECB Dec.3 (QE extension?)
3. Fed policy uncertainty - Next Fed meeting Dec 15-16 (expect hike Dec.16)
3. BoJ on-deck Dec.18
4. Ukraine/Russia debt, gas supply issues and geopolitical woes
6. Low oil prices and Venezuela = LatAm contagion and/or geopolitical risk threat?
3. Universe: SP1500 as defined by Standard &
Poor’s.
Long/Short factor portfolios are a compilation of
the top and bottom 20%.
Information Co-Efficient is over the entire market:
we rank the stocks by each factor and rank their
next 5 day total return prior to calculating the IC.
The higher the IC, the stronger the signal.
Conditional factors are the red columns;
A lot of quantitative models use earnings EPS
upgrades in their multi -factor modeling. Analysts
were very late to upgrade stocks post financial
crisis, managers missed out on some deep value
stocks as these stocks did not pass the EPS
upgrade factor.
Can we really believe in a high ROA if the taxes
paid/pre-tax earnings ratio is extraordinarily
different when compared to the respective
national tax rate? There could be a quality in
earnings issue present (abnormal accruals), so we
condition for this.
These are just two examples of why we look at
conditional factors. The list can be extensive.
The universe can become quite small.
Example: there may be few Downgrades for the
week, causing the IC and Long/Short performance
to be volatile and opposite.
Source: Freimark Blair 11/23/2015 For Institutional Use Only – Not For Public Distribution 3
-30
-20
-10
0
10
20
30
-1.2
-0.8
-0.4
0.0
0.4
0.8
1.2
%
Weekly Factor Performance
Long/Short Factor Returns SP1500 (% LHS) InformationCo-Efficient (RHS)
-30
-20
-10
0
10
20
30
-1.2
-0.8
-0.4
0.0
0.4
0.8
1.2
%
Conditional Weekly Factor Performance
Long/Short Factor Returns SP1500 (% LHS) InformationCo-Efficient (RHS)
4. Breakout the individual long-short factor books, perhaps a trend exists within. We define “Hit Ratio”
as the % of Global Industry Classification sectors that have a positive IC for the factor analyzed.
Source: Freimark Blair 11/23/2015 For Institutional Use Only – Not For Public Distribution 4
U.S. Median Factor Returns
Description Long Short L/S IC
ROA on quality (tax) 3.18 3.09 0.09 12
ROE on quality (tax) 3.32 3.06 0.26 12
ROA 3.43 2.58 0.86 12
ROE 3.13 2.52 0.61 11
Quality on (Low P/BK) 1.90 0.05 1.84 10
Price Momentum on Small caps 2.26 1.94 0.31 9
Size 3.04 2.22 0.82 8
EPS Dispersion 3.20 2.59 0.62 7
FB Price Momentum 2.96 2.16 0.81 6
# of UP Revisions 3.23 2.69 0.54 6
ESG A/B 3.30 2.98 0.32 6
Target Price Raised last mth 3.12 2.29 0.83 5
FB EPS Momentum 3mth 3.06 2.43 0.63 4
Quality on Downgrades 3.05 2.79 0.25 4
Quality on Upgrades 2.97 2.82 0.15 4
FB Quality 3.00 2.83 0.17 3
EPSLTG 3.31 2.91 0.40 3
Price to Taxes Paid 3.02 2.85 0.17 2
Price Volume 3.06 2.98 0.08 2
Price Target Raised 2.94 2.60 0.34 1
Earnings on (low coverage) 2.24 2.32 -0.07 1
Dividend Yield 2.92 2.37 0.55 0
ESG - Quality 2.62 3.68 -1.05 0
FB EPS Momentum 1mth 2.75 3.09 -0.34 -1
# of Brokers (low= best) 2.66 2.70 -0.03 -1
Beta 2.58 2.89 -0.31 -1
Growth on Downgrades 2.88 3.22 -0.34 -2
FB Value (PE rel to Sector) 2.55 3.41 -0.87 -2
Price to Earnings 2.83 3.41 -0.59 -3
Value on Downgrades 2.42 3.20 -0.78 -3
FB Growth 2.95 3.12 -0.16 -4
Value on Upgrades 2.90 3.77 -0.87 -5
Growth on (High P/BK) 3.26 3.77 -0.50 -7
Growth on Upgrades 2.75 3.18 -0.43 -8
Price to Book 2.39 3.23 -0.84 -12
Price to Cash Flow 1.94 3.29 -1.35 -15
Earnings on (high coverage) 2.25 2.03 0.22 -29
0% 20% 40% 60% 80% 100%
ROA
# of UP Revisions
FB EPS Momentum 1mth
Size
ROE
FB Quality
FB Price Momentum
EPS Momentum 3mth
Target Price Raised last mth
Beta
EPS Dispersion
Price to Taxes Paid
FB Value (PE rel to Sector)
Dividend Yield
EPSLTG
FB Growth
Price Target Raised
# of Brokers (low= best)
Price to Book
Price to Cash Flow
(Hit Ratio) % of Factor IC's that are + for Each Sector
Hit Ratio
6. Leadership turnover chart groups companies together on a returns basis for
the past fifty one weeks (Top 20%). The chart then shows what % of stocks
are STILL in that basket as of last week. The lower the column the more
turnover implied in the market’s leadership as the constituents are not the
same. Is it time to pause perhaps and take a deeper look as portfolios may
be getting stale?
Dimensionality of the market analyzes pair-wise factor correlations. No
returns used here. We are examining the relationship between factors and,
in this case, price momentum and value for the past 5 years. A rising line
implies our factors are not as diversified as we may think and are likely to
select the same stocks. Is it time to call our trading desk and sell some
positions and change allocation? Or, should you at least be thinking about
buying protection? You don’t want your entire stock screen to be red on the
same day, the boss might tap you on the shoulder.
Source: Freimark Blair 11/23/2015 For Institutional Use Only – Not For Public Distribution 6
0
10
20
30
40
50
60
%
Leadership Turnover
Leaders Laggers
-30
-25
-20
-15
-10
-5
0
5
10
15
Correlation
Dimensionality of the Market (Price/Value)
Dimensionality AVG +2StdDev AVG -2StdDev
7. Source: Freimark Blair 11/23/2015 For Institutional Use Only – Not For Public Distribution
Every week we take the price change of each stock in the index and compute their individual 50-Day-Rolling correlation
with the actual index (SP1500).
So if IBM goes up 50-days in a row and the SP1500 went up 50-days in a row that would be a correlation of 1.0 or 100%
for that stock. We are analyzing direction not magnitude.
The chart above runs this analysis for every individual-stock in the index and takes the overall average every week going
back 10 years. (Blue Line, LHS axis)
The (Green Line, RHS axis) is the monthly HFRI index % change for a Long/Short Hedge Fund strategy.
For L/S strategies to perform, they seek “low-stock-correlation”. This is because L/S managers want to be compensated
on their long- and short-books. They’re in search of two alphas. It’s the CTA strategies that tend to perform in periods of
high correlation, they can move in and out of positions quicker.
7
-12
-8
-4
0
4
8
12
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
%
SP1500, A Stock Picker's Market?
50-Day Rolling Correlation AvgCorrel HFRI Equity Long/Short Monthly Return (RHS)
8. This chart captures the last 12 months average and inter-quartile range for our core (5) Freimark Blair
factors. The larger the range the more volatile the factor. Quality is quite stable and relatively safe
given its low band range. Price Momentum can hurt performance if we are on the wrong direction of
the trade given its last 12 months volatile nature, depicted by the band range. You might need some
protection on this strategy. Refer to definition page for factor disclosures.
How Volatile Are Freimark Blair Factors in the US?
Source: Freimark Blair 11/23/2015 For Institutional Use Only – Not For Public Distribution 8
3.00
1.40
0.34
3.24
5.34
-20
-10
0
10
20
Earnings Momentum Growth Value Quality Price Momentum
IC%
FB 12mth Rolling Factor Effectiveness
Average ---- 25th Percentile ---- 75th Percentile
9. In the above table, we break out each sector’s Spearman
ranked Information Coefficient for the relevant factor
analyzed.
Market characteristics. Price levels and not just returns are
important. “Adjustment and Anchoring Bias” where people
take as a reference point a completely random and irrelevant
value when making a judgement about something else. For
example traders anchor to the 52-week high price such that
when the price is close to this level they are reluctant to bid
the price higher, even if new information warrants it. The
information eventually prevails and the stock price moves
up. Results show that stocks with prices close to their 52-
week high outperform stocks with prices that are very far
from their 52-week high.
Source: Freimark Blair 11/23/2015 For Institutional Use Only – Not For Public Distribution 9
SP1500 Factors Information Coefficient In Each Sector
Hit Ratio
ROA 9 4 41 10 12 -4 2 22 33 34 90%
# of UP Revisions 1 3 22 5 -1 16 13 25 -23 14 80%
FB EPS Momentum 1mth 2 1 -7 1 -3 13 -11 11 30 1 70%
Size -3 4 44 4 6 14 18 20 -22 -4 70%
ROE 4 -3 41 -10 9 1 5 29 -7 15 70%
FB Quality -4 15 25 -1 15 2 0 13 -22 6 70%
FB Price Momentum -3 20 32 -5 -24 1 -7 29 11 23 60%
EPS Momentum 3mth 4 11 0 -4 -4 8 -12 26 -1 11 60%
Target Price Raised last mth -3 9 27 -4 -15 21 -2 16 15 29 60%
Beta 18 -15 -13 -10 24 5 3 -18 33 -16 50%
EPS Dispersion -2 -16 27 -9 -8 0 2 23 -37 23 50%
Price to Taxes Paid 3 -7 51 -10 -21 25 9 11 -41 -15 50%
FB Value (PE rel to Sector) 9 1 -9 -23 -7 -9 6 -16 51 5 50%
Dividend Yield -8 4 10 11 -7 6 13 -6 -9 -14 50%
EPSLTG 5 5 -8 -15 5 -12 -8 20 -25 -18 40%
FB Growth -18 0 -13 7 5 -6 -3 21 -15 18 40%
Price Target Raised 9 -6 -16 -10 3 -7 -6 -2 -11 17 30%
# of Brokers (low= best) -5 7 -5 1 2 -13 -19 -10 -6 -3 30%
Price to Book 6 -6 -39 -19 -21 -6 0 -42 25 -4 20%
Price to Cash Flow -5 7 -35 -21 -15 -3 9 -36 -44 -18 20%
Info Tech Materials Telecommunication UtilitiesConsumer Discretionary Consumer Staples Energy Financials Health Care Industrials
0
10
20
30
40
50
%
Bull / Bear Indicator
Percentage of stocks making 52wk high/lows during week
52wk High
52wk Low
10. 10Source: Freimark Blair 11/23/2015 For Institutional Use Only – Not For Public Distribution
Chart displays the SP-1500 stocks that made 52-week-highs or -lows as a % of their respective GIC sector.
Note, the high/low could be made on any given day of the previous trading week (Mon-Fri), but counted only once.
For example, a value of 20% implies 1 out of 5 stocks of their particular sector made a 52-week-high / -low. We’re
analyzing the depth/breadth of the move within sectors. Equity markets can rise/fall due to movements from large stocks
which can be less representative of the overall pulse of the market. An example is when Apple Inc. moves higher on
individual company news, the Tech index moves higher but the constituents of Tech are not participating.
We also analyze weekly changes, trying to identify if a sector kicked-off recently or lagged, relative to the week prior.
11. These charts represent
the % of companies in
each sector relative to
our universe (SP1500).
We have only selected
the most over and
under allocated sectors
relative to the original
market allocation. The
factor portfolio
construction is based
again on the top 20% of
stocks exposed to the
factor. Example, if our
top 20% of value stocks
(our long book) has 10
financial stocks in it and
our top value portfolio
has a total of 50 stocks,
then this is a 20%
allocation to that sector.
We compare this to the
original market
allocation to determine
if our factors are
favoring a sector.
Which sectors did our core Freimark Blair factors over/under weight the most?
Source: Freimark Blair 11/23/2015 For Institutional Use Only – Not For Public Distribution 11
19
4
15
20
0 5 10 15 20 25
Industrials
Financials
%
% Market % Growth
19
6
15
20
0 5 10 15 20 25
Industrials
Financials
%
% Market % Quality
21
17
16
20
0 5 10 15 20 25
Info Tech
Financials
%
% Market % Value
12
1
5
6
0 2 4 6 8 10 12 14
Consumer Staples
Energy
%
% Market % Price Momentum
12. Sector Analysis
Last week did
analysts upgrade or
downgrade the
market and sectors
on an EPS basis?
Source: Freimark Blair 11/23/2015 For Institutional Use Only – Not For Public Distribution 12
0 10 20 30
1
%
% Market Upgrades % Market Downgrades
0 10 20 30
Telecoms
Materials
Industrials
Utilities
Consumer Staples
Health Care
Info Tech
Energy
Financials
Consumer Disc
%
% Weekly Upgrades % Weekly Downgrades
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
SP1500 Consumer
Disc
Info Tech Industrials Telecoms Financials Health Care Materials Consumer
Staples
Utilites Energy
SP1500 Sectors One Week Total Return (%)
13. FB Price Momentum We skip the last month. Look at the previous 11 month’s of stocks total return and normalize it with the monthly
standard deviation of monthly total return. We do not want to rate stocks that have underperformed for the
majority of the year but spiked up massively in the last month. We are looking for momentum. High ranks best.
FB Value PE relative to Market Price to Earnings/Stocks Sectors Average Price to Earnings.
FB EPS Momentum 1mth (Mean EPS(now) – Mean EPS(-1mth))/abs(Mean EPS -1mth). Require more than 3 analysts coverage.
EPS Momentum 3mth (Mean EPS(now) – Mean EPS(-3mth))/abs(Mean EPS -3mth). Require more than 3 analysts coverage.
EPS Dispersion (Highest analyst EPS estimate – Lowest EPS estimate)/abs(mean EPS). Low ranks best, looking for certainty amongst
analysts even though uncertainty among analysts can be perceived as opportunistic.
Number of Brokers Low ranks best so we are looking for stocks that are not highly covered by analysts (opportunistic).
Price Target Raised Price Target(now) – Price Target(last)/scaled by Price Target(last). Higher is best.
Price to Taxes Paid Current Price to Taxes Paid from cash flow statement (Quality measure). Low ranks best just like PE.
Price Volume 5-day avg price / 1-month, same for volume, zscore with sector, sum scores. Long previous week high price/volume stocks short
low price- low volume stocks. Are on fire, or unloved , momentum-volume stocks trend continuing.
EPSLTG EPS Long Term Growth.
ESG A/B Long [AAA, AA, A] ESG rated companies from MSCI that are in the SP1500, short [BBB, BB, B, CCC]
ESG – Quality First screen for stocks that are [AAA, AA, A] ESG rated, then run the Quality model as per next page.
Price Momentum conditional on Size Prior to conducting Price Momentum analysis we screen for small cap stocks first. We expect small cap stocks to do
better with this factor as our back tests suggest.
Number of UP Revisions Higher ranks best scaled by total number of brokers. An up revision is an EPS upgrade.
1 Year Beta Daily returns correlation with SP1500.
Quality Conditional on Upgrades First screen for only stocks that have been upgraded this week. Then run the quality model against the list.
Quality Conditional on Downgrades First screen for only stocks that have been downgraded this week. Then run the quality model against the list.
Earnings Momentum Conditional We believe low analyst covered stocks have a higher signal for Earnings Momentum. We also include highly
on low analyst coverage covered pre screen list to cross check our sanity, we can be wrong on occasions.
Earnings Momentum Conditional Earnings Momentum for stocks that are highly covered by analysts.
on high analyst coverage
Growth Conditional on Upgrades First screen for only stocks that have been upgraded this week. Then run the growth model against the list.
Growth Conditional on Downgrades First screen for only stocks that have been downgraded this week. Then run the growth model against the list.
ROA Conditional on quality (tax) First screen for only stocks that have paid taxes (cash flow statement) at a % similar to their country’s tax rate.
ROE Conditional on quality (tax) First screen for only stocks that have paid taxes (cash flow statement) at a % similar to their country’s tax rate.
It is a quality check. Accruals can manipulate earnings and therefore effect ROE or ROA.
Value Conditional on Upgrades First screen for stocks that have been upgraded this week. Then run the value model.
Value Conditional on Downgrades First screen for stocks that have been downgraded this week. Then run the value model. Sanity check.
Quality Conditional on Low Price/Book First screen for only the lowest quintile (20%) of stocks ranked by Price/Book prior to running analysis.
Growth Conditional on High Price/Book First screen for only the highest quintile (20%) of stocks ranked by Price/Book prior to running analysis.
FactSet sourced data 11/23/2015
Factor Definitions
14. FB Quality
Uses most recent quarter but year on year comparisons. All factors are ranked using the zscore system which analyzes the values standard deviation away from the
stock’s sector average. We then sum up the individual values and form the total multi-factor score. For example if company XZY had a Return on Assets (ROA) of 40
and the relevant GIC sector average is 20 with a standard deviation of 10, this stock scores a 2 because it is 2x standard deviations away from it’s sector average. The
final score is based on a sum of all individual factors below. Then as in all of our factors analyzed, we go long the top 20% and short the bottom 20%.
Profitability signal: 1) Stocks return on assets (Last 12months Net Income divided by the average Total Assets of the last 2 years, ROA) zscore
2) ROA zscore minus last years
3) Gross Margin (Gross Income to Sales) zscore compared to last years
Cash basis signal: 4) Cash flow from operations divided by the average Total Assets of the last 2 years (CFROA), zscore
Accrual signal: 5) CFROA zscore minus ROA zscore
Leverage signal: 6) Total debt to last 2 years average for total assets zscore. (Last years score minus current year), looking for a reduction
Liquidity signal: 7) Current Assets to Current Liabilities zscore compared to last years
Financing signal: 8) Company issue capital over the last year measured as a zscore (note it is a minus, so if company has issued shares it is a minus)
Efficiency signal: 9) Asset Turnover (Sales divided by the average Total Assets of the last 2 years) zscore compared to last years
FB Growth
Uses a binary scoring system (1 or 0). The final score is based on a sum of all individual factors below. Then as in all of our factors analyzed, go long the top 20% and
short the bottom 20%.
Profitability signal: 1) Is the stock’s ROA greater than GIC sector peers median
2) Is the stock’s CFROA greater than GIC sector peers median
Accrual signal: 3) Is the stock’s CFROA greater than ROA
Variability signal (will it persist): 4) Is the stock’s last 5 year’s standard deviation of Net Income LESS THAN their peers sector median standard deviation
5) Is the stock’s last 5 year’s standard deviation of Sales LESS THAN their peers sector median standard deviation
Future Investment Signal: 6) Is the stock’s Capital Expenditure divided by average total assets (CAPEX), greater than their peers sector median
7) Is the stock’s Research + Development divided by average total assets (R+D), greater than their peers sector median
FactSet sourced data 11/23/2015
Factor Definitions
