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Laird Research - Economics
April 18, 2016
Where we are now . . . . . . . . . . . . . . . . . . . . . . . . 1
Indicators for US Economy . . . . . . . . . . . . . . . . . . . 2
Global Financial Markets . . . . . . . . . . . . . . . . . . . . 4
US Key Interest Rates . . . . . . . . . . . . . . . . . . . . . . 9
US Inļ¬‚ation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
QE Taper Tracker . . . . . . . . . . . . . . . . . . . . . . . . . 11
Exchange Rates . . . . . . . . . . . . . . . . . . . . . . . . . . 12
US Banking Indicators . . . . . . . . . . . . . . . . . . . . . . 13
US Employment Indicators . . . . . . . . . . . . . . . . . . . 14
US Business Activity Indicators . . . . . . . . . . . . . . . . 16
US Consumption Indicators . . . . . . . . . . . . . . . . . . 17
US Housing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Global Housing . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Global Business Indicators . . . . . . . . . . . . . . . . . . . 22
Canadian Indicators . . . . . . . . . . . . . . . . . . . . . . . 24
European Indicators . . . . . . . . . . . . . . . . . . . . . . . 26
Chinese Indicators . . . . . . . . . . . . . . . . . . . . . . . . 28
Global Climate Change . . . . . . . . . . . . . . . . . . . . . 29
Where we are now
The Laird Report presents a selection of economic data from around
the world to help ļ¬gure where we are today. It was originally designed
to be read on the train - 1 page per minute on my 30 minute morning
commute.
This is the time when the divergence between corporate proļ¬ts and
how individuals are actually fairing becomes visible. In the US, corpo-
rate proļ¬ts are clearly down year over year (see page 4). Given that
they were at historic highs thanks to larger than usual proļ¬t margins,
this is not particularly unusual (ie. itā€™s heading towards normalacy
rather than a collapse overall). On the other hand, inļ¬‚ation is low
(thanks oil!) and employment in the US is still strong. In a real sense,
this is more a game of catch-up as individuals have been signiļ¬cantly
trailing corporate proļ¬ts.
One area this report is deļ¬cient is in tracking the service industry.
This report heavily focuses on asset prices, employment and manufac-
turing and only indirectly looks at services. This is a weakness because
services are accounting for the bulk of GDP in most countries. For
China this is a particular weakness in our understanding of their econ-
omy as manufacturing has slowed down but there is a countervailing
force of the Chinese government pushing for an improvement on their
service sector. (Note the layoļ¬€s in the past two months of millions of
miners etc, with the view that they will be retrained for the service
sector). Ultimately we are going to have to ļ¬nd a better way to track
this part of the economy.
Global trade is still down in this report. Again, from the reading
Iā€™ve been doing, it seems that the service sector is taking up some of
the slack on this.
higher wages, more inļ¬‚ation, and higher proļ¬ts.
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 18, 2016
Indicators for US Economy
Leading indicators are indicators that usually change before the
economy as a whole changes. They are useful as short-term predictors
of the economy. Our list includes the Philly Fedā€™s Leading Index which
summarizes 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 ļ¬nancial
situation and the economy in general). Red dots are points where a
new trend has started.
Leading Index for the US
Index:Est.6monthgrowth
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’2āˆ’10123
median: 1.56
Feb 2016: 1.57
Growth
Contraction
Initial Unemployment Claims
1000'sofClaimsperWeek
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
0100300500700
median: 348.50
Apr 2016: 265.00
Manufacturing Ave. Weekly Hours Worked
HoursworkedperWeek
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
394041424344
median: 40.60
Mar 2016: 41.70
ISM Manfacturing āˆ’ PMI
Index:SteadyState=50
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
3040506070
median: 53.30
Mar 2016: 51.80expanding economy
contracting economy
www.lairdresearch.com April 18, 2016 Page 2
Leading indicators are indicators that usually change before the
economy as a whole changes. They are useful as short-term predictors
of the economy. Our list includes the Philly Fedā€™s Leading Index which
summarizes 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 ļ¬nancial
situation and the economy in general). Red dots are points where a
new trend has started.
Durable Goods: Manufacturers New Orders
BillionsofDollars
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
150200250300
median: 185.46
Feb 2016: 229.12
Index of Truck Tonnage
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
100110120130
median: 113.05
Feb 2016: 135.80
Capex (ex. Defense & Planes)
BillionsofDollars
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
40506070
median: 57.99
Feb 2016: 66.97
U. Michigan: Consumer Sentiment
Index1966Q1=100
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
5060708090100110
median: 88.80
Mar 2016: 91.00
www.lairdresearch.com April 18, 2016 Page 3
Global Financial Markets
Global Stock Market Returns
Country Index Name Close Date Current
Value
Weekly
Change
Monthly
Change
3 month
Change
12
month
Change
Corr to
S&P500
Corr to
TSX
North America
USA S&P 500 Apr 15 2,080.7 1.6% I 3.2% I 10.7% I -1.2% J 1.00 0.75
USA NASDAQ Composite Apr 15 4,938.2 1.8% I 4.4% I 10.0% I -1.5% J 0.96 0.67
USA Wilshire 5000 Total Market Apr 15 21,463.5 1.9% I 3.7% I 11.0% I -3.9% J 0.99 0.76
Canada S&P TSX Apr 15 13,637.2 1.8% I 1.8% I 13.0% I -11.7% J 0.75 1.00
Europe and Russia
France CAC 40 Apr 15 4,495.2 4.5% I 0.5% I 6.8% I -14.4% J 0.58 0.55
Germany DAX Apr 15 10,051.6 4.5% I 1.2% I 5.3% I -17.8% J 0.53 0.46
United Kingdom FTSE Apr 15 6,343.8 2.2% I 3.3% I 9.3% I -10.6% J 0.63 0.64
Russia Market Vectors Russia ETF Apr 15 16.8 2.0% I 7.7% I 35.6% I -15.3% J 0.63 0.73
Asia
Taiwan TSEC weighted index Apr 15 8,700.4 1.9% I 1.0% I 12.1% I -8.8% J 0.22 0.25
China Shanghai Composite Index Apr 15 3,078.1 3.1% I 7.5% I 6.1% I -24.6% J 0.18 0.15
Japan NIKKEI 225 Apr 15 16,848.0 6.5% I -1.6% J -1.7% J -15.2% J 0.05 0.09
Hong Kong Hang Seng Apr 15 21,316.5 4.6% I 5.1% I 9.2% I -22.8% J 0.27 0.33
Korea Kospi Apr 15 2,014.7 2.2% I 2.3% I 7.2% I -5.0% J 0.22 0.27
South Asia and Austrailia
India Bombay Stock Exchange Apr 13 25,626.8 2.9% I 3.3% I 3.1% I -11.8% J 0.40 0.41
Indonesia Jakarta Apr 15 4,823.6 -0.5% J -0.5% J 6.6% I -10.9% J 0.13 0.23
Malaysia FTSE Bursa Malaysia KLCI Apr 15 1,728.0 0.6% I 2.2% I 6.1% I -6.1% J 0.31 0.29
Australia All Ordinaries Apr 15 5,224.1 4.1% I 1.1% I 5.6% I -11.1% J 0.13 0.28
New Zealand NZX 50 Index Gross Apr 15 6,844.7 1.7% I 4.1% I 11.0% I 16.9% I 0.09 0.11
South America
Brasil IBOVESPA Apr 15 53,228.0 5.8% I 12.9% I 38.0% I -3.1% J 0.39 0.49
Argentina MERVAL Buenos Aires Apr 15 13,237.9 8.3% I 9.6% I 32.1% I 9.1% I 0.49 0.55
Mexico Bolsa index Apr 15 45,536.5 1.5% I 3.0% I 11.5% I 0.6% I 0.70 0.64
MENA and Africa
Egypt Market Vectors Egypt ETF Apr 15 38.6 -0.5% J 6.8% I 20.7% I -28.2% J 0.42 0.50
(Gulf States) Market Vectors Gulf States ETF Apr 15 22.4 1.9% I 5.4% I 17.6% I -16.5% J 0.30 0.28
South Africa iShares MSCI South Africa Index Apr 15 54.3 5.7% I 14.0% I 38.9% I -20.2% J 0.68 0.67
(Africa) Market Vectors Africa ETF Apr 15 19.6 4.0% I 4.8% I 28.9% I -24.2% J 0.59 0.71
Commodities
USD Spot Oil West Texas Int. Apr 11 $40.5 18.0% I 5.1% I 28.8% I -22.1% J 0.42 0.62
USD Gold LME Spot Apr 15 $1,229.8 -0.4% J -0.3% J 13.7% I 3.4% I 0.01 0.02
Note: Correlations are based on daily arithmetic returns for the most recent 100 trading days.
www.lairdresearch.com April 18, 2016 Page 4
S&P 500 Composite Index
The S&P 500 Composite Index is widely regarded as the best single
gauge of the large cap U.S. equities market. A key ļ¬gure is the valua-
tion level of the S&P500 as measured by the Price/Earnings ratio. We
present two versions: (1) a 12-month trailing earnings version which
reļ¬‚ects current earnings but is skewed by short term variances and (2)
a cyclically adjusted version which looks at the inļ¬‚ation adjusted earn-
ings over a 10 year period (i.e. at least one business cycle). Forecasted
earnings numbers are estimates provided by S&P.
S&P 500 Profit Margins and Overall Corporate Profit Margins (Trailing 12 months)
Percent
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
0
2
4
6
8
10
12
14
0
2
4
6
8
10
12
14
Percent
Total Corporate Profits (% of GDP) āˆ’ median: 6.2%, Q4/15: 9.0%
Net Profit Margin (S&P 500 Earnings / Revenue) āˆ’ median: 6.6%, Q4/15: 7.7%
S&P Quarterly Earnings (USD$ 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
āˆ’5.00
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
āˆ’5.00
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
Tech Bubble
Japanese Asset Bubble
House BubbleAsian Financial Crisis
US Financial Crisis
Eurozone crisis
Oil Crisis I Oil Crisis II
Gulf War
Savings and Loans Crisis
High Inflation Period
Afganistan/Iraq WarVietnam War
Reported Earnings
Operating 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
0
10
20
30
40
50
0
10
20
30
40
50
Multiple
Multiple
12āˆ’month P/E ( median = 17.4, Apr = 22.7)
10āˆ’year CAPE ( median = 19.5, Apr = 25.6)
www.lairdresearch.com April 18, 2016 Page 5
S&P 500 Composite Distributions
This is a view of the price performance of the S&P 500 index com-
panies. The area of each box is proportional to the companyā€™s market
cap, while the colour is determined by the percentage change in price
over the past month. In addition, companies are sorted according to
their industry group.
AAPL
+9.3%
GOOG
+5.6%
MSFT
+5.8%
FB
āˆ’0.16%
V
+7.3%
ORCL
+8%
INTC
+3.6%
IBM
+13%
CSCO
+4.9%
MA
+7.3%
QCOM
ACN
TXN EMC
CRM
ADP
YHOO
HPE
EBAY
INTU
ATVI
AMAT
FISV
TEL
FIS
EQIX
EA
NVDA
ADI
CA
MU
BRKāˆ’B
+4.8%
WFC
āˆ’0.96%
JPM
+5.3%
BAC
+6.5%
C
+8.8%
USB
+3.7%
GS
+2.5%
SPG AIG
AXP
BLK
MS
MET
PSA
PNC BK
CB
SCHW
COF
TRV
PRU
CME
MMC
CCI
ICE
AFL
MHFI
GGP
AVB
HCN
SYF
STT
PLD
BEN
DFS
VTR
PGR
BXP
MTB
WY
O
IVZ
L
XL
FRT
SLG
LNC
JNJ
+2.8%
PFE
+8.2%
MRK
+9.4%
GILD
+10%
UNH
+5.1%
AMGN
+7.9%
BMY
MDT
+4.5%
AGN
āˆ’27%
ABBV
+5.6%
CELG
+2.2%
LLY
ABT
+10%
BIIB
TMO
+7.6%
ESRX
REGN
SYK
AET
MCK
CI BDX
HCA
CAH
BSX
ZTS
ZBH
EW
A WAT
AMZN
+8.1%
HD
+8%
DIS
+0.96%
CMCSA
+5.1%
MCD NKE SBUX
LOW PCLN
TWC
TWX FOX TJX
F TGT GM
CCL
YUM
ORLY
LB
DG JCI
CBS DLPH
OMC
DLTR
UA
GPC
MHK HOT
M
DHI
HBI
BBY SIG
FL
PG
+1.3%
WMT
+4.7%
KO
+6.3%
PM
+11%
PEP
+5.5%
MO
CVS
+4%
KHC WBA
RAI
COST MDLZ
CL
+5.8%
KMB
GIS KR
EL STZ
K
TSN
SYY
HSY CAG
DPS
CLX
GE
+3.8%
MMM
+5.8%
UPS
+7.3%
HON BA
UTX
LMT UNP
DHR FDX
CAT
GD
ITW
RTN
DAL NOC EMR
ETN
LUV
WM
NSC
CSX
DE
AAL
GLW
UAL
CMI
ROP
APH
RSG
IR
TYC
PH
VRSK
LLL
XOM
+4.5%
CVX
+13%
SLB
+3%
OXY COP
PSX EOG
KMI
HAL
VLO
PXD
SE
MPC
BHI
APA
HES
NBL
DUK NEE
SO D
AEP
EXC
PPL
PEG
EIX
ED
ES
DTE
FE
ETR
AEE
NI
DOW
DD
MON
LYB
ECL
PX
PPG
SHW
IP
NUE
VMC AA
FCX
BLL
IFF
CF
T
+2.9%
VZ
āˆ’0.21%
LVLT CTL
Information Technology Financials
Health Care
Consumer Discretionary
Consumer Staples
Industrials
Energy Utilities Materials
Telecommunications
Services
<āˆ’25.0% āˆ’20.0% āˆ’15.0% āˆ’10.0% āˆ’5.0% 0.0% 5.0% 10.0% 15.0% 20.0% >25.0%
% Change in Price from Mar 1, 2016 to Apr 15, 2016
Average Median Median Median
Sector Change P/Sales P/Book P/E
Energy 10.6% I 1.6 1.9 25.5
Materials 8.2% I 1.6 4.3 24.0
Utilities 7.1% I 2.0 2.0 22.0
Information Technology 6.1% I 3.5 4.3 24.8
Industrials 5.9% I 1.5 3.6 19.5
Average Median Median Median
Sector Change P/Sales P/Book P/E
Financials 5.4% I 2.6 1.6 16.5
Health Care 4.3% I 3.3 3.9 27.0
Consumer Discretionary 4.1% I 1.7 4.1 19.7
Consumer Staples 3.5% I 2.6 5.9 28.3
Telecommunications Services 1.8% I 1.6 1.9 14.4
www.lairdresearch.com April 18, 2016 Page 6
US Equity Valuations
A key valuation metric is Tobinā€™s q: the ratio between the market
value of the entire US stock market versus US net assets at replacement
cost (ie. what you pay versus what you get). Warren Buļ¬€et famously
follows stock market value as a percentage of GNP, which is highly
(93%) correlated to Tobinā€™s q.
We can also take the reverse approach: assume the market has
valuations correct, we can determine the required returns of future es-
timated earnings. These are quoted for both debt (using BAA rated
securities as a proxy) and equity premiums above the risk free rate (10
year US Treasuries). These ļ¬gures are alternate approaches to under-
standing the current market sentiment - higher premiums indicate a
demand for greater returns for the same price and show the level of
risk-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
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 = 0.76, Dec = 0.95)
S&P 500 Price/Sales (median = 1.35, Dec = 1.82)
Equity and Debt Risk Premiums: Spread vs. Risk Free Rate (10āˆ’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
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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
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 = 4.2%, Apr = 4.9%)
Debt (BAA) Premium (median = 2.0%, Apr = 3.0%)
www.lairdresearch.com April 18, 2016 Page 7
US Mutual Fund Flows
Fund ļ¬‚ows describe the net investments in equity and bond mutual
funds in the US market, as described in ICIā€™s ā€œTrends in Mutual Fund
Investingā€ report. Note however that this is only part of the story as
it does not include ETF fund ļ¬‚ows - part of the changes are investors
entering or leaving the market, and part is investors shifting to ETFā€™s
from mutual funds.
US Net New Investment Cash Flow to Mutual Funds
US$billions(monthly)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
āˆ’40āˆ’2002040
Domestic Equity
World Equity
Taxable Bonds
Municipal Bonds
US Net New Investment Cash Flow to Mutual Funds
US$billions(Monthly)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
āˆ’60āˆ’40āˆ’200204060
Flows to Equity
Flows to Bonds
Net Market Flows
www.lairdresearch.com April 18, 2016 Page 8
US Key Interest Rates
Interest rates are often leading indicators of stress in the ļ¬nancial
system. The yield curve show the time structure of interest rates on
government bonds - Usually the longer the time the loan is outstanding,
the higher the rate charged. However if a recession is expected, then
the fed cuts rates and this relationship is inverted - leading to negative
spreads 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 most
of the time).
For corporate bonds, the key issue is the spread between bond rates
(i.e. AAA vs BAA bonds) or between government loans (LIBOR vs
Fedfunds - the infamous ā€œTED Spreadā€). Here a spike correlates to an
aversion to risk, which is an indication that something bad is happen-
ing.
US Treasury Yield Curves
ForwardInstantaneousRates(%)
15
16
17
18
19
20
21
22
23
24
25
26
0.0
0.5
1.0
1.5
2.0
0.0
0.5
1.0
1.5
2.0
Apr 14, 2016 (Today)
Mar 14, 2016 (1 mo ago)
Jan 14, 2016 (3 mo ago)
14 Apr 2015 (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
0%
1%
2%
3%
4%
5%
6%
7%
0%
1%
2%
3%
4%
5%
6%
7%10 Yr Treasury
3 Mo Treasury
Spread
AAA vs. BAA Bond Spreads
4%
5%
6%
7%
8%
9%
4%
5%
6%
7%
8%
9%
Percent
AAA
BAA
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
median: 91.00
Apr 2016: 119.00
0
100
200
300
0
100
200
300
Spread(bps)
LIBOR vs. Fedfunds Rate
0%
1%
2%
3%
4%
5%
6%
7%
0%
1%
2%
3%
4%
5%
6%
7%
Percent
3 mos tāˆ’bill
LIBOR
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
median: 36.38
Apr 2016: 41.08
0
100
200
300
0
100
200
300
Spread(bps)
www.lairdresearch.com April 18, 2016 Page 9
US Inļ¬‚ation
Generally, the US Fed tries to anchor long run inļ¬‚ation expectations
to approximately 2%. Inļ¬‚ation can be measured with the Consumer
Price Index (CPI) or the Personal Consumption Expenditures (PCE)
index.
In both cases, it makes sense to exclude items that vary quickly like
Food and Energy to get a clearer picture of inļ¬‚ation (usually called
Core Inļ¬‚ation). The Fed seems to think PCI more accurately reļ¬‚ects
the entire basket of goods and services that households purchase.
Finally, we can make a reasonable estimate of future inļ¬‚ation ex-
pectations by comparing real return and normal bonds to construct an
imputed forward inļ¬‚ation expectation. The 5y5y chart shows expected
5 year inļ¬‚ation rates at a point 5 years in the future. Neat trick that.
Consumer Price Index
Percent
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
āˆ’1%
0%
1%
2%
3%
4%
5%
6%
āˆ’1%
0%
1%
2%
3%
4%
5%
6%
US Inflation Rate YoY% (Mar = 0.87%)
US Inflation ex Food & Energy YoY% (Mar = 2.2%)
Personal Consumption Expenditures
Percent(YearoverYear)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’10123456
PCE Inflation Rate YoY% (Feb = 0.96%)
PCE Core Inflation YoY% (Feb = 1.7%)
5āˆ’Year, 5āˆ’Year Forward Inflation Expectation Rate
Percent
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
āˆ’10123456
5 year forward Inflation Expectation
Actual 5yr Inflation (CPI measure)
Actual 5yr Inflation (PCE Measure)
www.lairdresearch.com April 18, 2016 Page 10
QE Taper Tracker
The US has been using the program of Quantitative Easing to pro-
vide monetary stimulous to its economy. The Fed has engaged in a
series of programs (QE1, QE2 & QE3) designed to drive down long
term rates and improve liquidity though purchases of treasuries, mor-
gage backed securites and other debt from banks.
The higher demand for long maturity securities would drive up their
price, but as these securities have a ļ¬xed coupon, their yield would be
decreased (yield ā‰ˆ coupon / price) thus driving down long term rates.
In 2011-2012, ā€œOperation Twistā€ attempted to reduce rates without
increasing liquidity. They went back to QE in 2013.
The Fed chairman suggested in June 2013 the economy was recover-
ing enough that they could start slowing down purchases (ā€œtaperingā€).
The Fed backed oļ¬€ after a brief market panic. The Fed announced in
Dec 2013 that it was starting the taper, a decision partly driven by
seeing key targets of inļ¬‚ation around 2% and unemployment being less
than 6.5%. In Oct 2014, they announced the end of purchases.
QE Asset Purchases to Date (Treasury & Mortgage Backed Securities)
Trillions
0.0
0.5
1.0
1.5
2.0
2.5
0.0
0.5
1.0
1.5
2.0
2.5
QE1 QE2 Operation Twist QE3 TaperTreasuries
Mortgage Backed Securities
Total Monthly Asset Purchases (Treasury + Mortgage Backed Securities)
Billions
āˆ’100
āˆ’50
0
50
100
150
200
āˆ’100
āˆ’50
0
50
100
150
200
Month to date Apr 13: $13.1
Inflation and Unemployment āˆ’ Relative to Targets
Percent
0
2
4
6
8
10
0
2
4
6
8
10
Target Unemployment 6.5%
Target Inflation 2%
U.S. 10 Year and 3 Month Treasury Constant Maturity Yields
Percent
0
1
2
3
4
5
0
1
2
3
4
5
2008 2009 2010 2011 2012 2013 2014 2015
Short Term Rates:
Once at zero, Fed moved to QE
Long Term Rates:
Moving up in anticipation of Taper?
www.lairdresearch.com April 18, 2016 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
0.620.710.810.901.001.09
USA/CAD
0.550.610.660.720.770.82
Euro/CAD
59.1674.7190.26105.81121.36136.91
Japan/CAD
0.380.440.490.550.610.67
U.K./CAD
0.591.101.602.112.613.12
Brazil/CAD
CAD Appreciating
CAD Depreciating
Change in F/X: Mar 1 2016 to Apr 8 2016
(Trade Weighted Currency Index of USD Trading Partners)
āˆ’3.0%
āˆ’1.5%
1.5%
3.0%
Euro
āˆ’2.0%
UK
1.9%
Japan
āˆ’2.0%
South Korea
āˆ’3.7%
China
1.7%
India
1.1%
Brazil
āˆ’5.3%
Mexico
2.2%
Canada
āˆ’0.1%
USA
āˆ’2.9%
Country vs. Average
Appreciating
Depreciating
% Change over 3 months vs. Canada
<āˆ’10.0% āˆ’8.0% āˆ’6.0% āˆ’4.0% āˆ’2.0% 0.0% 2.0% 4.0% 6.0% 8.0% >10.0%
CAD depreciatingCAD appreciating
ARG
āˆ’16.8%
AUS
āˆ’0.8%
BRA
0.9%
CHN
āˆ’10.4%
IND
āˆ’9.8%
RUS
3.2%
USA
āˆ’11.8%
EUR
āˆ’8.8%
JPY
āˆ’4.8%
KRW
āˆ’8.3%
MXN
āˆ’8.3%
ZAR
1.6%
www.lairdresearch.com April 18, 2016 Page 12
US Banking Indicators
The banking and ļ¬nance industry is a key indicator of the health
of the US economy. It provides crucial liquidity to the economy in the
form of credit, and the breakdown of that system is one of the exac-
erbating factors of the 2008 recession. Key ļ¬gures to track are the
Net Interest Margins which determine proļ¬tability (ie. the diļ¬€erence
between what a bank pays to depositors versus what the bank is paid
by creditors), along with levels of non-performing loans (i.e. loan loss
reserves and actual deliquency rates).
US Banks Net Interest Margin
Percent
3.03.54.04.5
median: 3.94
2015 Q4: 3.02
Repos Outstanding with Fed. Reserve
BillionsofDollars
0200400600
median: 58.38
Apr 2016: 258.54
Bank ROE āˆ’ Assets between $300Māˆ’$1B
Percent
051015
median: 12.81
2015 Q4: 9.93
Consumer Credit Outstanding
%YearlyChange
āˆ’505101520
median: 7.52
Feb 2016: 6.61
Total Business Loans
%YearlyChange
āˆ’2001020 median: 8.62
Mar 2016: 10.41
US Nonperforming Loans
Percent
12345
median: 2.05
2015 Q4: 1.55
St. Louis Financial Stress Index
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
0246
median: 0.089
Apr 2016: āˆ’0.81
Commercial Paper Outstanding
TrillionsofDollars
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
1.01.41.82.2
median: 1.33
Apr 2016: 1.09
Residential Morgage Delinquency Rate
Percent
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
246810
median: 2.33
2015 Q4: 5.17
www.lairdresearch.com April 18, 2016 Page 13
US Employment Indicators
Unemployment rates are considered the ā€œsingle best indicator of
current labour conditionsā€ by the Fed. The pace of payroll growth is
highly correlated with a number of economic indicators.Payroll changes
are another way to track the change in unemployment rate.
Unemployment only captures the percentage of people who are in
the labour market who donā€™t currently have a job - another measure
is what percentage of the whole population wants a job (employed or
not) - this is the Participation Rate.
The Beveridge Curve measures labour market eļ¬ƒciency by looking
at the relationship between job openings and the unemployment rate.
The curve slopes downward reļ¬‚ecting that higher rates of unemploy-
ment occur coincidentally with lower levels of job vacancies.
Unemployment Rate
Percent
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
median: 6.10
Mar 2016: 5.00
4
5
6
7
8
9
10
11
4
5
6
7
8
9
10
11
Percent
4 5 6 7 8 9 10
2.02.53.03.54.0
Beveridge Curve (Unemployment vs. Job Openings)
Unemployment Rate (%)
JobOpenings(%totalEmployment)
Dec 2000 āˆ’ Dec 2008
Jan 2009 āˆ’ Jan 2016
Feb 2016
Participation Rate
PercentofPop.
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
6364656667
median: 66.00
Mar 2016: 63.00
Total Nonfarm Payroll Change
MonthlyChange(000s)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’5000500
median: 168
Mar 2016: 215
www.lairdresearch.com April 18, 2016 Page 14
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 a
full-time job - they are employed but under-utilitized. Temporary help
demand 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 jobs
is generally bad, though perhaps not unsurprising in a recovery.
Median Duration of Unemployment
Weeks
510152025
median: 8.70
Mar 2016: 11.40
(U6) Unemployed + PT + Marginally Attached
Percent
810121416
median: 9.80
Mar 2016: 9.80
4āˆ’week moving average of Initial Claims
Jan1995=100
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
050100150200
median: 107.15
Apr 2016: 81.48
Unemployed over 27 weeks
MillionsofPersons
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
01234567
median: 0.80
Mar 2016: 2.31
Services: Temp Help
MillionsofPersons
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
1.52.02.53.0
median: 2.26
Mar 2016: 2.89
āˆ’200 0 200 400 600
15
20
25
30
35
40
Annual Change in Employment Levels (000s of Workers)
Averagewages($/hour)
Private Industry Employment Change (Mar 2015 āˆ’ Mar 2016)
Construction
Durable Goods
Education
Financial Activities
Health Services
Information
Leisure and Hospitality
Manufacturing
Mining and Logging
Nondurable Goods
Other Services
Professional &
Business Services
Retail Trade
Transportation
Utilities
Wholesale Trade
Circle size relative to total employees in industry
www.lairdresearch.com April 18, 2016 Page 15
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 the
current business environment.
Manufacturing: Real Output
YoYPercentChange
āˆ’1001020
median: 8.70
Oct 2015: 6.93
ISM Manufacturing āˆ’ PMI
3040506070
Mar 2016: 51.80
manufac. expanding
manufac. contracting
ISM Manufacturing: New Orders Index
304050607080
Mar 2016: 58.30
Increase in new orders
Decrease in new orders
Nonāˆ’Manufac. New Orders: Capital Goods
BillionsofDollars
40506070
median: 57.99
Feb 2016: 66.97
Average Weekly Hours: Manufacturing
3940414243
median: 41.20
Mar 2016: 41.70
Industrial Production: Manufacturing
YoYPercentChange
āˆ’15āˆ’50510
median: 3.00
Mar 2016: 0.52
Inventory to Sales Ratio
Ratio
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
1.11.21.31.41.51.6
median: 1.37
Feb 2016: 1.41
Chicago Fed: Sales, Orders & Inventory
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’0.50.00.5
Feb 2016: āˆ’0.03
Above ave growth
Below ave growth
ISM Nonāˆ’Manufacturing Bus. Activity Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
35455565
Mar 2016: 59.80
Growth
Contraction
www.lairdresearch.com April 18, 2016 Page 16
US Consumption Indicators
Variations in consumer activity are a leading indicator of the
strength of the economy. We track consumer sentiment (their expec-
tations about the future), consumer loan activity (indicator of new
purchase activity), and new orders and sales of consumer goods.
U. Michigan: Consumer Sentiment
Index1966Q1=100
5060708090110
median: 88.80
Mar 2016: 91.00
Consumer Loans (All banks)
YoY%Change
āˆ’10010203040
median: 7.50
Mar 2016: 7.87
Accounting
Change
Deliquency Rate on Consumer Loans
Percentage
2.03.04.0
median: 3.46
Oct 2015: 2.02
New Orders: Durable Consumer Goods
YoY%Change
āˆ’20020
median: 4.30
Feb 2016: 9.58
New Orders: Nonāˆ’durable Consumer Goods
YoY%Change
āˆ’2001020
median: 4.17
Feb 2016: āˆ’9.92
Personal Consumption & Housing Index
Index
āˆ’0.40.00.20.4
median: 0.02
Feb 2016: āˆ’0.09above ave growth
below ave growth
Light Cars and Trucks Sales
MillionsofUnits
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
10121416182022
median: 14.84
Mar 2016: 16.46
Personal Saving Rate
Percent
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
246810
median: 5.50
Feb 2016: 5.40
Retail Food and Service Sales
YoY%Change(Real)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’10āˆ’505
median: 2.45
Mar 2016: 0.87
www.lairdresearch.com April 18, 2016 Page 17
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. Since
personal consumption is about 70% of the US economy and house val-
ues directly impact household wealth, housing is an important indicator
in the health of the overall economy. In particular, housing investment
was an important driver of the economy getting out of the last few
recessions (though not this one so far). Here we track housing prices
and especially indicators which show the current state of the housing
market.
15 20 25 30 35
150200250300
Personal Income vs. Housing Prices (Inflation adjusted values)
NewHomePrice(000's)
Disposable Income Per Capita (000's)
Feb 2016
r2
: 89.5%
Range: Jan 1959 āˆ’ Feb 2016
Blue dots > +5% change in next year
Red dots < āˆ’5% change in next year
New Housing Units Permits Authorized
MillionsofUnits
0.51.01.52.02.5
median: 1.34
Feb 2016: 1.18
New Home Median Sale Price
SalePrice$000's
100150200250300
Feb 2016: 301.40
Homeowner's Equity Level
Percent
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
4050607080
median: 66.50
2015 Q4: 56.90
New Homes: Median Months on the Market
Months
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
468101214
median: 4.90
Feb 2016: 3.80
US Monthly Supply of Homes
MonthsSupply
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
4681012
median: 5.90
Feb 2016: 5.60
www.lairdresearch.com April 18, 2016 Page 18
US Housing - FHFA Quarterly Index
The Federal Housing Finance Agency provides a quarterly survey
on house prices, based on sales prices and appraisal data. This gener-
ates a housing index for 355 municipal areas in the US from 1979 to
present. We have provided an alternative view of this data looking at
the 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 start
of the housing crisis (deļ¬ned as the maximum price between 2007-2009
for each city). The circled dots are the cities in the survey, while the
background colours are interpolated from these points using a loess
smoother.
Change from 2007 Peak āˆ’ Q4 2015
āˆ’50%
āˆ’40%
āˆ’30%
āˆ’20%
āˆ’10%
0%
10%
20%
30%
40%
50%
Today's Home Prices
Percentage Change from 2007āˆ’2009 Peak
Frequency
āˆ’75% āˆ’50% āˆ’25% 0% 25% 50% 75%
Year over Year Change āˆ’ Q4 2015
āˆ’10%
āˆ’8%
āˆ’6%
āˆ’4%
āˆ’2%
0%
2%
4%
6%
8%
10%
YoY Change in this quarter
YoY Percent Change
Frequency
āˆ’15% āˆ’10% āˆ’5% 0% 5% 10% 15%
www.lairdresearch.com April 18, 2016 Page 19
Global Housing
The Bank for International Settlements has begun collecting global
housing indicies, which are useful for showing what has been happening
with global house prices. Note that these are not all the same data set -
each country measures housing prices in slightly diļ¬€erent ways, so they
are only broadly comparable. Black lines are the data series, blue bars
on the right axis show the year over year percent change.
Brazil āˆ’ Metro All Dwellings
Q12011=100
6080100140
Dec 2015: 137.10
Chile āˆ’ All Dwellings
Jun 2015: 127.92
Peru (Lima) āˆ’ All Dwellings
Dec 2015: 193.62
āˆ’4002040
Mexico āˆ’ All Dwellings
Q12011=100
6080100140
Dec 2015: 126.60
China (Beijing) āˆ’ All Dwellings
Dec 2015: 131.55
Hong Kong āˆ’ Residential Prices
Jan 2016: 165.29
āˆ’4002040
Indonesia āˆ’ Major Cities housing
Q12011=100
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
6080100140
Dec 2015: 135.71
India āˆ’ Major Cities housing
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
Sep 2015: 205.91
Singapore āˆ’ All Dwellings
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
Sep 2015: 100.00
āˆ’4002040
www.lairdresearch.com April 18, 2016 Page 20
Philippines (Manila) āˆ’ Flats
Q12011=100
6080120
Dec 2015: 146.25
Japan āˆ’ All Dwellings
Nov 2015: 104.90
Australia āˆ’ All Dwellings
Sep 2015: 126.97
āˆ’4002040
New Zealand āˆ’ All Dwellings Big Cities
Q12011=100
6080120
Sep 2015: 153.58
Turkey āˆ’ All Dwellings
Dec 2015: 193.00
South Africa āˆ’ Residential
Feb 2016: 114.18
āˆ’4002040
Israel āˆ’ All Dwellings
Q12011=100
6080120
Nov 2015: 134.11
Korea āˆ’ All Dwellings
Feb 2016: 113.99
Russia āˆ’ All Dwellings (Urban)
Sep 2015: 123.98
āˆ’4002040
Euro zone āˆ’ All Dwellings
Q12011=100
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
6080120
Sep 2015: 99.15
Canada āˆ’ New Houses
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
Jan 2016: 109.60
US āˆ’ New Single Family Houses
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
Dec 2015: 123.48
āˆ’4002040
www.lairdresearch.com April 18, 2016 Page 21
Global Business Indicators
Global Manufacturing PMI Reports
The Purchasing Managersā€™ Index (PMI) is an indicator reļ¬‚ecting
purchasing managersā€™ acquisition of goods and services. An index read-
ing of 50.0 means that business conditions are unchanged, a number
over 50.0 indicates an improvement while anything below 50.0 suggests
a decline. The further away from 50.0 the index is, the stronger the
change over the month. The chart at the bottom shows a moving av-
erage of a number of PMIā€™s, along with standard deviation bands to
show a global average.
Global Māˆ’PMI āˆ’ March 2016
<40.0 42.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0 >60.0
Steady ExpandingContracting
Eurozone
51.6
Global PMI
50.5
TWN
51.1MEX
53.2
KOR
49.5
JPN
49.1
VNM
50.7
IDN
50.6
ZAF
47.0
AUS
58.1
BRA
46.0
CAN
51.5
CHN
49.7
IND
52.4
RUS
48.3
SAU
54.5
USA
51.5
Global Māˆ’PMI Monthly Change
<āˆ’5.0 āˆ’4.0 āˆ’3.0 āˆ’2.0 āˆ’1.0 0.0 1.0 2.0 3.0 4.0 >5.0
PMI Change ImprovingDeteriorating
Eurozone
0.4
Global PMI
0.5
TWN
1.7MEX
0.1
KOR
0.8
JPN
āˆ’1.0
VNM
0.4
IDN
1.9
ZAF
āˆ’2.1
AUS
4.6
BRA
1.5
CAN
2.1
CHN
1.7
IND
1.3
RUS
āˆ’1.0
SAU
0.1
USA
0.2
Purchase Managers Index (Manufacturing) āˆ’ China, Japan, USA, Canada, France, Germany, Italy, UK, Australia
04
05
06
07
08
09
10
11
12
13
14
15
16
3040506070
3040506070
Business Conditions Contracting
Business Conditions Expanding
www.lairdresearch.com April 18, 2016 Page 22
Global Manufacturing PMI Chart
This is an alternate view of the global PMI reports. Here, we look
at all the various PMI data series in a single chart and watch their
evolution over time.
Red numbers indicate contraction (as estimated by PMI) while
green numbers indicate expansion.
Mar14
Apr14
May14
Jun14
Jul14
Aug14
Sep14
Oct14
Nov14
Dec14
Jan15
Feb15
Mar15
Apr15
May15
Jun15
Jul15
Aug15
Sep15
Oct15
Nov15
Dec15
Jan16
Feb16
Mar16
Australia
India
Indonesia
Viet Nam
Taiwan
China
Korea
Japan
South Africa
Saudi Arabia
Turkey
Russia
United Kingdom
Greece
Germany
France
Italy
Czech Republic
Spain
Poland
Ireland
Netherlands
Eurozone
Brazil
Mexico
Canada
United States
Global PMI 52.4 51.9 52.2 52.6 52.4 52.6 52.2 52.2 51.8 51.6 51.7 52.0 51.7 51.0 51.2 51.0 51.0 50.7 50.7 51.3 51.2 50.7 50.9 50.0 50.5
55.5 55.4 56.4 57.3 55.8 57.9 57.5 55.9 54.8 53.9 53.9 55.1 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
53.3 52.9 52.2 53.5 54.3 54.8 53.5 55.3 55.3 53.9 51.0 48.7 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
51.7 51.8 51.9 51.8 51.5 52.1 52.6 53.3 54.3 55.3 56.6 54.4 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
50.6 49.3 48.8 48.7 49.1 50.2 49.3 49.1 48.7 50.2 50.7 49.6 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
53.0 53.4 52.2 51.8 51.8 50.7 50.3 50.6 50.1 50.6 51.0 51.0 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
53.7 53.4 53.6 52.3 53.5 51.7 52.2 53.0 54.6 53.6 54.1 52.2 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
55.5 56.1 55.0 55.3 55.4 57.3 55.7 56.6 56.2 56.9 55.1 57.5 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
54.0 52.0 50.8 50.3 49.4 49.0 49.5 51.2 53.2 52.8 55.2 55.1 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
52.8 52.7 52.9 54.6 53.9 52.8 52.6 52.6 54.7 53.8 54.7 54.2 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
55.5 56.5 57.3 54.7 56.5 54.3 55.6 54.4 55.6 53.3 56.1 55.6 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
52.4 54.0 53.2 52.6 51.9 49.8 50.7 49.0 49.0 48.4 49.9 51.9 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
52.1 51.2 49.6 48.2 47.8 46.9 48.8 48.5 48.4 47.5 49.2 47.6 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
53.7 54.1 52.3 52.0 52.4 51.4 49.9 51.4 49.5 51.2 50.9 51.1 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
49.7 51.1 51.0 49.4 48.7 50.1 48.4 48.8 49.1 49.4 48.3 48.4 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
55.3 57.3 57.0 57.5 55.4 52.5 51.6 53.2 53.5 52.5 53.1 54.1 54.4 51.9 52.0 51.4 51.9 51.6 51.8 55.5 52.7 51.9 52.9 50.8 51.0
48.3 48.5 48.9 49.1 51.0 51.0 50.4 50.3 51.7 48.9 47.6 49.7 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
51.7 51.1 50.1 48.8 48.5 50.3 50.4 51.5 52.2 51.4 49.8 49.6 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
57.0 58.5 57.0 59.2 60.1 60.7 61.8 59.1 57.6 57.9 57.8 58.5 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
50.3 47.4 44.3 46.6 45.9 49.0 50.7 52.7 50.5 50.2 49.8 50.0 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
53.9 49.4 49.9 51.5 50.5 52.5 51.7 52.4 52.0 52.0 52.2 51.6 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
50.4 50.2 49.5 48.4 49.3 50.3 48.8 48.7 49.0 49.9 51.1 51.1 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
48.0 48.1 49.4 50.7 51.7 50.2 50.2 50.4 50.0 49.6 49.7 50.7 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
52.7 52.3 52.4 54.0 55.8 56.1 53.3 52.0 51.4 50.0 51.7 52.1 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
51.3 53.1 52.5 52.3 51.7 50.3 51.7 51.0 52.1 52.7 51.5 51.7 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
50.1 51.1 52.4 52.7 52.7 49.5 50.7 49.2 48.0 47.6 48.5 47.5 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
51.3 51.3 51.4 51.5 53.0 52.4 51.0 51.6 53.3 54.5 52.9 51.2 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
47.9 44.8 49.2 48.9 50.7 47.3 46.5 49.4 50.1 46.9 49.0 45.4 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
www.lairdresearch.com April 18, 2016 Page 23
Canadian Indicators
Retail Trade (SA)
YoYPercentChange
āˆ’50510
median: 4.67
Jan 2016: 6.38
Total Manufacturing Sales Growth
YoYPercentGrowth
āˆ’20āˆ’1001020
median: 3.83
Feb 2016: 3.85
Manufacturing New Orders Growth
YoYPercentGrowth
āˆ’30āˆ’100102030
median: 4.08
Feb 2016: 2.58
1yr vs. 10yr Canada Bond Yields
Yield(Percent)
0246810
median: 5.66
Mar 2016: 1.22
10 yr bond
1 yr bond
Manufacturing PMI
48505254
Mar 2016: 51.50
Sales and New Orders (SA)
YoYPercentChange
āˆ’20āˆ’1001020
Sales
New Orders (smoothed)
Tbill Yield Spread (10 yr āˆ’ 3mo)
Spread(Percent)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’101234
median: 1.31
Mar 2016: 0.78
Inflation (total and core)
YoYPercentChange
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’101234
median: 1.90
Feb 2016: 1.36
Total
Core
Inventory to Sales Ratio (SA)
Ratio
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
1.31.41.51.6
median: 1.35
Feb 2016: 1.40
www.lairdresearch.com April 18, 2016 Page 24
6.6 6.8 7.0 7.2 7.4 7.6
1.31.41.51.61.71.81.9
Beveridge Curve (Mar 2011 āˆ’ Dec 2015)
as.numeric(can.bev$ui.rate)
as.numeric(can.bev$vacancies)
Mar 2011 āˆ’ Dec 2012
Jan 2013 āˆ’ Nov 2015
Dec 2015
Unemployment Rate
JobVacancyrate(Industrial)
Ownership/Rental Price Ratio
RatioofAccomodationOwnership/RentRatio
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
90100110120130140150
Calgary
Montreal
Vancouver
Toronto
Note: Using prices relative to 2002 as base year
Ownership relatively more
expensive vs 2002
Rent relatively more expensive vs 2002
Unemployment Rate (SA)
Percent
345678910
Canada 7.1%
Alberta 7.1%
Ontario 6.8%
Debt Service Ratios (SA)
Percent
0246810
Total Debt: 6.2%
Mortgage: 3.2%
Consumer Debt: 6.2%
Housing Starts and Building Permits (smoothed)
YoYPercentChange
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’40āˆ’2002040
Permits
Starts
www.lairdresearch.com April 18, 2016 Page 25
European Indicators
Unemployment Rates
Percentage
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
051015202530
FR
DE
GB
IT
GR
ES
EU
Business Employment Expectations
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’40āˆ’20010
Industrial Orderbook Levels
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’60āˆ’40āˆ’20020
Country Employment
Expect.
Unempl.
(%)
Bond Yields
(%)
Retail
Turnover
Manufacturing
Turnover
Inļ¬‚ation
(YoY %)
Industry
Orderbook
PMI
Series Dates Mar 2016 Mar 2016 Mar 2016 Feb 2016 Feb 2016 Mar 2016 Mar 2016 Mar 2016
France -6.9 I 10.2 K 0.51 J 111.9 I 105.1 J -0.1 K -14.0 J 49.6 J
Germany -5.7 J 4.3 K 0.17 K NA 114.5 J 0.1 I -12.2 I 50.7 I
United Kingdom 3.2 I 5.0 K 1.46 I 113.8 J NA 0.5 -16.6 I 51.0 I
Italy -1.6 I 11.7 I 1.38 J 100.6 J NA -0.2 K -13.5 I 53.5 I
Greece -4.3 J 24.4 I 9.12 J NA NA -0.7 J -26.3 I 49.0 I
Spain 6.5 I 20.4 J 1.54 J NA NA -1.0 K -5.4 I 53.4 J
Eurozone (EU28) -2.2 I 8.9 K 1.19 J 108.0 J 109.8 I 0.0 -13.8 I NA
www.lairdresearch.com April 18, 2016 Page 26
Government Bond YieldsLongTermYields%
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
0246810
Economic Sentiment
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
60708090110130
Consumer Confidence
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’100āˆ’60āˆ’20020
Inflation (Harmonized Prices)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
median: 1.90
Mar 2016: 0.00
āˆ’1
0
1
2
3
4
5
6
7
Harmonized Inflation: Feb 2016
AUT
0.6%
BGR
āˆ’1.9%
DEU
0.1%
ESP
āˆ’1.0%
FIN
0.0%
FRA
āˆ’0.1%
GBR
0.5%
GRC
āˆ’0.7%
HRV
āˆ’0.9%
HUN
āˆ’0.2%
IRL
āˆ’0.6%
ISL
0.3%
ITA
āˆ’0.2%
NOR
3.6%
POL
āˆ’0.4%
ROU
āˆ’2.4%
SWE
1.2%
<āˆ’1.0%0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% >7.0%
YoY % Change in Prices
PMI: March 2016
<40.042.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0>60.0
Steady ExpandingContracting
BRA
46.0
CAN
51.5
DEU
50.7
ESP
53.4
FRA
49.6
GBR
51.0
GRC
49.0
IRL
54.9
ITA
53.5
MEX
53.2
POL
53.8
SAU
54.5
TUR
49.2
USA
51.5
RUS
48.3
PMI Change: Feb āˆ’ Mar
<āˆ’5.0āˆ’4.0 āˆ’3.0 āˆ’2.0 āˆ’1.0 0.0 1.0 2.0 3.0 4.0 >5.0
PMI Change ImprovingDeteriorating
CAN
2.1
DEU
0.2
ESP
āˆ’0.7
FRA
āˆ’0.6
GBR
0.2
GRC
0.6
IRL
2.0
ITA
1.3
POL
1.0
TUR
āˆ’1.1
USA
0.2
RUS
āˆ’1.0
www.lairdresearch.com April 18, 2016 Page 27
Chinese Indicators
Tracking the Chinese economy is a tricky. As reported in the Fi-
nancial Times, Premier Li Keqiang conļ¬ded to US oļ¬ƒcials in 2007 that
gross domestic product was ā€œman madeā€ and ā€œfor reference onlyā€. 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 oļ¬ƒcial version put out by the Chinese government and
diļ¬€ers slightly from an HSBC version. Finally we include the Shanghai
Composite 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
4045505560
Mar 2016: 49.70
Shanghai Composite Index
IndexValue(MonthlyHigh/Low)
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
0100030005000
Apr 2016: 3009.53
Electricity Generated
100MillionKWH(logscale)
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
1000200030005000
Feb 2016: 4351.00
Electricity Generated
Long Term Trend
Short Term Average
Consumer Confidence Index
Index
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
98100102104106108110
median: 103.95
Feb 2016: 104.40
Exports
YoYPercentChange
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
āˆ’20020406080
median: 18.35
Feb 2016: āˆ’25.40
Retail Sales Growth
YoYPercentChange
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
101520
median: 12.90
Jan 2016: 10.20
www.lairdresearch.com April 18, 2016 Page 28
Global Climate Change
Temperature and precipitation data are taken from the US National
Climatic Data Center and presented as the average monthly anomaly
from the previous 6 months. Anomalies are deļ¬ned as the diļ¬€erence
from the average value over the period from 1971-2000 for the tem-
perature map and over the 20th century for the global temparature
chart.
Average Temperature Anomalies from Sep 2015 - Feb 2016
<āˆ’4.0 āˆ’3.0 āˆ’2.0 āˆ’1.0 0.0 1.0 2.0 3.0 >4.0
Anomalies in Celcius WarmerCooler Anomalies in Celcius
āˆ’4 āˆ’2 0 2 4
Historic Global Temperature Deviations
DegreesCelciusDeviations
āˆ’0.50.00.51.0
Feb 2016: 1.21
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020
www.lairdresearch.com April 18, 2016 Page 29

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Global Economics Update - April 2016

  • 1. .... Laird Research - Economics April 18, 2016 Where we are now . . . . . . . . . . . . . . . . . . . . . . . . 1 Indicators for US Economy . . . . . . . . . . . . . . . . . . . 2 Global Financial Markets . . . . . . . . . . . . . . . . . . . . 4 US Key Interest Rates . . . . . . . . . . . . . . . . . . . . . . 9 US Inļ¬‚ation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 QE Taper Tracker . . . . . . . . . . . . . . . . . . . . . . . . . 11 Exchange Rates . . . . . . . . . . . . . . . . . . . . . . . . . . 12 US Banking Indicators . . . . . . . . . . . . . . . . . . . . . . 13 US Employment Indicators . . . . . . . . . . . . . . . . . . . 14 US Business Activity Indicators . . . . . . . . . . . . . . . . 16 US Consumption Indicators . . . . . . . . . . . . . . . . . . 17 US Housing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Global Housing . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Global Business Indicators . . . . . . . . . . . . . . . . . . . 22 Canadian Indicators . . . . . . . . . . . . . . . . . . . . . . . 24 European Indicators . . . . . . . . . . . . . . . . . . . . . . . 26 Chinese Indicators . . . . . . . . . . . . . . . . . . . . . . . . 28 Global Climate Change . . . . . . . . . . . . . . . . . . . . . 29 Where we are now The Laird Report presents a selection of economic data from around the world to help ļ¬gure where we are today. It was originally designed to be read on the train - 1 page per minute on my 30 minute morning commute. This is the time when the divergence between corporate proļ¬ts and how individuals are actually fairing becomes visible. In the US, corpo- rate proļ¬ts are clearly down year over year (see page 4). Given that they were at historic highs thanks to larger than usual proļ¬t margins, this is not particularly unusual (ie. itā€™s heading towards normalacy rather than a collapse overall). On the other hand, inļ¬‚ation is low (thanks oil!) and employment in the US is still strong. In a real sense, this is more a game of catch-up as individuals have been signiļ¬cantly trailing corporate proļ¬ts. One area this report is deļ¬cient is in tracking the service industry. This report heavily focuses on asset prices, employment and manufac- turing and only indirectly looks at services. This is a weakness because services are accounting for the bulk of GDP in most countries. For China this is a particular weakness in our understanding of their econ- omy as manufacturing has slowed down but there is a countervailing force of the Chinese government pushing for an improvement on their service sector. (Note the layoļ¬€s in the past two months of millions of miners etc, with the view that they will be retrained for the service sector). Ultimately we are going to have to ļ¬nd a better way to track this part of the economy. Global trade is still down in this report. Again, from the reading Iā€™ve been doing, it seems that the service sector is taking up some of the slack on this. higher wages, more inļ¬‚ation, and higher proļ¬ts. 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 18, 2016
  • 2. Indicators for US Economy Leading indicators are indicators that usually change before the economy as a whole changes. They are useful as short-term predictors of the economy. Our list includes the Philly Fedā€™s Leading Index which summarizes 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 ļ¬nancial situation and the economy in general). Red dots are points where a new trend has started. Leading Index for the US Index:Est.6monthgrowth 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’2āˆ’10123 median: 1.56 Feb 2016: 1.57 Growth Contraction Initial Unemployment Claims 1000'sofClaimsperWeek 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 0100300500700 median: 348.50 Apr 2016: 265.00 Manufacturing Ave. Weekly Hours Worked HoursworkedperWeek 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 394041424344 median: 40.60 Mar 2016: 41.70 ISM Manfacturing āˆ’ PMI Index:SteadyState=50 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 3040506070 median: 53.30 Mar 2016: 51.80expanding economy contracting economy www.lairdresearch.com April 18, 2016 Page 2
  • 3. Leading indicators are indicators that usually change before the economy as a whole changes. They are useful as short-term predictors of the economy. Our list includes the Philly Fedā€™s Leading Index which summarizes 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 ļ¬nancial situation and the economy in general). Red dots are points where a new trend has started. Durable Goods: Manufacturers New Orders BillionsofDollars 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 150200250300 median: 185.46 Feb 2016: 229.12 Index of Truck Tonnage Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 100110120130 median: 113.05 Feb 2016: 135.80 Capex (ex. Defense & Planes) BillionsofDollars 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 40506070 median: 57.99 Feb 2016: 66.97 U. Michigan: Consumer Sentiment Index1966Q1=100 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 5060708090100110 median: 88.80 Mar 2016: 91.00 www.lairdresearch.com April 18, 2016 Page 3
  • 4. Global Financial Markets Global Stock Market Returns Country Index Name Close Date Current Value Weekly Change Monthly Change 3 month Change 12 month Change Corr to S&P500 Corr to TSX North America USA S&P 500 Apr 15 2,080.7 1.6% I 3.2% I 10.7% I -1.2% J 1.00 0.75 USA NASDAQ Composite Apr 15 4,938.2 1.8% I 4.4% I 10.0% I -1.5% J 0.96 0.67 USA Wilshire 5000 Total Market Apr 15 21,463.5 1.9% I 3.7% I 11.0% I -3.9% J 0.99 0.76 Canada S&P TSX Apr 15 13,637.2 1.8% I 1.8% I 13.0% I -11.7% J 0.75 1.00 Europe and Russia France CAC 40 Apr 15 4,495.2 4.5% I 0.5% I 6.8% I -14.4% J 0.58 0.55 Germany DAX Apr 15 10,051.6 4.5% I 1.2% I 5.3% I -17.8% J 0.53 0.46 United Kingdom FTSE Apr 15 6,343.8 2.2% I 3.3% I 9.3% I -10.6% J 0.63 0.64 Russia Market Vectors Russia ETF Apr 15 16.8 2.0% I 7.7% I 35.6% I -15.3% J 0.63 0.73 Asia Taiwan TSEC weighted index Apr 15 8,700.4 1.9% I 1.0% I 12.1% I -8.8% J 0.22 0.25 China Shanghai Composite Index Apr 15 3,078.1 3.1% I 7.5% I 6.1% I -24.6% J 0.18 0.15 Japan NIKKEI 225 Apr 15 16,848.0 6.5% I -1.6% J -1.7% J -15.2% J 0.05 0.09 Hong Kong Hang Seng Apr 15 21,316.5 4.6% I 5.1% I 9.2% I -22.8% J 0.27 0.33 Korea Kospi Apr 15 2,014.7 2.2% I 2.3% I 7.2% I -5.0% J 0.22 0.27 South Asia and Austrailia India Bombay Stock Exchange Apr 13 25,626.8 2.9% I 3.3% I 3.1% I -11.8% J 0.40 0.41 Indonesia Jakarta Apr 15 4,823.6 -0.5% J -0.5% J 6.6% I -10.9% J 0.13 0.23 Malaysia FTSE Bursa Malaysia KLCI Apr 15 1,728.0 0.6% I 2.2% I 6.1% I -6.1% J 0.31 0.29 Australia All Ordinaries Apr 15 5,224.1 4.1% I 1.1% I 5.6% I -11.1% J 0.13 0.28 New Zealand NZX 50 Index Gross Apr 15 6,844.7 1.7% I 4.1% I 11.0% I 16.9% I 0.09 0.11 South America Brasil IBOVESPA Apr 15 53,228.0 5.8% I 12.9% I 38.0% I -3.1% J 0.39 0.49 Argentina MERVAL Buenos Aires Apr 15 13,237.9 8.3% I 9.6% I 32.1% I 9.1% I 0.49 0.55 Mexico Bolsa index Apr 15 45,536.5 1.5% I 3.0% I 11.5% I 0.6% I 0.70 0.64 MENA and Africa Egypt Market Vectors Egypt ETF Apr 15 38.6 -0.5% J 6.8% I 20.7% I -28.2% J 0.42 0.50 (Gulf States) Market Vectors Gulf States ETF Apr 15 22.4 1.9% I 5.4% I 17.6% I -16.5% J 0.30 0.28 South Africa iShares MSCI South Africa Index Apr 15 54.3 5.7% I 14.0% I 38.9% I -20.2% J 0.68 0.67 (Africa) Market Vectors Africa ETF Apr 15 19.6 4.0% I 4.8% I 28.9% I -24.2% J 0.59 0.71 Commodities USD Spot Oil West Texas Int. Apr 11 $40.5 18.0% I 5.1% I 28.8% I -22.1% J 0.42 0.62 USD Gold LME Spot Apr 15 $1,229.8 -0.4% J -0.3% J 13.7% I 3.4% I 0.01 0.02 Note: Correlations are based on daily arithmetic returns for the most recent 100 trading days. www.lairdresearch.com April 18, 2016 Page 4
  • 5. S&P 500 Composite Index The S&P 500 Composite Index is widely regarded as the best single gauge of the large cap U.S. equities market. A key ļ¬gure is the valua- tion level of the S&P500 as measured by the Price/Earnings ratio. We present two versions: (1) a 12-month trailing earnings version which reļ¬‚ects current earnings but is skewed by short term variances and (2) a cyclically adjusted version which looks at the inļ¬‚ation adjusted earn- ings over a 10 year period (i.e. at least one business cycle). Forecasted earnings numbers are estimates provided by S&P. S&P 500 Profit Margins and Overall Corporate Profit Margins (Trailing 12 months) Percent 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 14 Percent Total Corporate Profits (% of GDP) āˆ’ median: 6.2%, Q4/15: 9.0% Net Profit Margin (S&P 500 Earnings / Revenue) āˆ’ median: 6.6%, Q4/15: 7.7% S&P Quarterly Earnings (USD$ 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 āˆ’5.00 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 āˆ’5.00 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 Tech Bubble Japanese Asset Bubble House BubbleAsian Financial Crisis US Financial Crisis Eurozone crisis Oil Crisis I Oil Crisis II Gulf War Savings and Loans Crisis High Inflation Period Afganistan/Iraq WarVietnam War Reported Earnings Operating 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 0 10 20 30 40 50 0 10 20 30 40 50 Multiple Multiple 12āˆ’month P/E ( median = 17.4, Apr = 22.7) 10āˆ’year CAPE ( median = 19.5, Apr = 25.6) www.lairdresearch.com April 18, 2016 Page 5
  • 6. S&P 500 Composite Distributions This is a view of the price performance of the S&P 500 index com- panies. The area of each box is proportional to the companyā€™s market cap, while the colour is determined by the percentage change in price over the past month. In addition, companies are sorted according to their industry group. AAPL +9.3% GOOG +5.6% MSFT +5.8% FB āˆ’0.16% V +7.3% ORCL +8% INTC +3.6% IBM +13% CSCO +4.9% MA +7.3% QCOM ACN TXN EMC CRM ADP YHOO HPE EBAY INTU ATVI AMAT FISV TEL FIS EQIX EA NVDA ADI CA MU BRKāˆ’B +4.8% WFC āˆ’0.96% JPM +5.3% BAC +6.5% C +8.8% USB +3.7% GS +2.5% SPG AIG AXP BLK MS MET PSA PNC BK CB SCHW COF TRV PRU CME MMC CCI ICE AFL MHFI GGP AVB HCN SYF STT PLD BEN DFS VTR PGR BXP MTB WY O IVZ L XL FRT SLG LNC JNJ +2.8% PFE +8.2% MRK +9.4% GILD +10% UNH +5.1% AMGN +7.9% BMY MDT +4.5% AGN āˆ’27% ABBV +5.6% CELG +2.2% LLY ABT +10% BIIB TMO +7.6% ESRX REGN SYK AET MCK CI BDX HCA CAH BSX ZTS ZBH EW A WAT AMZN +8.1% HD +8% DIS +0.96% CMCSA +5.1% MCD NKE SBUX LOW PCLN TWC TWX FOX TJX F TGT GM CCL YUM ORLY LB DG JCI CBS DLPH OMC DLTR UA GPC MHK HOT M DHI HBI BBY SIG FL PG +1.3% WMT +4.7% KO +6.3% PM +11% PEP +5.5% MO CVS +4% KHC WBA RAI COST MDLZ CL +5.8% KMB GIS KR EL STZ K TSN SYY HSY CAG DPS CLX GE +3.8% MMM +5.8% UPS +7.3% HON BA UTX LMT UNP DHR FDX CAT GD ITW RTN DAL NOC EMR ETN LUV WM NSC CSX DE AAL GLW UAL CMI ROP APH RSG IR TYC PH VRSK LLL XOM +4.5% CVX +13% SLB +3% OXY COP PSX EOG KMI HAL VLO PXD SE MPC BHI APA HES NBL DUK NEE SO D AEP EXC PPL PEG EIX ED ES DTE FE ETR AEE NI DOW DD MON LYB ECL PX PPG SHW IP NUE VMC AA FCX BLL IFF CF T +2.9% VZ āˆ’0.21% LVLT CTL Information Technology Financials Health Care Consumer Discretionary Consumer Staples Industrials Energy Utilities Materials Telecommunications Services <āˆ’25.0% āˆ’20.0% āˆ’15.0% āˆ’10.0% āˆ’5.0% 0.0% 5.0% 10.0% 15.0% 20.0% >25.0% % Change in Price from Mar 1, 2016 to Apr 15, 2016 Average Median Median Median Sector Change P/Sales P/Book P/E Energy 10.6% I 1.6 1.9 25.5 Materials 8.2% I 1.6 4.3 24.0 Utilities 7.1% I 2.0 2.0 22.0 Information Technology 6.1% I 3.5 4.3 24.8 Industrials 5.9% I 1.5 3.6 19.5 Average Median Median Median Sector Change P/Sales P/Book P/E Financials 5.4% I 2.6 1.6 16.5 Health Care 4.3% I 3.3 3.9 27.0 Consumer Discretionary 4.1% I 1.7 4.1 19.7 Consumer Staples 3.5% I 2.6 5.9 28.3 Telecommunications Services 1.8% I 1.6 1.9 14.4 www.lairdresearch.com April 18, 2016 Page 6
  • 7. US Equity Valuations A key valuation metric is Tobinā€™s q: the ratio between the market value of the entire US stock market versus US net assets at replacement cost (ie. what you pay versus what you get). Warren Buļ¬€et famously follows stock market value as a percentage of GNP, which is highly (93%) correlated to Tobinā€™s q. We can also take the reverse approach: assume the market has valuations correct, we can determine the required returns of future es- timated earnings. These are quoted for both debt (using BAA rated securities as a proxy) and equity premiums above the risk free rate (10 year US Treasuries). These ļ¬gures are alternate approaches to under- standing the current market sentiment - higher premiums indicate a demand for greater returns for the same price and show the level of risk-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 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 = 0.76, Dec = 0.95) S&P 500 Price/Sales (median = 1.35, Dec = 1.82) Equity and Debt Risk Premiums: Spread vs. Risk Free Rate (10āˆ’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 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 = 4.2%, Apr = 4.9%) Debt (BAA) Premium (median = 2.0%, Apr = 3.0%) www.lairdresearch.com April 18, 2016 Page 7
  • 8. US Mutual Fund Flows Fund ļ¬‚ows describe the net investments in equity and bond mutual funds in the US market, as described in ICIā€™s ā€œTrends in Mutual Fund Investingā€ report. Note however that this is only part of the story as it does not include ETF fund ļ¬‚ows - part of the changes are investors entering or leaving the market, and part is investors shifting to ETFā€™s from mutual funds. US Net New Investment Cash Flow to Mutual Funds US$billions(monthly) 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 āˆ’40āˆ’2002040 Domestic Equity World Equity Taxable Bonds Municipal Bonds US Net New Investment Cash Flow to Mutual Funds US$billions(Monthly) 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 āˆ’60āˆ’40āˆ’200204060 Flows to Equity Flows to Bonds Net Market Flows www.lairdresearch.com April 18, 2016 Page 8
  • 9. US Key Interest Rates Interest rates are often leading indicators of stress in the ļ¬nancial system. The yield curve show the time structure of interest rates on government bonds - Usually the longer the time the loan is outstanding, the higher the rate charged. However if a recession is expected, then the fed cuts rates and this relationship is inverted - leading to negative spreads 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 most of the time). For corporate bonds, the key issue is the spread between bond rates (i.e. AAA vs BAA bonds) or between government loans (LIBOR vs Fedfunds - the infamous ā€œTED Spreadā€). Here a spike correlates to an aversion to risk, which is an indication that something bad is happen- ing. US Treasury Yield Curves ForwardInstantaneousRates(%) 15 16 17 18 19 20 21 22 23 24 25 26 0.0 0.5 1.0 1.5 2.0 0.0 0.5 1.0 1.5 2.0 Apr 14, 2016 (Today) Mar 14, 2016 (1 mo ago) Jan 14, 2016 (3 mo ago) 14 Apr 2015 (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 0% 1% 2% 3% 4% 5% 6% 7% 0% 1% 2% 3% 4% 5% 6% 7%10 Yr Treasury 3 Mo Treasury Spread AAA vs. BAA Bond Spreads 4% 5% 6% 7% 8% 9% 4% 5% 6% 7% 8% 9% Percent AAA BAA 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 median: 91.00 Apr 2016: 119.00 0 100 200 300 0 100 200 300 Spread(bps) LIBOR vs. Fedfunds Rate 0% 1% 2% 3% 4% 5% 6% 7% 0% 1% 2% 3% 4% 5% 6% 7% Percent 3 mos tāˆ’bill LIBOR 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 median: 36.38 Apr 2016: 41.08 0 100 200 300 0 100 200 300 Spread(bps) www.lairdresearch.com April 18, 2016 Page 9
  • 10. US Inļ¬‚ation Generally, the US Fed tries to anchor long run inļ¬‚ation expectations to approximately 2%. Inļ¬‚ation can be measured with the Consumer Price Index (CPI) or the Personal Consumption Expenditures (PCE) index. In both cases, it makes sense to exclude items that vary quickly like Food and Energy to get a clearer picture of inļ¬‚ation (usually called Core Inļ¬‚ation). The Fed seems to think PCI more accurately reļ¬‚ects the entire basket of goods and services that households purchase. Finally, we can make a reasonable estimate of future inļ¬‚ation ex- pectations by comparing real return and normal bonds to construct an imputed forward inļ¬‚ation expectation. The 5y5y chart shows expected 5 year inļ¬‚ation rates at a point 5 years in the future. Neat trick that. Consumer Price Index Percent 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 āˆ’1% 0% 1% 2% 3% 4% 5% 6% āˆ’1% 0% 1% 2% 3% 4% 5% 6% US Inflation Rate YoY% (Mar = 0.87%) US Inflation ex Food & Energy YoY% (Mar = 2.2%) Personal Consumption Expenditures Percent(YearoverYear) 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’10123456 PCE Inflation Rate YoY% (Feb = 0.96%) PCE Core Inflation YoY% (Feb = 1.7%) 5āˆ’Year, 5āˆ’Year Forward Inflation Expectation Rate Percent 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 āˆ’10123456 5 year forward Inflation Expectation Actual 5yr Inflation (CPI measure) Actual 5yr Inflation (PCE Measure) www.lairdresearch.com April 18, 2016 Page 10
  • 11. QE Taper Tracker The US has been using the program of Quantitative Easing to pro- vide monetary stimulous to its economy. The Fed has engaged in a series of programs (QE1, QE2 & QE3) designed to drive down long term rates and improve liquidity though purchases of treasuries, mor- gage backed securites and other debt from banks. The higher demand for long maturity securities would drive up their price, but as these securities have a ļ¬xed coupon, their yield would be decreased (yield ā‰ˆ coupon / price) thus driving down long term rates. In 2011-2012, ā€œOperation Twistā€ attempted to reduce rates without increasing liquidity. They went back to QE in 2013. The Fed chairman suggested in June 2013 the economy was recover- ing enough that they could start slowing down purchases (ā€œtaperingā€). The Fed backed oļ¬€ after a brief market panic. The Fed announced in Dec 2013 that it was starting the taper, a decision partly driven by seeing key targets of inļ¬‚ation around 2% and unemployment being less than 6.5%. In Oct 2014, they announced the end of purchases. QE Asset Purchases to Date (Treasury & Mortgage Backed Securities) Trillions 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 QE1 QE2 Operation Twist QE3 TaperTreasuries Mortgage Backed Securities Total Monthly Asset Purchases (Treasury + Mortgage Backed Securities) Billions āˆ’100 āˆ’50 0 50 100 150 200 āˆ’100 āˆ’50 0 50 100 150 200 Month to date Apr 13: $13.1 Inflation and Unemployment āˆ’ Relative to Targets Percent 0 2 4 6 8 10 0 2 4 6 8 10 Target Unemployment 6.5% Target Inflation 2% U.S. 10 Year and 3 Month Treasury Constant Maturity Yields Percent 0 1 2 3 4 5 0 1 2 3 4 5 2008 2009 2010 2011 2012 2013 2014 2015 Short Term Rates: Once at zero, Fed moved to QE Long Term Rates: Moving up in anticipation of Taper? www.lairdresearch.com April 18, 2016 Page 11
  • 12. 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 0.620.710.810.901.001.09 USA/CAD 0.550.610.660.720.770.82 Euro/CAD 59.1674.7190.26105.81121.36136.91 Japan/CAD 0.380.440.490.550.610.67 U.K./CAD 0.591.101.602.112.613.12 Brazil/CAD CAD Appreciating CAD Depreciating Change in F/X: Mar 1 2016 to Apr 8 2016 (Trade Weighted Currency Index of USD Trading Partners) āˆ’3.0% āˆ’1.5% 1.5% 3.0% Euro āˆ’2.0% UK 1.9% Japan āˆ’2.0% South Korea āˆ’3.7% China 1.7% India 1.1% Brazil āˆ’5.3% Mexico 2.2% Canada āˆ’0.1% USA āˆ’2.9% Country vs. Average Appreciating Depreciating % Change over 3 months vs. Canada <āˆ’10.0% āˆ’8.0% āˆ’6.0% āˆ’4.0% āˆ’2.0% 0.0% 2.0% 4.0% 6.0% 8.0% >10.0% CAD depreciatingCAD appreciating ARG āˆ’16.8% AUS āˆ’0.8% BRA 0.9% CHN āˆ’10.4% IND āˆ’9.8% RUS 3.2% USA āˆ’11.8% EUR āˆ’8.8% JPY āˆ’4.8% KRW āˆ’8.3% MXN āˆ’8.3% ZAR 1.6% www.lairdresearch.com April 18, 2016 Page 12
  • 13. US Banking Indicators The banking and ļ¬nance industry is a key indicator of the health of the US economy. It provides crucial liquidity to the economy in the form of credit, and the breakdown of that system is one of the exac- erbating factors of the 2008 recession. Key ļ¬gures to track are the Net Interest Margins which determine proļ¬tability (ie. the diļ¬€erence between what a bank pays to depositors versus what the bank is paid by creditors), along with levels of non-performing loans (i.e. loan loss reserves and actual deliquency rates). US Banks Net Interest Margin Percent 3.03.54.04.5 median: 3.94 2015 Q4: 3.02 Repos Outstanding with Fed. Reserve BillionsofDollars 0200400600 median: 58.38 Apr 2016: 258.54 Bank ROE āˆ’ Assets between $300Māˆ’$1B Percent 051015 median: 12.81 2015 Q4: 9.93 Consumer Credit Outstanding %YearlyChange āˆ’505101520 median: 7.52 Feb 2016: 6.61 Total Business Loans %YearlyChange āˆ’2001020 median: 8.62 Mar 2016: 10.41 US Nonperforming Loans Percent 12345 median: 2.05 2015 Q4: 1.55 St. Louis Financial Stress Index Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 0246 median: 0.089 Apr 2016: āˆ’0.81 Commercial Paper Outstanding TrillionsofDollars 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 1.01.41.82.2 median: 1.33 Apr 2016: 1.09 Residential Morgage Delinquency Rate Percent 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 246810 median: 2.33 2015 Q4: 5.17 www.lairdresearch.com April 18, 2016 Page 13
  • 14. US Employment Indicators Unemployment rates are considered the ā€œsingle best indicator of current labour conditionsā€ by the Fed. The pace of payroll growth is highly correlated with a number of economic indicators.Payroll changes are another way to track the change in unemployment rate. Unemployment only captures the percentage of people who are in the labour market who donā€™t currently have a job - another measure is what percentage of the whole population wants a job (employed or not) - this is the Participation Rate. The Beveridge Curve measures labour market eļ¬ƒciency by looking at the relationship between job openings and the unemployment rate. The curve slopes downward reļ¬‚ecting that higher rates of unemploy- ment occur coincidentally with lower levels of job vacancies. Unemployment Rate Percent 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 median: 6.10 Mar 2016: 5.00 4 5 6 7 8 9 10 11 4 5 6 7 8 9 10 11 Percent 4 5 6 7 8 9 10 2.02.53.03.54.0 Beveridge Curve (Unemployment vs. Job Openings) Unemployment Rate (%) JobOpenings(%totalEmployment) Dec 2000 āˆ’ Dec 2008 Jan 2009 āˆ’ Jan 2016 Feb 2016 Participation Rate PercentofPop. 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 6364656667 median: 66.00 Mar 2016: 63.00 Total Nonfarm Payroll Change MonthlyChange(000s) 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’5000500 median: 168 Mar 2016: 215 www.lairdresearch.com April 18, 2016 Page 14
  • 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 a full-time job - they are employed but under-utilitized. Temporary help demand 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 jobs is generally bad, though perhaps not unsurprising in a recovery. Median Duration of Unemployment Weeks 510152025 median: 8.70 Mar 2016: 11.40 (U6) Unemployed + PT + Marginally Attached Percent 810121416 median: 9.80 Mar 2016: 9.80 4āˆ’week moving average of Initial Claims Jan1995=100 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 050100150200 median: 107.15 Apr 2016: 81.48 Unemployed over 27 weeks MillionsofPersons 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 01234567 median: 0.80 Mar 2016: 2.31 Services: Temp Help MillionsofPersons 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 1.52.02.53.0 median: 2.26 Mar 2016: 2.89 āˆ’200 0 200 400 600 15 20 25 30 35 40 Annual Change in Employment Levels (000s of Workers) Averagewages($/hour) Private Industry Employment Change (Mar 2015 āˆ’ Mar 2016) Construction Durable Goods Education Financial Activities Health Services Information Leisure and Hospitality Manufacturing Mining and Logging Nondurable Goods Other Services Professional & Business Services Retail Trade Transportation Utilities Wholesale Trade Circle size relative to total employees in industry www.lairdresearch.com April 18, 2016 Page 15
  • 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 the current business environment. Manufacturing: Real Output YoYPercentChange āˆ’1001020 median: 8.70 Oct 2015: 6.93 ISM Manufacturing āˆ’ PMI 3040506070 Mar 2016: 51.80 manufac. expanding manufac. contracting ISM Manufacturing: New Orders Index 304050607080 Mar 2016: 58.30 Increase in new orders Decrease in new orders Nonāˆ’Manufac. New Orders: Capital Goods BillionsofDollars 40506070 median: 57.99 Feb 2016: 66.97 Average Weekly Hours: Manufacturing 3940414243 median: 41.20 Mar 2016: 41.70 Industrial Production: Manufacturing YoYPercentChange āˆ’15āˆ’50510 median: 3.00 Mar 2016: 0.52 Inventory to Sales Ratio Ratio 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 1.11.21.31.41.51.6 median: 1.37 Feb 2016: 1.41 Chicago Fed: Sales, Orders & Inventory Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’0.50.00.5 Feb 2016: āˆ’0.03 Above ave growth Below ave growth ISM Nonāˆ’Manufacturing Bus. Activity Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 35455565 Mar 2016: 59.80 Growth Contraction www.lairdresearch.com April 18, 2016 Page 16
  • 17. US Consumption Indicators Variations in consumer activity are a leading indicator of the strength of the economy. We track consumer sentiment (their expec- tations about the future), consumer loan activity (indicator of new purchase activity), and new orders and sales of consumer goods. U. Michigan: Consumer Sentiment Index1966Q1=100 5060708090110 median: 88.80 Mar 2016: 91.00 Consumer Loans (All banks) YoY%Change āˆ’10010203040 median: 7.50 Mar 2016: 7.87 Accounting Change Deliquency Rate on Consumer Loans Percentage 2.03.04.0 median: 3.46 Oct 2015: 2.02 New Orders: Durable Consumer Goods YoY%Change āˆ’20020 median: 4.30 Feb 2016: 9.58 New Orders: Nonāˆ’durable Consumer Goods YoY%Change āˆ’2001020 median: 4.17 Feb 2016: āˆ’9.92 Personal Consumption & Housing Index Index āˆ’0.40.00.20.4 median: 0.02 Feb 2016: āˆ’0.09above ave growth below ave growth Light Cars and Trucks Sales MillionsofUnits 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 10121416182022 median: 14.84 Mar 2016: 16.46 Personal Saving Rate Percent 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 246810 median: 5.50 Feb 2016: 5.40 Retail Food and Service Sales YoY%Change(Real) 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’10āˆ’505 median: 2.45 Mar 2016: 0.87 www.lairdresearch.com April 18, 2016 Page 17
  • 18. 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. Since personal consumption is about 70% of the US economy and house val- ues directly impact household wealth, housing is an important indicator in the health of the overall economy. In particular, housing investment was an important driver of the economy getting out of the last few recessions (though not this one so far). Here we track housing prices and especially indicators which show the current state of the housing market. 15 20 25 30 35 150200250300 Personal Income vs. Housing Prices (Inflation adjusted values) NewHomePrice(000's) Disposable Income Per Capita (000's) Feb 2016 r2 : 89.5% Range: Jan 1959 āˆ’ Feb 2016 Blue dots > +5% change in next year Red dots < āˆ’5% change in next year New Housing Units Permits Authorized MillionsofUnits 0.51.01.52.02.5 median: 1.34 Feb 2016: 1.18 New Home Median Sale Price SalePrice$000's 100150200250300 Feb 2016: 301.40 Homeowner's Equity Level Percent 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 4050607080 median: 66.50 2015 Q4: 56.90 New Homes: Median Months on the Market Months 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 468101214 median: 4.90 Feb 2016: 3.80 US Monthly Supply of Homes MonthsSupply 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 4681012 median: 5.90 Feb 2016: 5.60 www.lairdresearch.com April 18, 2016 Page 18
  • 19. US Housing - FHFA Quarterly Index The Federal Housing Finance Agency provides a quarterly survey on house prices, based on sales prices and appraisal data. This gener- ates a housing index for 355 municipal areas in the US from 1979 to present. We have provided an alternative view of this data looking at the 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 start of the housing crisis (deļ¬ned as the maximum price between 2007-2009 for each city). The circled dots are the cities in the survey, while the background colours are interpolated from these points using a loess smoother. Change from 2007 Peak āˆ’ Q4 2015 āˆ’50% āˆ’40% āˆ’30% āˆ’20% āˆ’10% 0% 10% 20% 30% 40% 50% Today's Home Prices Percentage Change from 2007āˆ’2009 Peak Frequency āˆ’75% āˆ’50% āˆ’25% 0% 25% 50% 75% Year over Year Change āˆ’ Q4 2015 āˆ’10% āˆ’8% āˆ’6% āˆ’4% āˆ’2% 0% 2% 4% 6% 8% 10% YoY Change in this quarter YoY Percent Change Frequency āˆ’15% āˆ’10% āˆ’5% 0% 5% 10% 15% www.lairdresearch.com April 18, 2016 Page 19
  • 20. Global Housing The Bank for International Settlements has begun collecting global housing indicies, which are useful for showing what has been happening with global house prices. Note that these are not all the same data set - each country measures housing prices in slightly diļ¬€erent ways, so they are only broadly comparable. Black lines are the data series, blue bars on the right axis show the year over year percent change. Brazil āˆ’ Metro All Dwellings Q12011=100 6080100140 Dec 2015: 137.10 Chile āˆ’ All Dwellings Jun 2015: 127.92 Peru (Lima) āˆ’ All Dwellings Dec 2015: 193.62 āˆ’4002040 Mexico āˆ’ All Dwellings Q12011=100 6080100140 Dec 2015: 126.60 China (Beijing) āˆ’ All Dwellings Dec 2015: 131.55 Hong Kong āˆ’ Residential Prices Jan 2016: 165.29 āˆ’4002040 Indonesia āˆ’ Major Cities housing Q12011=100 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 6080100140 Dec 2015: 135.71 India āˆ’ Major Cities housing 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 Sep 2015: 205.91 Singapore āˆ’ All Dwellings 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 Sep 2015: 100.00 āˆ’4002040 www.lairdresearch.com April 18, 2016 Page 20
  • 21. Philippines (Manila) āˆ’ Flats Q12011=100 6080120 Dec 2015: 146.25 Japan āˆ’ All Dwellings Nov 2015: 104.90 Australia āˆ’ All Dwellings Sep 2015: 126.97 āˆ’4002040 New Zealand āˆ’ All Dwellings Big Cities Q12011=100 6080120 Sep 2015: 153.58 Turkey āˆ’ All Dwellings Dec 2015: 193.00 South Africa āˆ’ Residential Feb 2016: 114.18 āˆ’4002040 Israel āˆ’ All Dwellings Q12011=100 6080120 Nov 2015: 134.11 Korea āˆ’ All Dwellings Feb 2016: 113.99 Russia āˆ’ All Dwellings (Urban) Sep 2015: 123.98 āˆ’4002040 Euro zone āˆ’ All Dwellings Q12011=100 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 6080120 Sep 2015: 99.15 Canada āˆ’ New Houses 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 Jan 2016: 109.60 US āˆ’ New Single Family Houses 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 Dec 2015: 123.48 āˆ’4002040 www.lairdresearch.com April 18, 2016 Page 21
  • 22. Global Business Indicators Global Manufacturing PMI Reports The Purchasing Managersā€™ Index (PMI) is an indicator reļ¬‚ecting purchasing managersā€™ acquisition of goods and services. An index read- ing of 50.0 means that business conditions are unchanged, a number over 50.0 indicates an improvement while anything below 50.0 suggests a decline. The further away from 50.0 the index is, the stronger the change over the month. The chart at the bottom shows a moving av- erage of a number of PMIā€™s, along with standard deviation bands to show a global average. Global Māˆ’PMI āˆ’ March 2016 <40.0 42.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0 >60.0 Steady ExpandingContracting Eurozone 51.6 Global PMI 50.5 TWN 51.1MEX 53.2 KOR 49.5 JPN 49.1 VNM 50.7 IDN 50.6 ZAF 47.0 AUS 58.1 BRA 46.0 CAN 51.5 CHN 49.7 IND 52.4 RUS 48.3 SAU 54.5 USA 51.5 Global Māˆ’PMI Monthly Change <āˆ’5.0 āˆ’4.0 āˆ’3.0 āˆ’2.0 āˆ’1.0 0.0 1.0 2.0 3.0 4.0 >5.0 PMI Change ImprovingDeteriorating Eurozone 0.4 Global PMI 0.5 TWN 1.7MEX 0.1 KOR 0.8 JPN āˆ’1.0 VNM 0.4 IDN 1.9 ZAF āˆ’2.1 AUS 4.6 BRA 1.5 CAN 2.1 CHN 1.7 IND 1.3 RUS āˆ’1.0 SAU 0.1 USA 0.2 Purchase Managers Index (Manufacturing) āˆ’ China, Japan, USA, Canada, France, Germany, Italy, UK, Australia 04 05 06 07 08 09 10 11 12 13 14 15 16 3040506070 3040506070 Business Conditions Contracting Business Conditions Expanding www.lairdresearch.com April 18, 2016 Page 22
  • 23. Global Manufacturing PMI Chart This is an alternate view of the global PMI reports. Here, we look at all the various PMI data series in a single chart and watch their evolution over time. Red numbers indicate contraction (as estimated by PMI) while green numbers indicate expansion. Mar14 Apr14 May14 Jun14 Jul14 Aug14 Sep14 Oct14 Nov14 Dec14 Jan15 Feb15 Mar15 Apr15 May15 Jun15 Jul15 Aug15 Sep15 Oct15 Nov15 Dec15 Jan16 Feb16 Mar16 Australia India Indonesia Viet Nam Taiwan China Korea Japan South Africa Saudi Arabia Turkey Russia United Kingdom Greece Germany France Italy Czech Republic Spain Poland Ireland Netherlands Eurozone Brazil Mexico Canada United States Global PMI 52.4 51.9 52.2 52.6 52.4 52.6 52.2 52.2 51.8 51.6 51.7 52.0 51.7 51.0 51.2 51.0 51.0 50.7 50.7 51.3 51.2 50.7 50.9 50.0 50.5 55.5 55.4 56.4 57.3 55.8 57.9 57.5 55.9 54.8 53.9 53.9 55.1 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 53.3 52.9 52.2 53.5 54.3 54.8 53.5 55.3 55.3 53.9 51.0 48.7 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 51.7 51.8 51.9 51.8 51.5 52.1 52.6 53.3 54.3 55.3 56.6 54.4 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 50.6 49.3 48.8 48.7 49.1 50.2 49.3 49.1 48.7 50.2 50.7 49.6 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 53.0 53.4 52.2 51.8 51.8 50.7 50.3 50.6 50.1 50.6 51.0 51.0 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 53.7 53.4 53.6 52.3 53.5 51.7 52.2 53.0 54.6 53.6 54.1 52.2 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 55.5 56.1 55.0 55.3 55.4 57.3 55.7 56.6 56.2 56.9 55.1 57.5 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 54.0 52.0 50.8 50.3 49.4 49.0 49.5 51.2 53.2 52.8 55.2 55.1 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 52.8 52.7 52.9 54.6 53.9 52.8 52.6 52.6 54.7 53.8 54.7 54.2 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 55.5 56.5 57.3 54.7 56.5 54.3 55.6 54.4 55.6 53.3 56.1 55.6 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 52.4 54.0 53.2 52.6 51.9 49.8 50.7 49.0 49.0 48.4 49.9 51.9 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 52.1 51.2 49.6 48.2 47.8 46.9 48.8 48.5 48.4 47.5 49.2 47.6 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 53.7 54.1 52.3 52.0 52.4 51.4 49.9 51.4 49.5 51.2 50.9 51.1 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 49.7 51.1 51.0 49.4 48.7 50.1 48.4 48.8 49.1 49.4 48.3 48.4 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 55.3 57.3 57.0 57.5 55.4 52.5 51.6 53.2 53.5 52.5 53.1 54.1 54.4 51.9 52.0 51.4 51.9 51.6 51.8 55.5 52.7 51.9 52.9 50.8 51.0 48.3 48.5 48.9 49.1 51.0 51.0 50.4 50.3 51.7 48.9 47.6 49.7 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 51.7 51.1 50.1 48.8 48.5 50.3 50.4 51.5 52.2 51.4 49.8 49.6 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 57.0 58.5 57.0 59.2 60.1 60.7 61.8 59.1 57.6 57.9 57.8 58.5 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 50.3 47.4 44.3 46.6 45.9 49.0 50.7 52.7 50.5 50.2 49.8 50.0 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 53.9 49.4 49.9 51.5 50.5 52.5 51.7 52.4 52.0 52.0 52.2 51.6 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 50.4 50.2 49.5 48.4 49.3 50.3 48.8 48.7 49.0 49.9 51.1 51.1 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 48.0 48.1 49.4 50.7 51.7 50.2 50.2 50.4 50.0 49.6 49.7 50.7 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 52.7 52.3 52.4 54.0 55.8 56.1 53.3 52.0 51.4 50.0 51.7 52.1 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 51.3 53.1 52.5 52.3 51.7 50.3 51.7 51.0 52.1 52.7 51.5 51.7 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 50.1 51.1 52.4 52.7 52.7 49.5 50.7 49.2 48.0 47.6 48.5 47.5 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 51.3 51.3 51.4 51.5 53.0 52.4 51.0 51.6 53.3 54.5 52.9 51.2 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 47.9 44.8 49.2 48.9 50.7 47.3 46.5 49.4 50.1 46.9 49.0 45.4 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 www.lairdresearch.com April 18, 2016 Page 23
  • 24. Canadian Indicators Retail Trade (SA) YoYPercentChange āˆ’50510 median: 4.67 Jan 2016: 6.38 Total Manufacturing Sales Growth YoYPercentGrowth āˆ’20āˆ’1001020 median: 3.83 Feb 2016: 3.85 Manufacturing New Orders Growth YoYPercentGrowth āˆ’30āˆ’100102030 median: 4.08 Feb 2016: 2.58 1yr vs. 10yr Canada Bond Yields Yield(Percent) 0246810 median: 5.66 Mar 2016: 1.22 10 yr bond 1 yr bond Manufacturing PMI 48505254 Mar 2016: 51.50 Sales and New Orders (SA) YoYPercentChange āˆ’20āˆ’1001020 Sales New Orders (smoothed) Tbill Yield Spread (10 yr āˆ’ 3mo) Spread(Percent) 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’101234 median: 1.31 Mar 2016: 0.78 Inflation (total and core) YoYPercentChange 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’101234 median: 1.90 Feb 2016: 1.36 Total Core Inventory to Sales Ratio (SA) Ratio 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 1.31.41.51.6 median: 1.35 Feb 2016: 1.40 www.lairdresearch.com April 18, 2016 Page 24
  • 25. 6.6 6.8 7.0 7.2 7.4 7.6 1.31.41.51.61.71.81.9 Beveridge Curve (Mar 2011 āˆ’ Dec 2015) as.numeric(can.bev$ui.rate) as.numeric(can.bev$vacancies) Mar 2011 āˆ’ Dec 2012 Jan 2013 āˆ’ Nov 2015 Dec 2015 Unemployment Rate JobVacancyrate(Industrial) Ownership/Rental Price Ratio RatioofAccomodationOwnership/RentRatio 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 90100110120130140150 Calgary Montreal Vancouver Toronto Note: Using prices relative to 2002 as base year Ownership relatively more expensive vs 2002 Rent relatively more expensive vs 2002 Unemployment Rate (SA) Percent 345678910 Canada 7.1% Alberta 7.1% Ontario 6.8% Debt Service Ratios (SA) Percent 0246810 Total Debt: 6.2% Mortgage: 3.2% Consumer Debt: 6.2% Housing Starts and Building Permits (smoothed) YoYPercentChange 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’40āˆ’2002040 Permits Starts www.lairdresearch.com April 18, 2016 Page 25
  • 26. European Indicators Unemployment Rates Percentage 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 051015202530 FR DE GB IT GR ES EU Business Employment Expectations Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’40āˆ’20010 Industrial Orderbook Levels Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’60āˆ’40āˆ’20020 Country Employment Expect. Unempl. (%) Bond Yields (%) Retail Turnover Manufacturing Turnover Inļ¬‚ation (YoY %) Industry Orderbook PMI Series Dates Mar 2016 Mar 2016 Mar 2016 Feb 2016 Feb 2016 Mar 2016 Mar 2016 Mar 2016 France -6.9 I 10.2 K 0.51 J 111.9 I 105.1 J -0.1 K -14.0 J 49.6 J Germany -5.7 J 4.3 K 0.17 K NA 114.5 J 0.1 I -12.2 I 50.7 I United Kingdom 3.2 I 5.0 K 1.46 I 113.8 J NA 0.5 -16.6 I 51.0 I Italy -1.6 I 11.7 I 1.38 J 100.6 J NA -0.2 K -13.5 I 53.5 I Greece -4.3 J 24.4 I 9.12 J NA NA -0.7 J -26.3 I 49.0 I Spain 6.5 I 20.4 J 1.54 J NA NA -1.0 K -5.4 I 53.4 J Eurozone (EU28) -2.2 I 8.9 K 1.19 J 108.0 J 109.8 I 0.0 -13.8 I NA www.lairdresearch.com April 18, 2016 Page 26
  • 27. Government Bond YieldsLongTermYields% 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 0246810 Economic Sentiment Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 60708090110130 Consumer Confidence Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’100āˆ’60āˆ’20020 Inflation (Harmonized Prices) 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 median: 1.90 Mar 2016: 0.00 āˆ’1 0 1 2 3 4 5 6 7 Harmonized Inflation: Feb 2016 AUT 0.6% BGR āˆ’1.9% DEU 0.1% ESP āˆ’1.0% FIN 0.0% FRA āˆ’0.1% GBR 0.5% GRC āˆ’0.7% HRV āˆ’0.9% HUN āˆ’0.2% IRL āˆ’0.6% ISL 0.3% ITA āˆ’0.2% NOR 3.6% POL āˆ’0.4% ROU āˆ’2.4% SWE 1.2% <āˆ’1.0%0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% >7.0% YoY % Change in Prices PMI: March 2016 <40.042.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0>60.0 Steady ExpandingContracting BRA 46.0 CAN 51.5 DEU 50.7 ESP 53.4 FRA 49.6 GBR 51.0 GRC 49.0 IRL 54.9 ITA 53.5 MEX 53.2 POL 53.8 SAU 54.5 TUR 49.2 USA 51.5 RUS 48.3 PMI Change: Feb āˆ’ Mar <āˆ’5.0āˆ’4.0 āˆ’3.0 āˆ’2.0 āˆ’1.0 0.0 1.0 2.0 3.0 4.0 >5.0 PMI Change ImprovingDeteriorating CAN 2.1 DEU 0.2 ESP āˆ’0.7 FRA āˆ’0.6 GBR 0.2 GRC 0.6 IRL 2.0 ITA 1.3 POL 1.0 TUR āˆ’1.1 USA 0.2 RUS āˆ’1.0 www.lairdresearch.com April 18, 2016 Page 27
  • 28. Chinese Indicators Tracking the Chinese economy is a tricky. As reported in the Fi- nancial Times, Premier Li Keqiang conļ¬ded to US oļ¬ƒcials in 2007 that gross domestic product was ā€œman madeā€ and ā€œfor reference onlyā€. 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 oļ¬ƒcial version put out by the Chinese government and diļ¬€ers slightly from an HSBC version. Finally we include the Shanghai Composite 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 4045505560 Mar 2016: 49.70 Shanghai Composite Index IndexValue(MonthlyHigh/Low) 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 0100030005000 Apr 2016: 3009.53 Electricity Generated 100MillionKWH(logscale) 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 1000200030005000 Feb 2016: 4351.00 Electricity Generated Long Term Trend Short Term Average Consumer Confidence Index Index 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 98100102104106108110 median: 103.95 Feb 2016: 104.40 Exports YoYPercentChange 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 āˆ’20020406080 median: 18.35 Feb 2016: āˆ’25.40 Retail Sales Growth YoYPercentChange 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 101520 median: 12.90 Jan 2016: 10.20 www.lairdresearch.com April 18, 2016 Page 28
  • 29. Global Climate Change Temperature and precipitation data are taken from the US National Climatic Data Center and presented as the average monthly anomaly from the previous 6 months. Anomalies are deļ¬ned as the diļ¬€erence from the average value over the period from 1971-2000 for the tem- perature map and over the 20th century for the global temparature chart. Average Temperature Anomalies from Sep 2015 - Feb 2016 <āˆ’4.0 āˆ’3.0 āˆ’2.0 āˆ’1.0 0.0 1.0 2.0 3.0 >4.0 Anomalies in Celcius WarmerCooler Anomalies in Celcius āˆ’4 āˆ’2 0 2 4 Historic Global Temperature Deviations DegreesCelciusDeviations āˆ’0.50.00.51.0 Feb 2016: 1.21 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 www.lairdresearch.com April 18, 2016 Page 29