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Global economics report 2017-04-14

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A monthly summary of global economic performance including employment, trade, business conditions, leading indicators and regional data.

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Global economics report 2017-04-14

  1. 1. .... 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 few changes to the report – in particular two new features: sentiment anal- ysis (p. 18) and a US economic heartbeat (p. 4). We’ll be making more changes over the next few months. Sentiment analysis is a technique that tries to use machine learning to determine the sentiment, positive or negative, of a block of text. In this case, we’re using conference call transcripts for the S&P 500 companies. We’re presenting the sentiment of the conference calls (ie. was it an upbeat or downbeat conference call) and plotting that against operating earnings for each component. There seems to be a good cor- relation between the two – and as we have much more conference call data, which is updated more often, this is a good predictor of earnings trends. The US Economic Heartbeat is a tool for summarizing the position of the US economy. We’ve been able to get a good monthly dataset of various measures of the economy and have pulled out the business cycle component of the data. The tracker shows a consistent pattern when we are in the midst of a recession – right now the economy feels as though it could go either way, but when it does break, this tool should help 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 strong uptick in the recent data, which is usually an indicator that something is 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
  2. 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 Fed’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 financial 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 17 −2−10123 median: 1.50 Dec 2016: 1.17 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 17 200300400500600 median: 346.62 Apr 2017: 247.25 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 17 394041424344 median: 40.60 Mar 2017: 41.80 Manfacturing − PMI Index:SteadyState=50 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 3040506070 median: 52.70 Mar 2017: 53.30expanding economy contracting economy www.lairdresearch.com April 14, 2017 Page 2
  3. 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 Fed’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 financial 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 17 150200250 median: 186.49 Feb 2017: 235.96 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 17 100110120130140 median: 113.50 Feb 2017: 138.40 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 17 40506070 median: 58.58 Feb 2017: 64.74 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 17 5060708090100110 median: 89.10 Mar 2017: 96.90 www.lairdresearch.com April 14, 2017 Page 3
  4. 4. US Economic Heartbeat MarketHack Inc. is proud to present our proprietary Economic Heartbeat index. It uses monthly economic data from 1960 onwards to create a diffusion index. Each point represents the index value for a 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/monetary policy. 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Good Times Danger Zone Recession Recovery Recession Recovery Recession Recovery Recession Recovery Recession Recovery Recession Recovery Recession Recovery YOU ARE HERE Recession months Non−recession months Current month (Jan 2017) www.lairdresearch.com April 14, 2017 Page 4
  5. 5. 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 13 2,328.9 -1.2% J -1.9% J 2.4% I 11.8% I 1.00 0.66 USA NASDAQ Composite Apr 13 5,805.1 -1.3% J -1.2% J 4.1% I 17.3% I 0.89 0.58 USA Wilshire 5000 Total Market Apr 13 24,262.6 -1.2% J -1.6% J 1.9% I 13.0% I 0.96 0.66 Canada S&P TSX Apr 13 15,535.5 -1.0% J -0.1% J 0.2% I 13.6% I 0.66 1.00 Europe and Russia France CAC 40 Apr 13 5,071.1 -1.0% J 1.4% I 3.0% I 12.9% I 0.62 0.53 Germany DAX Apr 13 12,109.0 -1.0% J 1.0% I 4.1% I 20.8% I 0.61 0.50 Russia Market Vectors Russia ETF Apr 13 20.1 -5.7% J 0.9% I -6.5% J 18.5% I 0.42 0.53 Asia Taiwan TSEC weighted index Apr 13 9,836.7 -0.6% J 1.4% I 4.9% I 13.7% I -0.09 0.01 China Shanghai Composite Index Apr 13 3,276.0 -0.2% J 1.2% I 5.2% I 6.8% I 0.06 0.05 Japan NIKKEI 225 Apr 13 18,426.8 -0.9% J -6.1% J -4.5% J 12.5% I 0.27 0.28 Hong Kong Hang Seng Apr 13 24,261.7 -0.0% J 1.8% I 5.8% I 14.7% I -0.06 0.04 Korea Kospi Apr 13 2,148.6 -0.2% J 1.5% I 3.5% I 6.6% I -0.03 -0.07 South Asia and Austrailia India Bombay Stock Exchange Apr 13 29,461.4 -1.6% J 0.1% I 8.2% I 15.0% I 0.04 -0.04 Indonesia Jakarta Apr 13 5,616.5 -1.1% J 3.8% I 6.5% I 15.7% I -0.13 0.01 Malaysia FTSE Bursa Malaysia KLCI Apr 13 1,738.2 -0.1% J 0.9% I 3.9% I 0.9% I 0.03 0.13 Australia All Ordinaries Apr 13 5,925.9 0.5% I 2.3% I 2.6% I 15.6% I 0.10 0.16 New Zealand NZX 50 Index Gross Apr 13 7,229.8 -0.8% J 0.5% I 2.6% I 6.7% I 0.02 0.09 South America Brasil IBOVESPA Apr 13 62,826.0 -2.2% J -4.1% J -1.3% J 18.2% I 0.35 0.49 Argentina MERVAL Buenos Aires Apr 12 20,812.2 0.6% I 8.5% I 11.9% I 64.0% I 0.24 0.51 Mexico Bolsa index Apr 12 48,955.8 -0.5% J 3.9% I 6.3% I 8.6% I 0.34 0.41 MENA and Africa Egypt Market Vectors Egypt ETF Apr 13 28.3 -1.2% J 1.1% I 3.4% I -27.1% J 0.07 0.14 (Gulf States) Market Vectors Gulf States ETF Oct 07 23.0 3.2% I 1.2% I 6.4% I -6.4% J 0.16 0.05 South Africa iShares MSCI South Africa Index Apr 13 57.2 5.4% I 0.8% I 3.0% I 8.7% I 0.42 0.44 (Africa) Market Vectors Africa ETF Apr 13 21.3 2.0% I 3.5% I 1.2% I 11.7% I 0.31 0.35 Commodities USD Spot Oil West Texas Int. Apr 10 $53.1 5.6% I 10.4% I 4.4% I 31.1% I 0.16 0.41 USD Gold LME Spot Apr 13 $1,286.1 2.6% I 6.5% I 7.5% I 3.2% I -0.17 -0.14 Note: Correlations are based on daily arithmetic returns for the most recent 100 trading days. www.lairdresearch.com April 14, 2017 Page 5
  6. 6. S&P 500 Composite Index The S&P 500 Composite Index is widely regarded as the best single gauge of the large cap U.S. equities market. A key figure is the valua- tion level of the S&P500 as measured by the Price/Earnings ratio. We present two versions: (1) a 12-month trailing earnings version which reflects current earnings but is skewed by short term variances and (2) a cyclically adjusted version which looks at the inflation adjusted earn- ings over a 10 year period (i.e. at least one business cycle). Forecasted earnings numbers are estimates provided by S&P. S&P 500 Profit Margins and Overall Corporate Profit Margins (Trailing 12 months) Percent 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 14 Percent Total Corporate Profits (% of GDP) − median: 6.2%, Q4/16: 9.2% Net Profit Margin (S&P 500 Earnings / Revenue) − median: 6.7%, Q4/16: 8.2% S&P Quarterly Earnings (USD$ 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 18 Estimates −5.00 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 −5.00 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 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 18 0 10 20 30 40 50 0 10 20 30 40 50 Multiple Multiple 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
  7. 7. 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 SYF STI 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 BCR A 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 WM CMI PCAR IR ROP PH ROK AYI XOM −1.6% CVX −6.8% SLB −5% COP EOG OXY KMI HAL PSX PXD 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 Consumer Discretionary Consumer Staples Industrials Energy Utilities Real Estate Materials Telecommunication 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 Median Sector Change P/Sales P/Book P/E Utilities 1.5% I 2.2 2.0 21.6 Real Estate 0.7% I 8.7 2.8 31.2 Consumer Staples 0.0% I 2.6 4.8 25.0 Consumer Discretionary -0.2% J 1.6 3.7 18.7 Information Technology -0.9% J 3.7 5.0 26.4 Health Care -1.7% J 3.7 4.0 27.3 Average Median Median Median Sector Change P/Sales P/Book P/E Telecommunication Services -1.8% J 1.5 2.0 20.5 Materials -3.2% J 1.9 4.1 26.5 Industrials -3.7% J 1.8 4.2 23.4 Energy -3.8% J 3.4 2.0 22.6 Financials -8.7% J 2.9 1.5 16.3 www.lairdresearch.com April 14, 2017 Page 7
  8. 8. US Equity Valuations A key valuation metric is Tobin’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 Buffet famously follows 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 has valuations correct, we can determine the required returns of future es- timated earnings. These are quoted for both debt (using BBB rated securities as a proxy) and equity premiums above the risk free rate (10 year US Treasuries). These figures 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 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
  9. 9. US Mutual Fund Flows Fund flows describe the net investments in equity and bond mutual funds as well as ETF’s in the US market, as described in ICI’s “Trends in Mutual Fund Investing” report. Previously we just looked at mutual fund flows, but with the global trend to ETF’s, this only presented a partial picture. US Net New Investment Cash Flow to Mutual Funds & ETFs US$billions(monthly) 2014 2015 2016 2017 −40−2002040 Domestic Equity World Equity Taxable Bonds Municipal Bonds US Net New Investment Cash Flow to Mutual Funds & ETFs US$billions(Monthly) 2014 2015 2016 2017 −60−40−200204060 Flows to Equity Flows to Bonds Net Market Flows www.lairdresearch.com April 14, 2017 Page 9
  10. 10. US Key Interest Rates Interest rates are often leading indicators of stress in the financial 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 BBB bonds) or between government loans (LIBOR vs Fedfunds - the infamous “TED Spread”). Here a spike correlates to an aversion to risk, which is an indication that something bad is happen- ing. US Treasury Yield Curves ForwardInstantaneousRates(%) 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 3.0 Apr 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 Treasury 3 Mo Treasury Spread AAA vs. BBB Bond Spreads 2% 3% 4% 5% 6% 7% 8% 9% 10% 2% 3% 4% 5% 6% 7% 8% 9% 10% Percent AAA BBB 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 median: 112.00 Apr 2017: 66.00 0 100 200 300 400 0 100 200 300 400 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 t−bill LIBOR 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 median: 36.61 Apr 2017: 34.54 0 100 200 300 0 100 200 300 Spread(bps) www.lairdresearch.com April 14, 2017 Page 10
  11. 11. US Inflation Generally, the US Fed tries to anchor long run inflation expectations to approximately 2%. Inflation 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 inflation (usually called Core Inflation). The Fed seems to think PCI more accurately reflects the 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 an imputed forward inflation expectation. The 5y5y chart shows expected 5 year inflation 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 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 Percent(YearoverYear) 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 −10123456 PCE Inflation Rate YoY% (Aug = 0.96%) PCE Core Inflation YoY% (Aug = 1.7%) 5−Year, 5−Year Forward Inflation Expectation Rate Percent 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 −10123456 5 year forward Inflation Expectation Actual 5yr Inflation (CPI measure) Actual 5yr Inflation (PCE Measure) www.lairdresearch.com April 14, 2017 Page 11
  12. 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 17 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: 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 Appreciating Depreciating % 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% EUR 1.6% JPY 6.0% KRW 6.9% MXN −3.1% ZAR 10.3% www.lairdresearch.com April 14, 2017 Page 12
  13. 13. US Banking Indicators The banking and finance 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 figures to track are the Net Interest Margins which determine profitability (ie. the difference 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 3.03.54.04.5 median: 3.93 Oct 2016: 3.05 Repos Outstanding with Fed. Reserve BillionsofDollars 0200400600 median: 62.03 Apr 2017: 357.43 Bank ROE − Assets between $300M−$1B Percent 051015 median: 12.68 Oct 2016: 9.93 Consumer Credit Outstanding %YearlyChange −505101520 median: 7.41 Feb 2017: 6.31 Total Business Loans %YearlyChange −2001020 median: 8.63 Feb 2017: 5.39 US Nonperforming Loans 12345 median: 1.95 Oct 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 −112345 median: −0.001 Apr 2017: −1.37 Commercial Paper Outstanding TrillionsofDollars 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 1.01.41.82.2 median: 1.31 Apr 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 246810 median: 2.36 Oct 2016: 4.15 www.lairdresearch.com April 14, 2017 Page 13
  14. 14. US Charge-Off Indication A “charge-off” is an accounting declaration by a creditor that a particular 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 determination is 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 the health of creditors. In this graph, the various charge-offs are presented as a percentage of total relevant debt outstanding. For example, credit card 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 Percent 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
  15. 15. US Employment Indicators Unemployment rates are considered the “single best indicator of current labour conditions” 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 don’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 efficiency by looking at 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 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 18 median: 6.10 Mar 2017: 4.50 4 5 6 7 8 9 10 11 4 5 6 7 8 9 10 11 Percent Beveridge Curve Unemployment Rate HelpWantedIndex 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 90 100 110 1950's 1960's 1970's 1980's 1990's 2000's 2010's Participation Rate PercentofPop. 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 6364656667 median: 66.00 Mar 2017: 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 17 −5000500 median: 164 Mar 2017: 98 www.lairdresearch.com April 14, 2017 Page 15
  16. 16. 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: 8.90 Mar 2017: 10.30 (U6) Unemployed + PT + Marginally Attached Percent 810121416 median: 9.70 Mar 2017: 8.90 4−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 17 50100150200 median: 106.57 Apr 2017: 76.02 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 17 01234567 median: 0.82 Mar 2017: 1.76 Services: Temp Help MillionsofPersons 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 1.52.02.53.0 median: 2.29 Mar 2017: 3.00 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 2016 − Mar 2017) 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 14, 2017 Page 16
  17. 17. 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 −1001020 median: 7.87 Oct 2016: 3.26 Manufacturing − PMI 354045505560 Mar 2017: 53.30 manufac. expanding manufac. contracting Manufacturers' Durable Goods Orders BillionsofDollars 150200250 Feb 2017: 235.96 Increase in new orders Decrease in new orders Non−Manufac. New Orders: Capital Goods BillionsofDollars 40506070 median: 58.58 Feb 2017: 64.74 Average Weekly Hours: Manufacturing 3940414243 median: 41.20 Mar 2017: 41.80 Industrial Production: Manufacturing YoYPercentChange −15−50510 median: 2.86 Feb 2017: 1.50 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 17 1.11.21.31.41.51.6 median: 1.37 Jan 2017: 1.35 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 17 −0.50.00.5 Feb 2017: 0.08 Above 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 95105115125 Feb 2017: 126.40 www.lairdresearch.com April 14, 2017 Page 17
  18. 18. S&P 500 Sentiment Analysis Sentiment analysis tries to determine the attitude of a speaker with respect to some topic or the overall contextual polarity of a document. In this particular case, we are evaluating earnings conference calls for the 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 the arbitrary date of January 2012. While it is not an exact science, the models do capture the significant negative sentiment in 2007-2008 and the subsequent recovery. −1500−50005001500 Normalized Sentiment (Based on 17,948 Earnings Calls) SentimentValue(IndexJan2012=0) 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 CD CD: +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 Ut Ut: +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) Utilities S&P 500 Sentiment Increasing Sentiment Decreasing −1000100200 Month over Month Sentiment Change − Apr 2017 +72 +49 +88 +98 +5 +162 +69 +23 +103 +98 +2 Consumer Discretionary Consumer Staples Energy Financials Health Care Industrials Information Technology Materials Real Estate Telecommunications Services Utilities www.lairdresearch.com April 14, 2017 Page 18
  19. 19. 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
  20. 20. 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
  21. 21. 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: 89.10 Mar 2017: 96.90 Consumer Loans (All banks) YoY%Change −10010203040 median: 7.63 Feb 2017: 6.92 Accounting Change Deliquency Rate on Consumer Loans Percentage 2.03.04.0 median: 3.42 Oct 2016: 2.15 New Orders: Durable Consumer Goods YoY%Change −20020 median: 4.35 Feb 2017: −4.20 New Orders: Non−durable Consumer Goods YoY%Change −2001020 median: 3.75 Feb 2017: 13.36 Personal Consumption & Housing Index Index −0.40.00.20.4 median: 0.02 Feb 2017: −0.03above 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 17 10121416182022 median: 14.91 Mar 2017: 16.53 Personal Saving Rate Percent 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 246810 median: 5.70 Feb 2017: 5.60 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 17 −10−505 median: 2.45 Feb 2017: 2.79 www.lairdresearch.com April 14, 2017 Page 21
  22. 22. 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 40 150200250300 Personal Income vs. Housing Prices (Inflation adjusted values) NewHomePrice(000's) Disposable Income Per Capita (000's) February 2017 r2 : 89.9% Range: Jan 1962 − Feb 2017 Blue dots > +5% change in next year Red dots < −5% change in next year New Housing Units Permits Authorized MillionsofUnits 0.51.01.52.02.5 median: 1.33 Feb 2017: 1.22 New Home Median Sale Price SalePrice$000's 100200300 Feb 2017: 296.20 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 17 4050607080 median: 66.50 Oct 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 468101214 median: 4.90 Feb 2017: 3.40 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 17 4681012 median: 5.80 Feb 2017: 5.40 www.lairdresearch.com April 14, 2017 Page 22
  23. 23. 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 (defined 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 − Q2 2016 −50% −40% −30% −20% −10% 0% 10% 20% 30% 40% 50% Today's Home Prices Percentage Change from 2007−2009 Peak Frequency −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 Frequency −15% −10% −5% 0% 5% 10% 15% www.lairdresearch.com April 14, 2017 Page 23
  24. 24. Global Business Indicators Global Manufacturing PMI Reports The Purchasing Managers’ Index (PMI) is an indicator reflecting purchasing managers’ 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 PMI’s, along with standard deviation bands to show 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 Eurozone 56.2 Global PMI 53.0 TWN 56.2MEX 51.5 KOR 48.4 JPN 52.4 VNM 54.6 IDN 50.5 ZAF 50.7 AUS 57.5 BRA 49.6 CAN 55.5 CHN 51.2 IND 52.5 RUS 52.4 SAU 56.4 USA 53.3 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 Eurozone 0.8 Global PMI 0.0 TWN 1.7MEX 0.9 KOR −0.8 JPN −0.9 VNM 0.4 IDN 1.2 ZAF 0.2 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 3040506070 3040506070 Business Conditions Contracting Business Conditions Expanding www.lairdresearch.com April 14, 2017 Page 24
  25. 25. 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. Mar15 Apr15 May15 Jun15 Jul15 Aug15 Sep15 Oct15 Nov15 Dec15 Jan16 Feb16 Mar16 Apr16 May16 Jun16 Jul16 Aug16 Sep16 Oct16 Nov16 Dec16 Jan17 Feb17 Mar17 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
  26. 26. Global Trade/Export Metrics The CPB Netherlands Bureau for Economic Policy Analysis pub- lishes the World Trade Monitor. The WTM summarizes worldwide monthly data on international trade and production. Data is from a variety of sources, which are normalized into a set of indexed curves which show trends in world trade. World Imports and Exports Index:2010=100 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 708090100110120 Exports Imports World Exports by Region Index:2010=100 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 60708090100110120130 USA Japan Euro Area Latin America Africa & Middle East Emerging Asia www.lairdresearch.com April 14, 2017 Page 26
  27. 27. Canadian Indicators Retail Trade (SA) YoYPercentChange −50510 median: 4.61 Jan 2017: 4.49 Total Manufacturing Sales Growth YoYPercentGrowth −20−1001020 median: 3.56 Feb 2017: 6.81 Manufacturing New Orders Growth YoYPercentGrowth −30−100102030 median: 4.01 Feb 2017: 12.58 1yr vs. 10yr Canada Bond Yields Yield(Percent) 0246810 median: 5.54 Mar 2017: 1.59 10 yr bond 1 yr bond Manufacturing PMI 48505254 Mar 2017: 55.50 Sales and New Orders (SA) YoYPercentChange −20−1001020 Sales New Orders (smoothed) Tbill Yield Spread (10 yr − 3mo) Spread(Percent) 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 −101234 median: 1.28 Mar 2017: 1.05 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 17 −101234 median: 1.86 Feb 2017: 2.05 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 17 1.31.41.51.6 median: 1.35 Feb 2017: 1.34 www.lairdresearch.com April 14, 2017 Page 27
  28. 28. 6.6 6.8 7.0 7.2 7.4 7.6 1.21.31.41.51.61.71.81.9 Beveridge Curve (Mar 2011 − Dec 2016) as.numeric(can.bev$ui.rate) as.numeric(can.bev$vacancies) Mar 2011 − Dec 2012 Jan 2013 − Nov 2016 Dec 2016 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 17 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 6.7% Alberta 8.4% Ontario 6.4% Debt Service Ratios (SA) Percent 0246810 Total Debt: 6.1% Mortgage: 3.0% Consumer Debt: 6.3% 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 17 −40−2002040 Permits Starts www.lairdresearch.com April 14, 2017 Page 28
  29. 29. 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 17 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 17 −40−20010 Industrial Orderbook Levels Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 −60−40−20020 Country Employment Expect. Unempl. (%) Bond Yields (%) Retail Turnover Manufacturing Turnover Inflation (YoY %) Industry Order- book PMI Series Dates Mar 2017 Mar 2017 Mar 2017 Feb 2017 Feb 2017 Feb 2017 Mar 2017 Mar 2017 France -4.8 J 10.0 K 1.02 J 114.7 I 107.5 J 1.4 J -10.7 J 53.3 I Germany 3.9 J 3.9 K 0.35 I NA 118.9 I 2.2 I -1.8 J 58.3 I United Kingdom Of Great Britain And Northern Ireland 11.9 I 4.5 J 1.13 J 120.4 I NA 1.8 I 6.8 I 54.2 J Italy 4.3 I 11.5 J 2.40 I 102.6 J NA 1.6 I -6.5 I 55.7 I Greece 2.7 J 23.5 K 7.17 J NA NA 1.4 J -20.9 I 46.7 J Spain 4.0 J 18.0 J 1.72 I NA NA 3.0 I -1.8 J 53.9 J Eurozone (EU28) 4.6 I 8.0 J 1.44 K 112.8 I 115.5 I 1.9 I -4.8 K NA www.lairdresearch.com April 14, 2017 Page 29
  30. 30. Government Bond YieldsLongTermYields% 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 0246810 Economic Sentiment Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 60708090110130 Consumer Confidence Index 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 −100−60−20020 Inflation (Harmonized Prices) 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 median: 1.90 Feb 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 BRA 49.6 CAN 55.5 DEU 58.3 ESP 53.9 FRA 53.3 GBR 54.2 GRC 46.7 IRL 53.6 ITA 55.7 MEX 51.5 POL 53.5 SAU 56.4 TUR 52.3 USA 53.3 RUS 52.4 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
  31. 31. 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 that gross 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 and differs 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 17 4045505560 Mar 2017: 51.20 Shanghai Composite Index IndexValue(MonthlyHigh/Low) 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 0100030005000 Apr 2017: 3273.83 Electricity Generated 100MillionKWH(logscale) 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 1000200030005000 Feb 2017: 4657.50 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 17 100105110 median: 104.05 Feb 2017: 112.60 Exports YoYPercentChange 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 −20020406080 median: 17.80 Mar 2017: 16.40 Retail Sales Growth YoYPercentChange 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 101520 median: 12.75 Feb 2017: 9.50 www.lairdresearch.com April 14, 2017 Page 31
  32. 32. Global Climate Data 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 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 temparature chart. Average Temperature Anomalies from Sep 2016 - Feb 2017 <−4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 >4.0 Anomalies in Celsius WarmerCooler Anomalies in Celcius −4 −2 0 2 4 Historic Global Temperature Deviations DegreesCelsiusDeviations −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
  33. 33. Subscription Info The Global Economics Report is published by Laird Research Inc. To sign up for a FREE subscription to this report, please visit our website: LairdResearch.com. Comments or suggestions? We’d love to hear from you! Disclaimer: This document has been prepared in good faith on the basis of information available at the date of publication without any independent verification. Laird Research Inc. collects its data from public sources which it believes to be accurate, however it does not guarantee or warrant the accuracy, reliability, completeness or currency of the information in this publication nor its usefulness in achieving any purpose. Readers are responsible 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 be reproduced in any form without written permission from Laird Research Inc. Note that the data provided herein is collected from publicly available sources, 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

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