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....Global Economics Report
April 14, 2017
Where We Are Now . . . . . . . . . . . . . . . . . . . . . . . 1
Indicators for US Economy . . . . . . . . . . . . . . . . . . . 2
US Economic Heartbeat . . . . . . . . . . . . . . . . . . . . . 4
Global Financial Markets . . . . . . . . . . . . . . . . . . . . 5
US Key Interest Rates . . . . . . . . . . . . . . . . . . . . . . 10
US Inflation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Exchange Rates . . . . . . . . . . . . . . . . . . . . . . . . . . 12
US Banking Indicators . . . . . . . . . . . . . . . . . . . . . . 13
US Employment Indicators . . . . . . . . . . . . . . . . . . . 15
US Business Activity Indicators . . . . . . . . . . . . . . . . 17
S&P 500 Sentiment Analysis . . . . . . . . . . . . . . . . . . 18
US Consumption Indicators . . . . . . . . . . . . . . . . . . 21
US Housing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Global Business Indicators . . . . . . . . . . . . . . . . . . . 24
Global Trade/Export Metrics . . . . . . . . . . . . . . . . . 26
Canadian Indicators . . . . . . . . . . . . . . . . . . . . . . . 27
European Indicators . . . . . . . . . . . . . . . . . . . . . . . 29
Chinese Indicators . . . . . . . . . . . . . . . . . . . . . . . . 31
Global Climate Data . . . . . . . . . . . . . . . . . . . . . . . 32
Where We Are Now
Welcome back to the Global Economics Report. We’ve made a fewchanges to the report – in particular two new features: sentiment anal-ysis (p. 18) and a US economic heartbeat (p. 4). We’ll be making morechanges over the next few months.
Sentiment analysis is a technique that tries to use machine learningto determine the sentiment, positive or negative, of a block of text.In this case, we’re using conference call transcripts for the S&P 500companies. We’re presenting the sentiment of the conference calls (ie.was it an upbeat or downbeat conference call) and plotting that againstoperating earnings for each component. There seems to be a good cor-relation between the two – and as we have much more conference calldata, which is updated more often, this is a good predictor of earningstrends.
The US Economic Heartbeat is a tool for summarizing the positionof the US economy. We’ve been able to get a good monthly dataset
of various measures of the economy and have pulled out the businesscycle component of the data. The tracker shows a consistent patternwhen we are in the midst of a recession – right now the economy feels asthough it could go either way, but when it does break, this tool shouldhelp to identify it as early as possible.
The usual metrics are also presented. One new metric is bank char-geoffs (p. 14) – a measure of bad debts for banks. It is showing a stronguptick in the recent data, which is usually an indicator that somethingis wrong in consumerland.
More to come... and welcome back.Formatting Notes The grey bars on the various charts are OECD
recession indicators for the respective countries.Subscription Info For a FREE subscription to this monthly re-
port, please visit sign up at our website: www.lairdresearch.com
Laird Research, April 14, 2017
Indicators for US Economy
Leading indicators are indicators that usually change before theeconomy as a whole changes. They are useful as short-term predictorsof the economy. Our list includes the Philly Fed’s Leading Index whichsummarizes multiple indicators; initial jobless claims and hours worked(both decrease quickly when demand for employee services drops and
vice versa); purchasing manager indicies; trucking indices showing de-mand for transport; new order and housing permit indicies and con-sumer sentiment (how consumers are feeling about their own financialsituation and the economy in general). Red dots are points where anew trend has started.
Leading Index for the US
Inde
x: E
st. 6
mon
th g
row
th
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−2
−1
01
23
median: 1.50Dec 2016: 1.17
Growth
Contraction
Initial Unemployment Claims
1000
's o
f Cla
ims
per
Wee
k
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
200
300
400
500
600
median: 346.62Apr 2017: 247.25
Manufacturing Ave. Weekly Hours Worked
Hou
rs w
orke
d pe
r W
eek
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
3940
4142
4344 median: 40.60
Mar 2017: 41.80
Manfacturing − PMI
Inde
x: S
tead
y S
tate
= 5
0
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
3040
5060
70 median: 52.70Mar 2017: 53.30expanding economy
contracting economy
www.lairdresearch.com April 14, 2017 Page 2
Leading indicators are indicators that usually change before theeconomy as a whole changes. They are useful as short-term predictorsof the economy. Our list includes the Philly Fed’s Leading Index whichsummarizes multiple indicators; initial jobless claims and hours worked(both decrease quickly when demand for employee services drops and
vice versa); purchasing manager indicies; trucking indices showing de-mand for transport; new order and housing permit indicies and con-sumer sentiment (how consumers are feeling about their own financialsituation and the economy in general). Red dots are points where anew trend has started.
Durable Goods: Manufacturers New Orders
Bill
ions
of D
olla
rs
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
150
200
250
median: 186.49Feb 2017: 235.96
Index of Truck Tonnage
Inde
x
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
100
110
120
130
140
median: 113.50Feb 2017: 138.40
Capex (ex. Defense & Planes)
Bill
ions
of D
olla
rs
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
4050
6070
median: 58.58Feb 2017: 64.74
U. Michigan: Consumer Sentiment
Inde
x 19
66 Q
1 =
100
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
5060
7080
9010
011
0
median: 89.10Mar 2017: 96.90
www.lairdresearch.com April 14, 2017 Page 3
US Economic Heartbeat
MarketHack Inc. is proud to present our proprietary EconomicHeartbeat index. It uses monthly economic data from 1960 onwardsto create a diffusion index. Each point represents the index value fora given month. Months with a recession are represented by red dots,otherwise they are blue.
The green line is selected to maximize the probability that dots
above the line indicate a recession – especially as it crosses the line.Our current month is shown in Purple at the far right of the series.
The index is based on such as: incomes, employment, industrial pro-duction, prices, housing, orders and inventories and credit/monetarypolicy.
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
Good Times
Danger Zone
Rec
essi
on
Recovery
Rec
essi
on
Recovery
Rec
essi
on
Recovery
Rec
essi
on Recovery
Rec
essi
on
Recovery
Rec
essi
on
Recovery
Rec
essi
on
Recovery YOU
AREHERE
Recession monthsNon−recession monthsCurrent month (Jan 2017)
www.lairdresearch.com April 14, 2017 Page 4
Global Financial Markets
Global Stock Market Returns
Country Index Name Close Date CurrentValue
WeeklyChange
MonthlyChange
3 monthChange
12month
Change
Corr toS&P500
Corr toTSX
North AmericaUSA S&P 500 Apr 13 2,328.9 -1.2% t -1.9% t 2.4% s 11.8% s 1.00 0.66USA NASDAQ Composite Apr 13 5,805.1 -1.3% t -1.2% t 4.1% s 17.3% s 0.89 0.58USA Wilshire 5000 Total Market Apr 13 24,262.6 -1.2% t -1.6% t 1.9% s 13.0% s 0.96 0.66Canada S&P TSX Apr 13 15,535.5 -1.0% t -0.1% t 0.2% s 13.6% s 0.66 1.00Europe and RussiaFrance CAC 40 Apr 13 5,071.1 -1.0% t 1.4% s 3.0% s 12.9% s 0.62 0.53Germany DAX Apr 13 12,109.0 -1.0% t 1.0% s 4.1% s 20.8% s 0.61 0.50Russia Market Vectors Russia ETF Apr 13 20.1 -5.7% t 0.9% s -6.5% t 18.5% s 0.42 0.53AsiaTaiwan TSEC weighted index Apr 13 9,836.7 -0.6% t 1.4% s 4.9% s 13.7% s -0.09 0.01China Shanghai Composite Index Apr 13 3,276.0 -0.2% t 1.2% s 5.2% s 6.8% s 0.06 0.05Japan NIKKEI 225 Apr 13 18,426.8 -0.9% t -6.1% t -4.5% t 12.5% s 0.27 0.28Hong Kong Hang Seng Apr 13 24,261.7 -0.0% t 1.8% s 5.8% s 14.7% s -0.06 0.04Korea Kospi Apr 13 2,148.6 -0.2% t 1.5% s 3.5% s 6.6% s -0.03 -0.07South Asia and AustrailiaIndia Bombay Stock Exchange Apr 13 29,461.4 -1.6% t 0.1% s 8.2% s 15.0% s 0.04 -0.04Indonesia Jakarta Apr 13 5,616.5 -1.1% t 3.8% s 6.5% s 15.7% s -0.13 0.01Malaysia FTSE Bursa Malaysia KLCI Apr 13 1,738.2 -0.1% t 0.9% s 3.9% s 0.9% s 0.03 0.13Australia All Ordinaries Apr 13 5,925.9 0.5% s 2.3% s 2.6% s 15.6% s 0.10 0.16New Zealand NZX 50 Index Gross Apr 13 7,229.8 -0.8% t 0.5% s 2.6% s 6.7% s 0.02 0.09South AmericaBrasil IBOVESPA Apr 13 62,826.0 -2.2% t -4.1% t -1.3% t 18.2% s 0.35 0.49Argentina MERVAL Buenos Aires Apr 12 20,812.2 0.6% s 8.5% s 11.9% s 64.0% s 0.24 0.51Mexico Bolsa index Apr 12 48,955.8 -0.5% t 3.9% s 6.3% s 8.6% s 0.34 0.41MENA and AfricaEgypt Market Vectors Egypt ETF Apr 13 28.3 -1.2% t 1.1% s 3.4% s -27.1% t 0.07 0.14(Gulf States) Market Vectors Gulf States ETF Oct 07 23.0 3.2% s 1.2% s 6.4% s -6.4% t 0.16 0.05South Africa iShares MSCI South Africa Index Apr 13 57.2 5.4% s 0.8% s 3.0% s 8.7% s 0.42 0.44(Africa) Market Vectors Africa ETF Apr 13 21.3 2.0% s 3.5% s 1.2% s 11.7% s 0.31 0.35CommoditiesUSD Spot Oil West Texas Int. Apr 10 $53.1 5.6% s 10.4% s 4.4% s 31.1% s 0.16 0.41USD Gold LME Spot Apr 13 $1,286.1 2.6% s 6.5% s 7.5% s 3.2% s -0.17 -0.14
Note: Correlations are based on daily arithmetic returns for the most recent 100 trading days.
www.lairdresearch.com April 14, 2017 Page 5
S&P 500 Composite Index
The S&P 500 Composite Index is widely regarded as the best singlegauge of the large cap U.S. equities market. A key figure is the valua-tion level of the S&P500 as measured by the Price/Earnings ratio. Wepresent two versions: (1) a 12-month trailing earnings version which
reflects current earnings but is skewed by short term variances and (2)a cyclically adjusted version which looks at the inflation adjusted earn-ings over a 10 year period (i.e. at least one business cycle). Forecastedearnings numbers are estimates provided by S&P.
S&P 500 Profit Margins and Overall Corporate Profit Margins (Trailing 12 months)
Per
cent
63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
02468
101214
02468101214
Per
cent
Total Corporate Profits (% of GDP) − median: 6.2%, Q4/16: 9.2%Net Profit Margin (S&P 500 Earnings / Revenue) − median: 6.7%, Q4/16: 8.2%
S&P Quarterly Earnings (USD$ Inflation Adjusted to current prices)
63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18E
stim
ates
−5.00 0.00 5.0010.0015.0020.0025.0030.0035.0040.0045.00
−5.00 0.00 5.0010.0015.0020.0025.0030.0035.0040.0045.00
Tech BubbleJapanese Asset Bubble
House BubbleAsian Financial Crisis
US Financial Crisis
Eurozone crisis
Oil Crisis I Oil Crisis II
Gulf WarSavings and Loans Crisis
High Inflation Period
Afganistan/Iraq WarVietnam War
Reported EarningsOperating Earnings
Trailing P/E Ratios for S&P500
63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
0
10
20
30
40
50
0
10
20
30
40
50
Mul
tiple
Mul
tiple
12−month trailing P/E ( median = 17.5, Apr = 23.2)10−year CAPE ( median = 19.7, Apr = 28.6)
www.lairdresearch.com April 14, 2017 Page 6
S&P 500 Composite Distributions
This is a view of the price performance of the S&P 500 companies.The area of each box is proportional to the market cap, while the colour
is determined by the percentage change in value over the past month.Companies are sorted according to their industry group.
AAPL+0.9%
GOOG−1.4%
MSFT+0.015%
FB+1.4%
V−0.13%
ORCL+3%
INTC−1.9%
CSCO−5%
IBM−6.8%
MA AVGO
QCOM
TXN ACN
ADBE NFLX
CRM
NVDA
ADP
CTSH
HPQ
HPE
MU
EA
FIS
GLW APH
RHT
STX
ADS
CA
IT
BRK−B−8.1%
JPM−9.3%
WFC−14%
BAC−12%
C−5.7%
GS USB
MS−13%
AXP
CB
BLK
AIG
MET
PNC
BK PRU
CME COF
MMC
BBT TRV
SPGI AON
STT ALL
AFL
SYFSTI
MCO
AMP
RF
L
IVZ
AJG
JNJ+0.91%
PFE−1.6%
MRK−4.8%
UNH−1.4%
AMGN−9.3%
MDT−2%
ABBV
CELG LLY BMY
GILD−4.5%
AGN−3%
ABT
TMO
DHR
BIIB
SYK
AET
ANTM
BDX
CI
BSX
ZBH
MYL
EW
ABC
BCRA
LH
WAT
MTD
CNC
AMZN+3.7%
DIS+1.9%
CMCSA
HD+0.08%
MCD
NKE
CHTR+1.5%
PCLN+0.32%
TWX
LOW
FOX
GM
TJX
F
CCL
MAR
TGT CBS
ROST
ORLY
YUM
NWL
OMC
DG
VIAB
LB
DHI
DRI
M
HBI
PG−1.8%
WMT+4.6%
KO+2.4%
PM+3.5%
PEP+2.7%
MO−4.9%
KHC RAI
WBA
CVS COST
MDLZ CL
KMB
STZ
GIS EL
KR
MNST
K
TSN
HSY
TAP
CPB
CLX
GE−2.1%
MMM
BA−4.5%
HON−3.7%
UPS UTX
UNP
LMT GD
CAT FDX
ITW RTN CSX
NOC JCI
DE
LUV
ETN
DAL
WMCMI
PCAR
IR ROP
PH
ROK
AYI
XOM−1.6%
CVX−6.8%
SLB−5%
COP
EOG
OXY
KMI
HAL
PSXPXD
VLO
BHI
NEE
DUK
SO
D
PCG EXC AEP
EIX PPL
ED
SPG
AMT
PSA
CCI
PLD
EQIX
WY
AVB
VTR
BXP O
KIM
DOW DD
ECL LYB PX
PPG
IP
VMC
MLM
BLL
IFF
T−3%
VZ−1.2%
LVLT CTL
Information Technology Financials
Health Care
ConsumerDiscretionary
ConsumerStaples
Industrials
Energy Utilities
Real Estate
MaterialsTelecommunication
Services
<−25.0% −20.0% −15.0% −10.0% −5.0% 0.0% 5.0% 10.0% 15.0% 20.0% >25.0%
% Change in Price from Mar 1, 2017 to Apr 13, 2017
Average Median Median MedianSector Change P/Sales P/Book P/EUtilities 1.5% s 2.2 2.0 21.6Real Estate 0.7% s 8.7 2.8 31.2Consumer Staples 0.0% s 2.6 4.8 25.0Consumer Discretionary -0.2% t 1.6 3.7 18.7Information Technology -0.9% t 3.7 5.0 26.4Health Care -1.7% t 3.7 4.0 27.3
Average Median Median MedianSector Change P/Sales P/Book P/ETelecommunication Services -1.8% t 1.5 2.0 20.5Materials -3.2% t 1.9 4.1 26.5Industrials -3.7% t 1.8 4.2 23.4Energy -3.8% t 3.4 2.0 22.6Financials -8.7% t 2.9 1.5 16.3
www.lairdresearch.com April 14, 2017 Page 7
US Equity Valuations
A key valuation metric is Tobin’s q: the ratio between the marketvalue of the entire US stock market versus US net assets at replacementcost (ie. what you pay versus what you get). Warren Buffet famouslyfollows stock market value as a percentage of GNP, which is highly(93%) correlated to Tobin’s q.
We can also take the reverse approach: assume the market hasvaluations correct, we can determine the required returns of future es-
timated earnings. These are quoted for both debt (using BBB ratedsecurities as a proxy) and equity premiums above the risk free rate (10year US Treasuries). These figures are alternate approaches to under-standing the current market sentiment - higher premiums indicate ademand for greater returns for the same price and show the level ofrisk-aversion in the market.
Tobin's q (Market Equity / Market Net Worth) and S&P500 Price/Sales
63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
0.25
0.50
0.75
1.00
1.25
1.50
1.75
0.25
0.50
0.75
1.00
1.25
1.50
1.75
Buying assets at a discount
Paying up for growth
Tobin Q (median = 0.77, Dec = 1.00)S&P 500 Price/Sales (median = 1.37, Dec = 1.95)
Equity and Debt Risk Premiums: Spread vs. Risk Free Rate (10−year US Treasury)
63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%Implied Equity Premium (median = 4.1%, Apr = 4.5%)Debt (BBB) Premium (median = 1.6%, Apr = 1.4%)Debt (BAA) Premium [Discontinued Series]
www.lairdresearch.com April 14, 2017 Page 8
US Mutual Fund Flows
Fund flows describe the net investments in equity and bond mutualfunds as well as ETF’s in the US market, as described in ICI’s “Trendsin Mutual Fund Investing” report. Previously we just looked at mutual
fund flows, but with the global trend to ETF’s, this only presented apartial picture.
US Net New Investment Cash Flow to Mutual Funds & ETFs
US
$ bi
llion
s (m
onth
ly)
2014 2015 2016 2017
−40
−20
020
40
Domestic EquityWorld EquityTaxable BondsMunicipal Bonds
US Net New Investment Cash Flow to Mutual Funds & ETFs
US
$ bi
llion
s (M
onth
ly)
2014 2015 2016 2017
−60
−40
−20
020
4060
Flows to EquityFlows to BondsNet Market Flows
www.lairdresearch.com April 14, 2017 Page 9
US Key Interest Rates
Interest rates are often leading indicators of stress in the financialsystem. The yield curve show the time structure of interest rates ongovernment bonds - Usually the longer the time the loan is outstanding,the higher the rate charged. However if a recession is expected, thenthe fed cuts rates and this relationship is inverted - leading to negativespreads where short term rates are higher than long term rates.
Almost every recession in the past century has been preceeded by an
inversion - though not every inversion preceeds a recession (just mostof the time).
For corporate bonds, the key issue is the spread between bond rates(i.e. AAA vs BBB bonds) or between government loans (LIBOR vsFedfunds - the infamous “TED Spread”). Here a spike correlates to anaversion to risk, which is an indication that something bad is happen-ing.
US Treasury Yield Curves
For
war
d In
stan
tane
ous
Rat
es (
%)
16 17 18 19 20 21 22 23 24 25 26 27
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0.0
0.5
1.0
1.5
2.0
2.5
3.0Apr 12, 2017 (Today)Mar 13, 2017 (1 mo ago)Jan 12, 2017 (3 mo ago)12 Apr 2016 (1 yr ago)
3 Month & 10 Yr Treasury Yields
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
0%
1%
2%
3%
4%
5%
6%
7%
0%
1%
2%
3%
4%
5%
6%
7%10 Yr Treasury3 Mo TreasurySpread
AAA vs. BBB Bond Spreads
2%3%4%5%6%7%8%9%
10%
2%3%4%5%6%7%8%9%10%
Per
cent
AAABBB
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
median: 112.00Apr 2017: 66.00
0100200300400
0100200300400
Spr
ead
(bps
)
LIBOR vs. Fedfunds Rate
0%
1%
2%
3%
4%
5%
6%
7%
0%
1%
2%
3%
4%
5%
6%
7%
Per
cent
3 mos t−billLIBOR
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
median: 36.61Apr 2017: 34.54
0100200300
0100200300
Spr
ead
(bps
)
www.lairdresearch.com April 14, 2017 Page 10
US Inflation
Generally, the US Fed tries to anchor long run inflation expectationsto approximately 2%. Inflation can be measured with the ConsumerPrice Index (CPI) or the Personal Consumption Expenditures (PCE)index.
In both cases, it makes sense to exclude items that vary quickly likeFood and Energy to get a clearer picture of inflation (usually called
Core Inflation). The Fed seems to think PCI more accurately reflectsthe entire basket of goods and services that households purchase.
Finally, we can make a reasonable estimate of future inflation ex-pectations by comparing real return and normal bonds to construct animputed forward inflation expectation. The 5y5y chart shows expected5 year inflation rates at a point 5 years in the future. Neat trick that.
Consumer Price Index
Per
cent
84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
−1%
0%
1%
2%
3%
4%
5%
6%
−1%
0%
1%
2%
3%
4%
5%
6%
US Inflation Rate YoY% (Aug = 1.1%)US Inflation ex Food & Energy YoY% (Aug = 2.3%)
Personal Consumption Expenditures
Per
cent
(Ye
ar o
ver
Year
)
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−1
01
23
45
6
PCE Inflation Rate YoY% (Aug = 0.96%)PCE Core Inflation YoY% (Aug = 1.7%)
5−Year, 5−Year Forward Inflation Expectation Rate
Per
cent
07 08 09 10 11 12 13 14 15 16 17 18 19 20 21
−1
01
23
45
6
5 year forward Inflation ExpectationActual 5yr Inflation (CPI measure)Actual 5yr Inflation (PCE Measure)
www.lairdresearch.com April 14, 2017 Page 11
Exchange Rates
10 Week Moving Average CAD Exchange Rates
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
0.62
0.71
0.81
0.90
1.00
1.09
US
A /
CA
D
0.55
0.61
0.66
0.72
0.77
0.82
Eur
o / C
AD
59.
16 7
4.71
90.
2610
5.81
121.
3613
6.91
Japa
n / C
AD
0.38
0.44
0.49
0.55
0.61
0.67
U.K
. / C
AD
0.59
1.10
1.60
2.11
2.61
3.12
Bra
zil /
CA
D
CAD Appreciating
CAD Depreciating
Change in F/X: Aug 1 2016 to Sep 30 2016(Trade Weighted Currency Index of USD Trading Partners)
−3.0%
−1.5%
1.5%
3.0%
Euro−0.7%
UK 1.3%
Japan−1.2%
South Korea−0.9%
China 0.2%
India−0.3%
Brazil−0.8%
Mexico 2.5%
Canada−0.0%
USA 0.2%
Country vs. Average
AppreciatingDepreciating
% Change over 3 months vs. Canada
<−10.0% −8.0% −6.0% −4.0% −2.0% 0.0% 2.0% 4.0% 6.0% 8.0% >10.0%
CAD depreciatingCAD appreciating
ARG−5.4%
AUS 4.4%
BRA 7.6%
CHN 1.6%
IND 3.9%
RUS 2.4%
USA 3.0%
EUR1.6%
JPY6.0%
KRW6.9%
MXN−3.1%
ZAR10.3%
www.lairdresearch.com April 14, 2017 Page 12
US Banking Indicators
The banking and finance industry is a key indicator of the healthof the US economy. It provides crucial liquidity to the economy in theform of credit, and the breakdown of that system is one of the exac-erbating factors of the 2008 recession. Key figures to track are the
Net Interest Margins which determine profitability (ie. the differencebetween what a bank pays to depositors versus what the bank is paidby creditors), along with levels of non-performing loans (i.e. loan lossreserves and actual deliquency rates).
US Banks Net Interest Margin
3.0
3.5
4.0
4.5
median: 3.93Oct 2016: 3.05
Repos Outstanding with Fed. Reserve
Bill
ions
of D
olla
rs
020
040
060
0
median: 62.03Apr 2017: 357.43
Bank ROE − Assets between $300M−$1B
Per
cent
05
1015
median: 12.68Oct 2016: 9.93
Consumer Credit Outstanding
% Y
early
Cha
nge
−5
05
1015
20
median: 7.41Feb 2017: 6.31
Total Business Loans%
Yea
rly C
hang
e
−20
010
20median: 8.63Feb 2017: 5.39
US Nonperforming Loans
12
34
5
median: 1.95Oct 2016: 1.39
St. Louis Financial Stress Index
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−1
12
34
5 median: −0.001Apr 2017: −1.37
Commercial Paper Outstanding
Trill
ions
of D
olla
rs
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
1.0
1.4
1.8
2.2
median: 1.31Apr 2017: 0.98
Residential Morgage Delinquency Rate
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
24
68
10
median: 2.36Oct 2016: 4.15
www.lairdresearch.com April 14, 2017 Page 13
US Charge-Off Indication
A “charge-off” is an accounting declaration by a creditor that aparticular debt is unlikely to be collected, either in whole or in part.Usually, the creditor is severely delinquent by the time this determina-tion is made. For credit card debt, as an example, this determinationis usually made by the bank after six months without payment.
However, there are charge-offs for a number of different kinds of
loans and increasing charge-offs are an important barometer of thehealth of creditors. In this graph, the various charge-offs are presentedas a percentage of total relevant debt outstanding. For example, creditcard charge-offs as a percentage of total credit card debt owed by con-sumers.
Charge−off Rates for Various Categories (Seasonally Adjusted)
85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
Per
cent
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
10.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
10.0%
3.56%
2.12%
0.47%0.39%0.07%0.01%
Credit Card Loans − All Commercial Banks (median: 4.25%, last: 3.56%)Consumer Loans − All Commercial Banks (median: 2.26%, last: 2.12%)All Loans − All Commercial Banks (median: 0.80%, last: 0.47%)Commercial and Industrial Loans (median: 0.66%, last: 0.39%)Single Family Residential Mortgages (median: 0.17%, last: 0.07%)Commercial Real Estate Loans (Ex− Farmland) (median: 0.16%, last: 0.01%)
www.lairdresearch.com April 14, 2017 Page 14
US Employment Indicators
Unemployment rates are considered the “single best indicator ofcurrent labour conditions” by the Fed. The pace of payroll growth ishighly correlated with a number of economic indicators.Payroll changesare another way to track the change in unemployment rate.
Unemployment only captures the percentage of people who are inthe labour market who don’t currently have a job - another measure
is what percentage of the whole population wants a job (employed ornot) - this is the Participation Rate.
The Beveridge Curve measures labour market efficiency by lookingat the relationship between job openings and the unemployment rate.The curve slopes downward reflecting that higher rates of unemploy-ment occur coincidentally with lower levels of job vacancies.
Unemployment Rate
Per
cent
79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
median: 6.10Mar 2017: 4.504
56789
1011
4567891011
Per
cent
Beveridge Curve
Unemployment Rate
Hel
p W
ante
d In
dex
3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 11.0
30
40
50
60
70
80
90
100
1101950's1960's1970's1980's1990's2000's2010's
Participation Rate
Per
cent
of P
op.
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
6364
6566
67
median: 66.00Mar 2017: 63.00
Total Nonfarm Payroll Change
Mon
thly
Cha
nge
(000
s)
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−50
00
500
median: 164Mar 2017: 98
www.lairdresearch.com April 14, 2017 Page 15
There are a number of other ways to measure the health of employ-ment. The U6 Rate includes people who are part time that want afull-time job - they are employed but under-utilitized. Temporary helpdemand is another indicator of labour market tightness or slack.
The large chart shows changes in private industry employment lev-els over the past year, versus how well those job segments typically pay.Lots of hiring in low paying jobs at the expense of higher paying jobsis generally bad, though perhaps not unsurprising in a recovery.
Median Duration of Unemployment
Wee
ks
510
1520
25 median: 8.90Mar 2017: 10.30
(U6) Unemployed + PT + Marginally Attached
Per
cent
810
1214
16
median: 9.70Mar 2017: 8.90
4−week moving average of Initial Claims
Jan
1995
= 1
00
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
5010
015
020
0
median: 106.57Apr 2017: 76.02
Unemployed over 27 weeks
Mill
ions
of P
erso
ns
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
01
23
45
67
median: 0.82Mar 2017: 1.76
Services: Temp Help
Mill
ions
of P
erso
ns
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
1.5
2.0
2.5
3.0
median: 2.29Mar 2017: 3.00
0 200 400 600
15
20
25
30
35
40
Annual Change in Employment Levels (000s of Workers)
Ave
rage
wag
es (
$/ho
ur)
Private Industry Employment Change (Mar 2016 − Mar 2017)
ConstructionDurable Goods
Education
Financial Activities
Health Services
Information
Leisure and Hospitality
Manufacturing
Mining and Logging
Nondurable GoodsOther Services
Professional &Business Services
Retail Trade
Transportation
Utilities
Wholesale Trade
Circle size relative to total employees in industry
www.lairdresearch.com April 14, 2017 Page 16
US Business Activity Indicators
Business activity is split between manufacturing activity and non-manufacturing activity. We are focusing on forward looking business
indicators like new order and inventory levels to give a sense of thecurrent business environment.
Manufacturing: Real Output
YoY
Per
cent
Cha
nge
−10
010
20
median: 7.87Oct 2016: 3.26
Manufacturing − PMI
3540
4550
5560
Mar 2017: 53.30
manufac. expanding
manufac. contracting
Manufacturers' Durable Goods Orders
Bill
ions
of D
olla
rs
150
200
250
Feb 2017: 235.96
Increase in new orders
Decrease in new orders
Non−Manufac. New Orders: Capital Goods
Bill
ions
of D
olla
rs
4050
6070
median: 58.58Feb 2017: 64.74
Average Weekly Hours: Manufacturing
3940
4142
43
median: 41.20Mar 2017: 41.80
Industrial Production: Manufacturing
YoY
Per
cent
Cha
nge
−15
−5
05
10
median: 2.86Feb 2017: 1.50
Inventory to Sales Ratio
Rat
io
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
1.1
1.2
1.3
1.4
1.5
1.6
median: 1.37Jan 2017: 1.35
Chicago Fed: Sales, Orders & Inventory
Inde
x
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−0.
50.
00.
5 Feb 2017: 0.08Above ave growth
Below ave growth
Freight Index
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
9510
511
512
5
Feb 2017: 126.40
www.lairdresearch.com April 14, 2017 Page 17
S&P 500 Sentiment Analysis
Sentiment analysis tries to determine the attitude of a speaker withrespect to some topic or the overall contextual polarity of a document.In this particular case, we are evaluating earnings conference calls forthe S&P 500 companies over the past 10 years.
We use a proprietary sentiment mining model to determine the“sen-timent” from the transcripts of 17,948 conference calls. The object is
to understand how the communication from executives on those con-ference calls changes over time.
The model focuses on “relative sentiment” – the tone relative to thearbitrary date of January 2012. While it is not an exact science, themodels do capture the significant negative sentiment in 2007-2008 andthe subsequent recovery.
−15
00−
500
050
015
00
Normalized Sentiment (Based on 17,948 Earnings Calls)
Sen
timen
t Val
ue (
Inde
x Ja
n 20
12 =
0)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
CDCD: +941
CS
CS: +853
En
En: +662
Fin
Fin: +688
HC HC: +348
Ind
Ind: +759
IT
IT: +715
Mat
Mat: +906
RE
RE: +801
Tel
Tel: +1101
UtUt: +730
(CD) Consumer Discretionary(CS) Consumer Staples(En) Energy(Fin) Financials(HC) Health Care(Ind) Industrials
(IT) Information Technology(Mat) Materials(RE) Real Estate(Tel) Telecommunications Services(Ut) UtilitiesS&P 500
Sentiment Increasing
Sentiment Decreasing
−10
00
100
200
Month over Month Sentiment Change − Apr 2017
+72+49
+88 +98
+5
+162
+69+23
+103 +98
+2
ConsumerDiscretionary
ConsumerStaples Energy Financials
HealthCare Industrials
InformationTechnology Materials
RealEstate
TelecommunicationsServices Utilities
www.lairdresearch.com April 14, 2017 Page 18
S&P 500 Sentiment (n = 17,948)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$−1.00$0.00
$4.00
$9.00
$14.00
$19.00
$24.00
$29.00
$34.00
$39.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Consumer Discretionary (n = 2,985)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$0.00
$1.00
$3.00
$5.00
$7.00
$9.00
$11.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Consumer Staples (n = 1,345)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$5.00
$7.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Energy (n = 1,326)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$−9.00
$−4.00
$0.00$1.00
$6.00
$11.00
$16.00
$21.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Financials (n = 2,169)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$−14.00
$−9.00
$−4.00
$0.00$1.00
$6.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Health Care (n = 2,233)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$7.00
$9.00
$11.00
$13.00
$15.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
www.lairdresearch.com April 14, 2017 Page 19
Industrials (n = 2,318)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$3.00
$5.00
$7.00
$9.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Information Technology (n = 2,435)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$4.00
$6.00
$8.00
$10.00
$12.00
$14.00
$16.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Materials (n = 916)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$−3.00
$−1.00
$0.00
$1.00
$3.00
$5.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Real Estate (n = 990)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$−1.00
$−0.50
$0.00
$0.50
$1.00
$1.50
$2.00
$2.50
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Telecommunications Services (n = 252)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$−3.00
$−1.00
$0.00
$1.00
$3.00
$5.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
Utilities (n = 979)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
−1500
−1000
−500
0
500
1000
1500
2000
$0.00
$2.00
$4.00
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)
www.lairdresearch.com April 14, 2017 Page 20
US Consumption Indicators
Variations in consumer activity are a leading indicator of thestrength of the economy. We track consumer sentiment (their expec-
tations about the future), consumer loan activity (indicator of newpurchase activity), and new orders and sales of consumer goods.
U. Michigan: Consumer Sentiment
Inde
x 19
66 Q
1 =
100
5060
7080
9011
0
median: 89.10Mar 2017: 96.90
Consumer Loans (All banks)
YoY
% C
hang
e
−10
010
2030
40
median: 7.63Feb 2017: 6.92
AccountingChange
Deliquency Rate on Consumer Loans
Per
cent
age
2.0
3.0
4.0
median: 3.42Oct 2016: 2.15
New Orders: Durable Consumer Goods
YoY
% C
hang
e
−20
020
median: 4.35Feb 2017: −4.20
New Orders: Non−durable Consumer Goods
YoY
% C
hang
e
−20
010
20
median: 3.75Feb 2017: 13.36
Personal Consumption & Housing Index
Inde
x
−0.
40.
00.
20.
4
median: 0.02Feb 2017: −0.03above ave growth
below ave growth
Light Cars and Trucks Sales
Mill
ions
of U
nits
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
1012
1416
1820
22
median: 14.91Mar 2017: 16.53
Personal Saving Rate
Per
cent
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
24
68
10
median: 5.70Feb 2017: 5.60
Retail Food and Service Sales
YoY
% C
hang
e (R
eal)
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−10
−5
05
median: 2.45Feb 2017: 2.79
www.lairdresearch.com April 14, 2017 Page 21
US Housing
Housing construction is only about 5-8% of the US economy, how-ever a house is typically the largest asset owned by a household. Sincepersonal consumption is about 70% of the US economy and house val-ues directly impact household wealth, housing is an important indicatorin the health of the overall economy. In particular, housing investment
was an important driver of the economy getting out of the last fewrecessions (though not this one so far). Here we track housing pricesand especially indicators which show the current state of the housingmarket.
15 20 25 30 35 40
150
200
250
300
Personal Income vs. Housing Prices (Inflation adjusted values)
New
Hom
e P
rice
(000
's)
Disposable Income Per Capita (000's)
February 2017
r2 : 89.9%Range: Jan 1962 − Feb 2017Blue dots > +5% change in next yearRed dots < −5% change in next year
New Housing Units Permits Authorized
Mill
ions
of U
nits
0.5
1.0
1.5
2.0
2.5
median: 1.33Feb 2017: 1.22
New Home Median Sale Price
Sal
e P
rice
$000
's
100
200
300
Feb 2017: 296.20
Homeowner's Equity Level
Per
cent
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
4050
6070
80 median: 66.50Oct 2016: 57.80
New Homes: Median Months on the Market
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
46
810
1214 median: 4.90
Feb 2017: 3.40
US Monthly Supply of Homes
Mon
ths
Sup
ply
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
46
810
12 median: 5.80Feb 2017: 5.40
www.lairdresearch.com April 14, 2017 Page 22
US Housing - FHFA Quarterly Index
The Federal Housing Finance Agency provides a quarterly surveyon house prices, based on sales prices and appraisal data. This gener-ates a housing index for 355 municipal areas in the US from 1979 topresent. We have provided an alternative view of this data looking atthe change in prices from the peak in the 2007 time frame.
The goal is to provide a sense of where the housing markets are
weak versus strong.The colours represent gain or losses since the startof the housing crisis (defined as the maximum price between 2007-2009for each city). The circled dots are the cities in the survey, while thebackground colours are interpolated from these points using a loesssmoother.
Change from 2007 Peak − Q2 2016
−50%
−40%
−30%
−20%
−10%
0%
10%
20%
30%
40%
50%
Today's Home Prices
Percentage Change from 2007−2009 Peak
Fre
quen
cy
−75% −50% −25% 0% 25% 50% 75%
Year over Year Change − Q2 2016
−10%
−8%
−6%
−4%
−2%
0%
2%
4%
6%
8%
10%
YoY Change in this quarter
YoY Percent Change
Fre
quen
cy
−15% −10% −5% 0% 5% 10% 15%
www.lairdresearch.com April 14, 2017 Page 23
Global Business Indicators
Global Manufacturing PMI Reports
The Purchasing Managers’ Index (PMI) is an indicator reflectingpurchasing managers’ acquisition of goods and services. An index read-ing of 50.0 means that business conditions are unchanged, a numberover 50.0 indicates an improvement while anything below 50.0 suggests
a decline. The further away from 50.0 the index is, the stronger thechange over the month. The chart at the bottom shows a moving av-erage of a number of PMI’s, along with standard deviation bands toshow a global average.
Global M−PMI − March 2017
<40.0 42.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0 >60.0
Steady ExpandingContracting
Eurozone56.2
Global PMI53.0
TWN56.2MEX
51.5
KOR48.4
JPN52.4
VNM54.6
IDN50.5
ZAF50.7
AUS57.5
BRA49.6
CAN55.5
CHN51.2
IND52.5
RUS52.4
SAU56.4
USA53.3
Global M−PMI Monthly Change
<−5.0 −4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 4.0 >5.0
PMI Change ImprovingDeteriorating
Eurozone0.8
Global PMI0.0
TWN1.7MEX
0.9
KOR−0.8
JPN−0.9
VNM0.4
IDN1.2
ZAF0.2
AUS−1.8
BRA 2.7
CAN 0.8
CHN−0.5
IND 1.8
RUS−0.1
SAU−0.6
USA−0.9
Purchase Managers Index (Manufacturing) − China, Japan, USA, Canada, France, Germany, Italy, UK, Australia
03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
3040
5060
70
3040
5060
70
Business Conditions Contracting
Business Conditions Expanding
www.lairdresearch.com April 14, 2017 Page 24
Global Manufacturing PMI Chart
This is an alternate view of the global PMI reports. Here, we lookat all the various PMI data series in a single chart and watch theirevolution over time.
Red numbers indicate contraction (as estimated by PMI) whilegreen numbers indicate expansion.
Mar
15
Apr
15
May
15
Jun
15
Jul 1
5
Aug
15
Sep
15
Oct
15
Nov
15
Dec
15
Jan
16
Feb
16
Mar
16
Apr
16
May
16
Jun
16
Jul 1
6
Aug
16
Sep
16
Oct
16
Nov
16
Dec
16
Jan
17
Feb
17
Mar
17
Australia
India
Indonesia
Viet Nam
Taiwan
China
South Korea
Japan
South Africa
Saudi Arabia
Turkey
Russia
UK
Greece
Germany
France
Italy
Czech Republic
Spain
Poland
Ireland
Netherlands
Eurozone
Brazil
Mexico
Canada
USA
Global PMI 51.7 51.0 51.2 51.0 51.0 50.7 50.7 51.3 51.2 50.7 50.9 50.0 50.6 50.1 50.0 50.4 51.0 50.8 51.0 52.0 52.1 52.7 52.7 53.0 53.0
55.7 54.1 54.0 53.6 53.8 53.0 53.1 54.1 52.8 51.2 52.4 51.3 51.5 50.8 50.7 51.3 52.9 52.0 51.5 53.4 54.1 54.3 55.0 54.2 53.3
48.9 49.0 49.8 51.3 50.8 49.4 48.6 48.0 48.6 47.5 49.3 49.4 51.5 52.2 52.1 51.8 51.9 51.1 50.3 51.1 51.5 51.8 53.5 54.7 55.5
53.8 53.8 53.3 52.0 52.9 52.4 52.1 53.0 53.0 52.4 52.2 53.1 53.2 52.4 53.6 51.1 50.6 50.9 51.9 51.8 51.1 50.2 50.8 50.6 51.5
46.2 46.0 45.9 46.5 47.2 45.8 47.0 44.1 43.8 45.6 47.4 44.5 46.0 42.6 41.6 43.2 46.0 45.7 46.0 46.3 46.2 45.2 44.0 46.9 49.6
52.2 52.0 52.2 52.5 52.4 52.3 52.0 52.3 52.8 53.2 52.3 51.2 51.6 51.7 51.5 52.8 52.0 51.7 52.6 53.5 53.7 54.9 55.2 55.4 56.2
52.5 54.0 55.5 56.2 56.0 53.9 53.0 53.7 53.5 53.4 52.4 51.7 53.6 52.6 52.7 52.0 53.2 53.5 53.4 55.7 57.0 57.3 56.5 58.3 57.8
56.8 55.8 57.1 54.6 56.7 53.6 53.8 53.6 53.3 54.2 54.3 52.9 54.9 52.6 51.5 53.0 50.2 51.7 51.3 52.1 53.7 55.7 55.5 53.8 53.6
54.8 54.0 52.4 54.3 54.5 51.1 50.9 52.2 52.1 52.1 50.9 52.8 53.8 51.0 52.1 51.8 50.3 51.5 52.2 50.2 51.9 54.3 54.8 54.2 53.5
54.3 54.2 55.8 54.5 53.6 53.2 51.7 51.3 53.1 53.0 55.4 54.1 53.4 53.5 51.8 52.2 51.0 51.0 52.3 53.3 54.5 55.3 55.6 54.8 53.9
56.1 54.7 55.5 56.9 57.5 56.6 55.5 54.0 54.2 55.6 56.9 55.5 54.3 53.6 53.3 51.8 49.3 50.1 52.0 53.3 52.2 53.8 55.7 57.6 57.5
53.3 53.8 54.8 54.1 55.3 53.8 52.7 54.1 54.9 55.6 53.2 52.2 53.5 53.9 52.4 53.5 51.2 49.8 51.0 50.9 52.2 53.2 53.0 55.0 55.7
48.8 48.0 49.4 50.7 49.6 48.3 50.6 50.6 50.6 51.4 50.0 50.2 49.6 48.0 48.4 48.3 48.6 48.3 49.7 51.8 51.7 53.5 53.6 52.2 53.3
52.8 52.1 51.1 51.9 51.8 53.3 52.3 52.1 52.9 53.2 52.3 50.5 50.7 51.8 52.1 54.5 53.8 53.6 54.3 55.0 54.3 55.6 56.4 56.8 58.3
48.9 46.5 48.0 46.9 30.2 39.1 43.3 47.3 48.1 50.2 50.0 48.4 49.0 49.7 48.4 50.4 48.7 50.4 49.2 48.6 48.3 49.3 46.6 47.7 46.7
54.4 51.9 52.0 51.4 51.9 51.6 51.8 55.5 52.7 51.9 52.9 50.8 50.7 49.2 50.1 52.1 48.2 53.3 55.4 54.2 53.4 56.1 55.7 54.6 54.2
48.1 48.9 47.6 48.7 48.3 47.9 49.1 50.2 50.1 48.7 49.8 49.3 48.3 48.0 49.6 51.5 49.5 50.8 51.1 52.4 53.6 53.7 54.7 52.5 52.4
48.0 48.5 50.2 49.0 50.1 49.3 48.0 49.5 50.9 52.2 50.9 50.3 49.2 48.9 49.4 47.4 47.6 47.0 48.3 49.8 48.8 47.7 48.7 49.7 52.3
60.1 58.3 57.0 56.1 57.5 58.7 56.5 55.7 56.3 54.4 53.9 54.4 54.5 54.2 54.8 54.4 56.0 56.6 55.3 53.2 55.0 55.5 56.7 57.0 56.4
51.6 51.5 50.1 49.2 48.9 49.3 47.9 47.5 49.6 49.1 49.6 49.1 47.0 47.9 50.2 49.6 49.9 49.8 50.7 50.5 50.8 51.6 51.3 50.5 50.7
50.3 49.9 50.9 50.1 51.2 51.7 51.0 52.4 52.6 52.6 52.3 50.1 49.1 48.2 47.7 48.1 49.3 49.5 50.4 51.4 51.3 52.4 52.7 53.3 52.4
49.2 48.8 47.8 46.1 47.6 47.9 49.2 49.1 49.1 50.7 49.5 48.7 49.5 50.0 50.1 50.5 50.1 48.6 47.6 48.0 48.0 49.4 49.0 49.2 48.4
49.6 48.9 49.2 49.4 47.8 47.3 47.2 48.3 48.6 48.2 48.4 48.0 49.7 49.4 49.2 48.6 50.6 50.0 50.1 51.2 50.9 51.9 51.0 51.7 51.2
51.0 49.2 49.3 46.3 47.1 46.1 46.9 47.8 49.5 51.7 50.6 49.4 51.1 49.7 48.5 50.5 51.0 51.8 52.2 52.7 54.7 56.2 55.6 54.5 56.2
50.7 53.5 54.8 52.2 52.6 51.3 49.5 50.1 49.4 51.3 51.5 50.3 50.7 52.3 52.7 52.6 51.9 52.2 52.9 51.7 54.0 52.4 51.9 54.2 54.6
46.4 46.7 47.1 47.8 47.3 48.4 47.4 47.8 46.9 47.8 48.9 48.7 50.6 50.9 50.6 51.9 48.4 50.4 50.9 48.7 49.7 49.0 50.4 49.3 50.5
52.1 51.3 52.6 51.3 52.7 52.3 51.2 50.7 50.3 49.1 51.1 51.1 52.4 50.5 50.7 51.7 51.8 52.6 52.1 54.4 52.3 49.6 50.4 50.7 52.5
46.3 48.0 52.3 44.2 50.4 51.7 52.1 50.2 52.5 51.9 51.5 53.5 58.1 53.4 51.0 51.8 56.4 46.9 49.8 50.5 54.2 55.4 51.2 59.3 57.5
www.lairdresearch.com April 14, 2017 Page 25
Global Trade/Export Metrics
The CPB Netherlands Bureau for Economic Policy Analysis pub-lishes the World Trade Monitor. The WTM summarizes worldwidemonthly data on international trade and production. Data is from a
variety of sources, which are normalized into a set of indexed curveswhich show trends in world trade.
World Imports and Exports
Inde
x: 2
010
= 1
00
99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
7080
9010
011
012
0
ExportsImports
World Exports by Region
Inde
x: 2
010
= 1
00
99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
6070
8090
100
110
120
130
USAJapanEuro Area
Latin AmericaAfrica & Middle EastEmerging Asia
www.lairdresearch.com April 14, 2017 Page 26
Canadian Indicators
Retail Trade (SA)
YoY
Per
cent
Cha
nge
−5
05
10
median: 4.61Jan 2017: 4.49
Total Manufacturing Sales Growth
YoY
Per
cent
Gro
wth
−20
−10
010
20
median: 3.56Feb 2017: 6.81
Manufacturing New Orders Growth
YoY
Per
cent
Gro
wth
−30
−10
010
2030
median: 4.01Feb 2017: 12.58
1yr vs. 10yr Canada Bond Yields
Yie
ld (
Per
cent
)
02
46
810
median: 5.54Mar 2017: 1.59
10 yr bond1 yr bond
Manufacturing PMI
4850
5254
Mar 2017: 55.50
Sales and New Orders (SA)
YoY
Per
cent
Cha
nge
−20
−10
010
20
SalesNew Orders (smoothed)
Tbill Yield Spread (10 yr − 3mo)
Spr
ead
(Per
cent
)
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−1
01
23
4
median: 1.28Mar 2017: 1.05
Inflation (total and core)
YoY
Per
cent
Cha
nge
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−1
01
23
4
median: 1.86Feb 2017: 2.05
TotalCore
Inventory to Sales Ratio (SA)
Rat
io
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
1.3
1.4
1.5
1.6
median: 1.35Feb 2017: 1.34
www.lairdresearch.com April 14, 2017 Page 27
6.6 6.8 7.0 7.2 7.4 7.6
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
Beveridge Curve (Mar 2011 − Dec 2016)
as.numeric(can.bev$ui.rate)
as.n
umer
ic(c
an.b
ev$v
acan
cies
) Mar 2011 − Dec 2012Jan 2013 − Nov 2016Dec 2016
Unemployment Rate
Job
Vac
ancy
rat
e (I
ndus
tria
l)
Ownership/Rental Price Ratio
Rat
io o
f Acc
omod
atio
n O
wne
rshi
p/R
ent R
atio
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
9010
011
012
013
014
015
0
CalgaryMontrealVancouverToronto
Note: Using prices relative to 2002 as base year
Ownership relatively moreexpensive vs 2002
Rent relatively more expensive vs 2002
Unemployment Rate (SA)
Per
cent
34
56
78
910
Canada 6.7%Alberta 8.4%Ontario 6.4%
Debt Service Ratios (SA)
Per
cent
02
46
810
Total Debt: 6.1%Mortgage: 3.0%Consumer Debt: 6.3%
Housing Starts and Building Permits (smoothed)
YoY
Per
cent
Cha
nge
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−40
−20
020
40
PermitsStarts
www.lairdresearch.com April 14, 2017 Page 28
European Indicators
Unemployment Rates
Per
cent
age
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
05
1015
2025
30
FR
DEGB
IT
GR
ES
EU
Business Employment Expectations
Inde
x
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−40
−20
010
Industrial Orderbook Levels
Inde
x
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−60
−40
−20
020
Country EmploymentExpect.
Unempl.(%)
BondYields
(%)
RetailTurnover
ManufacturingTurnover
Inflation(YoY
%)
IndustryOrder-book
PMI
Series Dates Mar 2017 Mar 2017 Mar 2017 Feb 2017 Feb 2017 Feb 2017 Mar 2017 Mar 2017� France -4.8 t 10.0 u 1.02 t 114.7 s 107.5 t 1.4 t -10.7 t 53.3 s� Germany 3.9 t 3.9 u 0.35 s NA 118.9 s 2.2 s -1.8 t 58.3 s� United Kingdom Of Great Britain And Northern Ireland 11.9 s 4.5 t 1.13 t 120.4 s NA 1.8 s 6.8 s 54.2 t� Italy 4.3 s 11.5 t 2.40 s 102.6 t NA 1.6 s -6.5 s 55.7 s� Greece 2.7 t 23.5 u 7.17 t NA NA 1.4 t -20.9 s 46.7 t� Spain 4.0 t 18.0 t 1.72 s NA NA 3.0 s -1.8 t 53.9 t� Eurozone (EU28) 4.6 s 8.0 t 1.44 u 112.8 s 115.5 s 1.9 s -4.8 u NA
www.lairdresearch.com April 14, 2017 Page 29
Government Bond YieldsLo
ng T
erm
Yie
lds
%
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
02
46
810
Economic Sentiment
Inde
x
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
6070
8090
110
130
Consumer Confidence
Inde
x
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−10
0−
60−
200
20Inflation (Harmonized Prices)
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
median: 1.90Feb 2017: 2.00
−1
0
1
2
3
4
5
6
7
Harmonized Inflation: Jan 2017
AUT 2.4%
BGR 0.9%
DEU 2.2%
ESP 3.0%
FIN 1.4%
FRA 1.4%
GBR 1.8%
GRC 1.4%
HRV 1.4%
HUN 2.9%
IRL 0.3%
ISL−0.2%
ITA 1.6%
NOR 2.7%
POL 1.9%
ROU 0.5%
SWE 1.9%
<−1.0%0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% >7.0%
YoY % Change in Prices
PMI: March 2017
<40.042.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0>60.0
Steady ExpandingContracting
BRA49.6
CAN55.5
DEU58.3
ESP53.9
FRA53.3
GBR54.2
GRC46.7
IRL53.6
ITA55.7
MEX51.5
POL53.5
SAU56.4
TUR52.3
USA53.3
RUS52.4
PMI Change: Feb − Mar
<−5.0−4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 4.0 >5.0
PMI Change ImprovingDeteriorating
CAN 0.8
DEU 1.5
ESP−0.9
FRA 1.1
GBR−0.4
GRC−1.0
IRL−0.2
ITA 0.7
POL−0.7
TUR 2.6
USA−0.9
RUS−0.1
www.lairdresearch.com April 14, 2017 Page 30
Chinese Indicators
Tracking the Chinese economy is a tricky. As reported in the Fi-nancial Times, Premier Li Keqiang confided to US officials in 2007 thatgross domestic product was “man made” and “for reference only”. In-stead, he suggested that it was much more useful to focus on three alter-native indicators: electricity consumption, rail cargo volumes and bank
lending (still tracking down that last one). We also include the PMI- which is an official version put out by the Chinese government anddiffers slightly from an HSBC version. Finally we include the ShanghaiComposite Index as a measure of stock performance.
Manufacturing PMI
99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
4045
5055
60
Mar 2017: 51.20
Shanghai Composite Index
Inde
x V
alue
(M
onth
ly H
igh/
Low
)
99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
010
0030
0050
00
Apr 2017: 3273.83
Electricity Generated
100
Mill
ion
KW
H (
log
scal
e)
99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
1000
2000
3000
5000
Feb 2017: 4657.50
Electricity GeneratedLong Term TrendShort Term Average
Consumer Confidence Index
Inde
x
99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
100
105
110
median: 104.05Feb 2017: 112.60
Exports
YoY
Per
cent
Cha
nge
99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
−20
020
4060
80
median: 17.80Mar 2017: 16.40
Retail Sales Growth
YoY
Per
cent
Cha
nge
99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
1015
20
median: 12.75Feb 2017: 9.50
www.lairdresearch.com April 14, 2017 Page 31
Global Climate Data
Temperature and precipitation data are taken from the US NationalClimatic Data Center and presented as the average monthly anomalyfrom the previous 6 months. Anomalies are defined as the difference
from the average value over the period from 1971-2000 for the tem-perature map and over the 20th century for the global temparaturechart.
Average Temperature Anomalies from Sep 2016 - Feb 2017
<−4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 >4.0Anomalies in Celsius WarmerCooler Anomalies in Celcius
−4 −2 0 2 4
Historic Global Temperature Deviations
Deg
rees
Cel
sius
Dev
iatio
ns
−0.
50.
00.
51.
0
Dec 2016: 0.79
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020
www.lairdresearch.com April 14, 2017 Page 32
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Disclaimer: This document has been prepared in good faith on the basis of information available at the date of publication without any independentverification. Laird Research Inc. collects its data from public sources which it believes to be accurate, however it does not guarantee or warrantthe accuracy, reliability, completeness or currency of the information in this publication nor its usefulness in achieving any purpose. Readers areresponsible for assessing the relevance and accuracy of the content of this publication. Laird Research Inc. will not be liable for any loss, damage,cost or expense incurred or arising by reason of any person using or relying on information in this publication.
Copyright: This publication is Copyright©2017 by Laird Research Inc. Apart from any use as permitted under the Copyright Act, no part may bereproduced in any form without written permission from Laird Research Inc. Note that the data provided herein is collected from publicly availablesources, such as the Federal Reserve Bank of St. Louis and government releases, and any copyright to that data belongs to the owners.
www.lairdresearch.com April 14, 2017 Page 33