Sectors

Equities have been rising at a dizzying speed year-to-date, as investors have extrapolated the tax reform EPS tailwind far into the future in a very short time span. The risk of a tactical, and likely short lived, 5-10% pullback is very high. Putting this potential correction in perspective is in order. A drop in the SPX to near its 50-day moving average would set the market back 6%, to near the 2,700 mark. As a reminder, the S&P 500 crossed 2,700 on January 3, 2018. A 10% drawdown would push the market below 2,600, a level first surpassed on Black Friday (top panel). While steep stock price increases are not unprecedented, at the current juncture all of our tactical indicators suggest that caution is warranted (please refer to the January 22 and January 29 Weekly Reports for more details). The equity market volatility curve has inverted and is now in backwardation, warning that the tactical pullback has yet to run its course (middle panel). The way we recommend defending against such exuberance is to book gains in high-beta pair trades, institute trailing stops to the high-conviction list high flyers and make some subsurface changes to intra-sector positioning. From a cyclical perspective we remain constructive on the broad market and given our view of no recession in the coming 9-12 months our investment strategy is to "buy the dip". Please see yesterday's report for additional details. Hunker Down Hunker Down

Highlights Chart 1Waiting For A Signal Waiting For A Signal Waiting For A Signal TIPS breakeven inflation rates are fast approaching our end-of-cycle targets (Chart 1). The 10-year and 5-year/5-year rates are currently 2.14% and 2.36% respectively, only slightly below our target range of 2.4% to 2.5%. If this trend continues it is highly likely that we will start to slowly reduce the credit risk in our portfolio in the coming weeks. Already, we find that some lower risk spread products (Foreign Agency bonds and Munis) are attractively valued relative to corporates. But there are also risks to exiting credit too early. First and foremost is that the recent widening in TIPS breakevens might reverse before it bleeds into higher core inflation. As we noted in last week's report, the St. Louis Fed's Price Pressures Measure is still supportive of an overweight allocation to corporate bonds (Chart 1, bottom panel) and core PCE inflation has only just risen to 1.5% year-over-year.1 Investors should maintain below-benchmark duration and an overweight allocation to corporate bonds for now, but be wary that the time to make end-of-cycle preparations is drawing nearer. Feature Investment Grade: Overweight Chart 2Investment Grade Market Overview Investment Grade Market Overview Investment Grade Market Overview Investment grade corporate bonds outperformed the duration-equivalent Treasury index by 72 basis points in January. The average index option-adjusted spread tightened 7 bps on the month, and currently sits at 85 bps. Investment grade corporate bond spreads continue to tighten, and with each additional basis point the evidence of extreme overvaluation grows. As of today, the 12-month breakeven spread for an A-rated corporate bond has only been tighter 3% of the time since 1989 (Chart 2). The same measure for a Baa-rated bond has only been tighter 4% of the time (panel 3). Further, the average spread on the Foreign Agency bond index is now 3 bps greater than the average spread of an equivalent-duration corporate bond, despite having an average credit rating that is three notches higher (Aa2/Aa3 versus A3/Baa1). Even a 10-year Aaa-rated Municipal bond now offers 7 bps greater after-tax yield than a duration-equivalent corporate bond for investors in the top marginal tax bracket (see page 9). The bottom line is that with such poor value in investment grade corporate spreads, we only need to see a stronger signal from our inflation indicators before reducing exposure.2 Depending on how inflation (and TIPS breakevens) evolve, that time could come relatively soon. The Federal Reserve's Senior Loan Officer Survey, released yesterday, showed that lending standards for commerical & industrial (C&I) loans eased somewhat in the fourth quarter of 2017, and also noted that banks expect to ease standards further on C&I loans to large and middle-market firms in 2018. Table 3ACorporate Sector Relative Valuation And Recommended Allocation* Warning Signs Warning Signs Table 3BCorporate Sector Risk Vs. Reward* Warning Signs Warning Signs High-Yield: Overweight Chart 3High-Yield Market Overview High-Yield Market Overview High-Yield Market Overview High-Yield outperformed the duration-equivalent Treasury index by 149 basis points in January. The average index option-adjusted spread tightened 24 bps on the month, and currently sits at 324 bps. Last week's equity sell-off and spike in the VIX suggest that some near-term junk spread widening could be in the cards (Chart 3). However, we expect it is still a bit too soon to move out of junk bonds for the cycle. That decision will be made based on whether our inflation indicators continue to rise in the coming weeks and/or months, suggesting that the monetary policy back-drop is becoming less accommodative. In terms of value, high-yield corporates offer better risk-adjusted value than their investment grade brethren. The 12-month breakeven spread for a Ba-rated high-yield bond has currently been tighter than it is today 14% of the time since 1995. The same figure comes in at 25% for a B-rated bond and 31% for a Caa-rated bond. Similar measures for investment grade corporates are significantly lower (see page 3). Further, assuming a default rate of 2.35% for the next 12 months and a recovery rate of 51%, we calculate that a position in high-yield bonds will return 209 bps in excess of Treasuries if spreads stay flat at current levels. Another 100 bps of spread tightening would imply an excess return of just over 6%, but this would bring junk spreads to all-time tight valuations and is probably too optimistic. Remain overweight high-yield for now. MBS: Neutral Chart 4MBS Market Overview MBS Market Overview MBS Market Overview Mortgage-Backed Securities underperformed the duration-equivalent Treasury index by 15 basis points in January. The conventional 30-year zero-volatility MBS spread narrowed 2 bps on the month, all concentrated in the compensation for prepayment risk (option cost). The option-adjusted spread (OAS) was flat on the month, and currently sits at 29 bps. After having widened for most of last year, the OAS for a conventional 30-year mortgage bond is now more attractive relative to an equivalent-duration investment grade corporate bond than at any time since 2014 (Chart 4). This makes MBS a reasonably attractive sector for investors looking to shift away from corporate bonds and de-risk their spread product portfolios. Further, there would appear to be very little risk of spread widening in the MBS sector. First, the schedule of run-off from the Fed's mortgage portfolio is already well known, and likely in the price. Second, mortgage refinancings are likely to stay contained in a rising interest rate environment (bottom panel). Finally, the risk of duration extension in MBS only becomes material when Treasury yields spike higher very quickly - on the order of 72 bps or more in a month - as we showed in last week's report.3 Investors should stay at neutral on MBS for now, but stand ready to increase exposure when the time comes to move out of corporate bonds for the cycle. Government-Related: Underweight Chart 5Government-Related Market Overview Government-Related Market Overview Government-Related Market Overview The Government-Related index outperformed the duration-equivalent Treasury index by 42 basis points in January. Sovereign bonds outperformed by 118 bps, Local Authorities by 67 bps, Foreign Agencies by 54 bps, Domestic Agencies by 8 bps and Surpranationals by 3 bps. USD-denominated Sovereign bonds continue to look expensive compared to Baa-rated U.S. Credit (Chart 5), yet they still managed to deliver almost identical excess returns during the past 12 months because of the U.S. dollar's large depreciation. Going forward, with the dollar's rapid decline unlikely to accelerate, we would avoid Sovereign bonds in favor of U.S. corporates. Valuation is more attractive elsewhere in the Government-Related index. Foreign Agency bonds now offer greater spreads than equivalent-duration U.S. corporate bonds, despite benefitting from higher credit quality (panel 4). Local Authority spreads also look attractive compared to recent history (bottom panel). We continue to recommend overweight allocations to both sectors. We remain underweight Domestic Agency and Supranational bonds. Though both sectors offer low risk and high credit quality, they also only offer 12 bps and 16 bps of option-adjusted spread, respectively. We much prefer Agency-backed MBS and CMBS which are also relatively low risk and offer option-adjusted spreads of 29 bps and 40 bps, respectively. Municipal Bonds: Underweight Chart 6Municipal Market Overview Municipal Market Overview Municipal Market Overview Municipal bonds outperformed the duration-equivalent Treasury index by 53 basis points in January (before adjusting for the tax advantage). The average AAA-rated Municipal / Treasury (M/T) yield ratio was flat on the month. Two market technicals spurred Muni outperformance in January. First, supply plunged after many advance refunding issues were pulled forward in anticipation of the U.S. tax bill (Chart 6). Second, the repeal of the state and local tax deduction led to increased demand for Munis, as evidenced by the recent jump in fund inflows (panel 3). In terms of credit quality, state and local government net borrowing as a percent of GDP likely fell to 0.9% in 2017 Q4 - assuming that corporate tax revenues are held constant. This is consistent with current low yield ratios (panel 4). Meanwhile, tax revenue growth should stay strong in the coming quarters due to recent increases in property prices and retail sales. While M/T yield ratios remain low compared to history, excessive valuations in investment grade corporate bonds mean that Munis are starting to look attractive by comparison. For example, for investors in the top marginal tax bracket, we calculate that the after-tax yield on a Aaa-rated municipal bond is 7 bps higher than the duration-equivalent yield offered by the investment grade corporate bond index, even though the corporate bond index offers an average credit rating of only A3/Baa1. While the bottom panel shows that this yield differential has been higher in the past, it is nevertheless an indication that we are approaching the end of the credit cycle. Stay underweight Munis for now, though an upgrade is likely when it comes time to exit our corporate bond overweights. Treasury Curve: Favor 5-Year Bullet Over 2/10 Barbell Chart 7Treasury Yield Curve Overview Treasury Yield Curve Overview Treasury Yield Curve Overview The Treasury curve bear steepened out to the 10-year maturity point in January, as bond markets started to price-in a rebound in inflation. The 2/10 slope steepened 7 basis points on the month and the 5/30 slope flattened 11 bps. The 2/10 slope steepened even further in the first five days of February and currently sits at 69 bps, up from its recent low of 50 bps. More near-term curve steepening is possible if long-maturity TIPS breakeven inflation rates continue to widen, especially since the Fed's median projected rate hike path for the next 12 months is already fully discounted (Chart 7). However, the yield curve is much more likely to be flatter by the end of the year than it is today. In large part because the upside in long-maturity yields will be limited once TIPS breakeven inflation rates reach our target fair value range of 2.4% to 2.5%. In terms of positioning, we continue to advocate a long position in the 5-year bullet versus a short position in a duration-matched 2/10 barbell. The 5-year continues to look very cheap on the curve (panel 3), or put differently, our model suggests that the 2/5/10 butterfly spread is currently priced for 29 bps of 2/10 curve flattening during the next six months (panel 4).4 This seems excessive for the time being. TIPS: Overweight Chart 8TIPS Market Overview TIPS Market Overview TIPS Market Overview TIPS outperformed the duration-equivalent nominal Treasury index by 75 basis points in January. The 10-year TIPS breakeven inflation rate increased 15 bps on the month. At 2.14% and 2.36%, respectively, the 10-year and 5-year/5-year forward TIPS breakeven inflation rates are still below our target range of 2.4% to 2.5%, but only modestly so. The big run-up in TIPS breakeven rates coincided with a jump in oil prices and, as we discussed in a recent report, this is no coincidence (Chart 8).5 The Fed has an asymmetric ability to influence inflation - it has an unlimited ability to tighten policy but its ability to ease policy is restricted by the zero-lower bound on interest rates. It is for this reason that when TIPS breakeven inflation rates become un-anchored to the downside, they also become much more sensitive to swings in commodity prices. In these environments the market sees inflation as increasingly determined by price pressures in the economy and not by the Fed's reaction function. The logical conclusion is that we should expect the tight correlation between oil prices and long-maturity TIPS breakeven rates to persist until breakevens reach our target fair value range of 2.4% to 2.5%. At that point, it is unlikely that further increases in commodity prices would filter through to long-maturity breakevens, because the market would anticipate a tightening response from the Fed. Stay overweight TIPS versus nominal Treasury securities for now. We will reduce exposure when our fair value target of 2.4% to 2.5% is achieved. ABS: Neutral Chart 9ABS Market Overview ABS Market Overview ABS Market Overview Asset-Backed Securities outperformed the duration-equivalent Treasury index by 4 basis points in January. The index option-adjusted spread (OAS) for Aaa-rated ABS tightened 2 bps on the month and now stands at 33 bps, only 6 bps above its all-time low (Chart 9). All in all, a 33 bps spread is still reasonably attractive for a sector that is Aaa rated with an average duration of 2. By way of comparison, the intermediate maturity Aaa Credit index offers an OAS of only 17 bps and has an average duration above 3. However, credit trends are clearly shifting against the Consumer ABS sector. The consumer credit delinquency rate has put in a bottom, albeit from a very healthy level, and the trend in the household debt service ratio suggests that delinquencies will continue to rise (panel 3). Further, the Federal Reserve's Senior Loan Officer Survey shows that lending standards on auto loans have tightened on net in each of the past 7 quarters, while credit card lending standards have tightened for 3 consecutive quarters. Even though lending standards on both auto loans and credit cards moved slightly closer to net easing territory in the fourth quarter of 2017, the reading from lending standards is still consistent with a rising delinquency rate (bottom panel). We retain a neutral allocation to consumer ABS due to still attractive spreads for a low-duration, high credit quality sector. However, if the uptrend in consumer delinquencies is sustained then our next move will probably be to reduce allocation to this sector. Non-Agency CMBS: Underweight Chart 10CMBS Market Overview CMBS Market Overview CMBS Market Overview Non-Agency Commercial Mortgage-Backed Securities outperformed the duration-equivalent Treasury index by 60 basis points in January. The index option-adjusted spread for non-agency Aaa-rated CMBS tightened 7 bps on the month and currently sits at 59 bps. The spread is now only 8 bps above the lowest level seen since the inception of the index in 2000 (Chart 10). Much like in the Consumer ABS sector, historically low CMBS spreads are observed at a time when lending standards are tightening in the commercial real estate (CRE) sector. The Federal Reserve's most recent Senior Loan Officer Survey shows that lending standards for nonfarm nonresidential CRE loans have tightened for 10 consecutive quarters, though they have been tightening less aggressively of late (panel 3). Agency CMBS: Overweight Agency CMBS outperformed the duration-equivalent Treasury index by 14 basis points in January. The index option-adjusted spread narrowed 1 bp on the month and currently sits at 40 bps. With an average spread of 40 bps and an average duration of around 5, this sector is not quite as attractive as Consumer ABS on a spread per unit of duration basis. However, it still offers greater expected compensation than a position in Conventional 30-year residential MBS which has an option-adjusted spread of 29 bps and a similar duration. Treasury Valuation Chart 11Treasury Fair Value Models Treasury Fair Value Models Treasury Fair Value Models The current reading from our 2-factor Treasury model (based on Global PMI and dollar sentiment) pegs fair value for the 10-year Treasury yield at 3.01% (Chart 11). Our 3-factor version of the model (not shown), which also incorporates the Global Economic Policy Uncertainty Index, places fair value at 3.06%. The Global PMI actually ticked down in January, but only slightly from 54.5 to 54.4. This small decline was more than offset in our model by the large drop in dollar sentiment, which just moved into "net bearish" territory (bottom panel). Of the four major economic blocs, PMIs increased in the U.S. and Japan, ticked down from an extremely high level in the Eurozone and held steady in China. For further details on our Treasury models please refer to U.S. Bond Strategy Weekly Report, "The Message From Our Treasury Models", dated October 11, 2016, available at usbs.bcaresearch.com. At the time of publication the 10-year Treasury yield was 2.84%. Ryan Swift, Vice President U.S. Bond Strategy rswift@bcaresearch.com Alex Wang, Research Analyst alexw@bcaresearch.com Jeremie Peloso, Research Assistant jeremiep@bcaresearch.com 1 Please see U.S. Bond Strategy Weekly Report, "The Most Important Chart In Finance", dated January 30, 2018, available at usbs.bcaresearch.com 2 Please see U.S. Bond Strategy Weekly Report, "The Most Important Chart In Finance", dated January 30, 2018, available at usbs.bcaresearch.com 3 Please see U.S. Bond Strategy Weekly Report, "The Most Important Chart In Finance", dated January 30, 2018, available at usbs.bcaresearch.com 4 For further details on our model please see U.S. Bond Strategy Special Report, "Bullets, Barbells And Butterflies", dated July 25, 2017, available at usbs.bcaresearch.com 5 Please see U.S. Bond Strategy Weekly Report, "It's Still All About Inflation", dated January 16, 2018, available at usbs.bcaresearch.com Fixed Income Sector Performance Recommended Portfolio Specification Corporate Sector Relative Valuation And Recommended Allocation Total Return Comparison: 7-Year Bullet Versus 2-20 Barbell (6-Month Investment Horizon)

Overweight The U.S. defense complex has seen a solid recovery in orders over the last three years (second panel), a notable feat because of the absence of a major conflict driving domestic orders. In fact in the past decade, domestic real defense spending has contracted more than it has expanded and even when it is growing, it has not been at a pace faster than mid-single digits (third panel). That may soon change. If early reports are correct, the Trump administration will raise its defense spending target to $716 billion for the 2019 budget, an increase of 13% from this past year's level. Such largesse should sustain the valuation rerating defense stocks have been enjoying. Stay overweight. The ticker symbols for the stocks in the BCA Defense index are: LMT, GD, RTN, NOC, LLL Defense Stocks Are Rallying Again Defense Stocks Are Rallying Again .

The GAA DM Equity Country Allocation model is updated as of January 31, 2018. The model has made large shifts in country allocations. The U.S. is upgraded to neutral from previously the largest underweight, driven largely by technical conditions. It seems dramatic, but as shown in Chart 2, the model did have similar large shifts in the past as well. Canada also has received a large increase to overweight driven by extremely attractive valuation. To fund these upgrades, the previously largest overweight in Italy is cut in half (mainly driven by liquidity and valuation) and Australia is back to underweight (trading places with Canada). As a result, the model now is overweight the Netherlands, Italy, Germany, Canada and Spain, neutral on the U.S. and underweight Japan, the U.K., France, Australia and Sweden as shown in Table 1. As shown in Table 2 and Chart 1, Chart 2 and Chart 3, the overall model outperformed its benchmark by 99 bps in January, largely driven by the Level 2 model which outperformed by 207 bps, thanks to the underweights in the U.K., Japan and Canada vs. the overweights in Italy, the Netherlands and Germany. Since going live in January 2016, the overall model has outperformed the benchmark by 190 bps, largely from the allocation among the 11 non-U.S. countries, which has outperformed its benchmark by 570 bps. The Level 1 model has performed in line with the MSCI world benchmark. Chart 1GAA DM Model Vs. MSCI World GAA DM Model Vs. MSCI World GAA DM Model Vs. MSCI World Chart 2GAA U.S. Vs. Non U.S. Model (Level1) GAA U.S. Vs. Non U.S. Model (Level1) GAA U.S. Vs. Non U.S. Model (Level1) Chart 3GAA Non U.S. Model (Level 2) GAA Non U.S. Model (Level 2) GAA Non U.S. Model (Level 2) Table 1Model Allocation Vs. Benchmark Weights GAA Quant Model Updates GAA Quant Model Updates Table 2Performance (Total Returns In USD) GAA Quant Model Updates GAA Quant Model Updates Please see also the website http://gaa.bcaresearch.com/trades/allocation_performance. For more details on the models, please see the January 29, 2016 Special Report, "Global Equity Allocation: Introducing the Developed Markets Country Allocation Model." http://gaa.bcaresearch.com/articles/view_report/18850. Please note that the overall country and sector recommendations published in our Monthly Portfolio Update and Quarterly Portfolio Outlook use the results of these quantitative models as one input, but do not stick slavishly to them. We believe that models are a useful check, but structural changes and unquantifiable factors need to be considered too in making overall recommendations. GAA Equity Sector Selection Model The GAA Equity Sector Selection Model (Chart 4) is updated as of January 31, 2018. The model continues to be bullish on global growth as seen by a 10% aggregate overweight in the cyclical sectors. The model continues to hold equal underweights in consumer staples, health care, telecom and utilities stocks. Looking forward, we believe improving global growth dynamics, and rising equity markets will help us maintain an aggregate cyclical pro-growth bias. For more details on the model, please see the Special Report "Introducing The GAA Equity Sector Selection Model," July 27, 2016 available at https://gaa.bcaresearch.com. Chart 4Overall Model Performance Overall Model Performance Overall Model Performance Table 3Allocations GAA Quant Model Updates GAA Quant Model Updates Table 4Performance Since Going Live GAA Quant Model Updates GAA Quant Model Updates Xiaoli Tang, Associate Vice President xiaoli@bcaresearch.com Aditya Kurian, Research Analyst adityak@bcaresearch.com

Highlights The German 10-year bund yield rising to 1%, or the U.S. 10-year T-bond yield rising to 3% would be a trigger to downgrade equities and upgrade bonds... ...especially as the blue sky expectations for global growth in H1 2018 will turn out to be overly-optimistic. On a 6-9 month horizon, upgrade Airlines to overweight. Downgrade Banks to underweight. Upgrade Germany (DAX) to neutral. Downgrade Italy (MIB) and Spain (IBEX) to underweight. Feature Where has the equity market cycle gone? Since 2012, the stock market's 6-month returns have generated an unprecedented consistency, with only a brief breakdown - at the end of 2015 - into negative territory (Chart of the Wesk and Chart I-2). Chart of the WeekSince 2012, The Equity Market ##br##Cycle Has Disappeared Since 2012, The Equity Market Cycle Has Disappeared Since 2012, The Equity Market Cycle Has Disappeared Chart I-2Much Less Cyclicality In Equities ##br##Than In Commodities Much Less Cyclicality In Equities Than In Commodities Much Less Cyclicality In Equities Than In Commodities The disappearance of the equity market cycle brings to mind the concept of the "Great Moderation", a term coined in 2002 to describe the big drop in business cycle volatility during the 1990s. In 2004, Ben Bernanke suggested that "improvements in monetary policy, though certainly not the only factor, probably were an important source of the Great Moderation." Today's Great Moderation 2.0 refers to the equity market cycle - or rather, its disappearance. And in finding a reason for the Great Moderation 2.0, Bernanke's attribution to monetary policy might be right on the money. Stick With TINA, Or Flirt With TIA? For many years, ultra-accommodative monetary policy has provided a consistent and substantial uplift to world stock market valuations. Since 2012, our preferred measure of equity market valuation - world stock market capitalisation to GDP - has almost doubled. This inexorable and relatively trouble-free rise has even spawned its own acronym: TINA - There Is No Alternative (to owning equities.) However, the uplift to stock market valuations has happened in a less obvious way than you might realise. Based on the excellent predictive power of stock market capitalisation to GDP, the prospective 10-year annualised return from world equities has collapsed from 9% in 2012 to 1.5% now (Chart I-3). Over the same period, the global 10-year bond yield has compressed from 3% to 1.5%. Hence, the collapse in prospective equity returns is not due to the decline in bond yields per se. It has happened mostly because the excess return offered by equities over bonds - the so-called 'equity risk premium' has compressed from 6% to zero (Chart I-4). Chart I-3World Equity Market Cap To GDP Implies##br## A Feeble Prospective 10-Year Return World Equity Market Cap To GDP Implies A Feeble Prospective 10-Year Return World Equity Market Cap To GDP Implies A Feeble Prospective 10-Year Return Chart I-4Prospective Equity Returns ##br##Have Become 'Bond Like' Prospective Equity Returns, Have Become "Bond Like" Prospective Equity Returns, Have Become "Bond Like" Ultra-accommodative monetary policy has caused the disappearance of the equity risk premium. The simple reason is that at low bond yields, the risk of owning bonds becomes similar to the risk of owning equities. Chart I-5Below A 2% Yield, 10-Year Bonds Have ##br##More Negative Skew Than Equities Beware The Great Moderation 2.0 Beware The Great Moderation 2.0 When bond yields approach their lower bound, bond prices have little upside but they have a lot of downside. This ratio of an investment's potential losses relative to its potential gains is the risk that most frightens investors,1 and is known as negative skew. At yields below 2%, bond returns become as negatively skewed as equity returns, or even more negatively skewed than equities (Chart I-5). As the risk of bonds increases to become 'equity-like', the prospective return from equities must compress to become 'bond-like'. Which is to say, equity valuations become substantially richer. All well and good - so long as the global 10-year bond yield stays low. Above a 2% yield, the negative skew on bond returns disappears, and equities once again require an excess prospective return over bonds. More colloquially, investors would dump TINA and start flirting with TIA (There Is an Alternative). In essence, a big threat to the Great Moderation 2.0 comes the global 10-year bond yield rising to 2% - broadly equivalent to the German 10-year bund yield rising to 1%, or the U.S. 10-year T-bond yield rising to 3%. Any moves towards these thresholds would be a trigger to downgrade equities and upgrade bonds - especially as we now explain why the blue sky expectations for global growth in H1 2018 will turn out to be overly-optimistic. The Equity Sector Cycle Is Alive And Well For the stock market in aggregate, the cycle has been moribund. But for equity sector relative performance, the cycle is very much alive and well. In The Cobweb Theory And Market Cycles 2 we showed and explained the existence of mini-cycles in economic and financial variables. To summarise, a lag between the demand for credit and its supply necessarily creates mini-cycles in both the price of credit (the bond yield) and the quantity of credit (the global credit impulse). Thereby it also creates mini-cycles in GDP growth. The useful point is that these cycles are very regular with half-cycles averaging 6-8 months. Which makes their turning points and phases predictable. Given that the global credit impulse cycle has been in a mini-upswing phase since last May, it is highly likely to turn into a mini-downswing phase through the first half of 2018. The latest data point, showing a tick down, seems to corroborate such a turning point. From an equity sector perspective, Banks versus Healthcare has closely tracked the phases of the credit impulse mini-cycle (Chart I-6). In all five of the last five mini-downswings, Banks have underperformed Healthcare, and we would expect no difference in the next mini-downswing. Hence, on a 6-9 month horizon, downgrade Banks to underweight. Unsurprisingly, exactly the same pattern applies to Basic Materials (and Energy) versus Healthcare (Chart I-7). Hence, on a 6-9 month horizon, stay underweight Basic Materials and Energy versus Healthcare. Also unsurprisingly, the performance of European Airlines is a mirror-image of the oil price cycle, given that aviation fuel comprises the sector's main variable cost (Chart I-8). As an aside, this also somewhat insulates the European Airlines against a strengthening euro, given that this variable cost is priced in dollars. Hence, on a 6-9 month horizon, upgrade European Airlines to overweight. Chart I-6Banks Vs. Healthcare Tracks The ##br##Credit Impulse Mini-Cycle Banks Vs. Healthcare Tracks The Credit Impulse Mini-Cycle Banks Vs. Healthcare Tracks The Credit Impulse Mini-Cycle Chart I-7Materials Vs. Healthcare Tracks The##br## Credit Impulse Mini-Cycle Materials Vs. Healthcare Tracks The Credit Impulse Mini-Cycle Materials Vs. Healthcare Tracks The Credit Impulse Mini-Cycle Chart I-8European Airlines Relative Performance Is A##br## Mirror-Image of The Oil Price Cycle European Airlines Relative Performance Is A Mirror-Image of The Oil Price Cycle European Airlines Relative Performance Is A Mirror-Image of The Oil Price Cycle Country Allocation Just Drops Out Of Sector Allocation Our core philosophy of investment reductionism teaches us that for most stock markets, the sector (and dominant company) skews swamp any effect that comes from the domestic economy. For example, the defining skew for Italy's MIB and Spain's IBEX is their large overweighting to banks. So unsurprisingly, MIB and IBEX relative performance reduces to: will banks outperform the market? (Chart I-9 and Chart I-10). Chart I-9Italy = Long Banks Italy = Long Banks Italy = Long Banks Chart I-10Spain = Long Banks Spain = Long Banks Spain = Long Banks Therefore, the key consideration for European equity country allocation is always: how to allocate to the vital few equity sectors that feature most often in the skews: Banks, Healthcare, Energy and Materials. To reiterate, our 6-9 month recommendation is to underweight Banks, Materials And Energy versus Healthcare, and to overweight Airlines versus the market. Then to arrive at a country allocation, combine the cyclical view on the vital few sectors with the country sector skews shown in Box I-1. Even if you disagree with our sector views, the sector-based approach is the right way to pick European equity markets. If you agree with our sector views, the result is the following updated European equity market allocation: Box I-1: The Vital Few Sector Skews That Drive Country Relative Performance For major equity indexes in the euro area, the dominant sector skews that drive relative performance are as follows: Germany (DAX) is overweight Chemicals, underweight Banks. France (CAC) is underweight Banks and Basic Materials. Italy (MIB) is overweight Banks. Spain (IBEX) is overweight Banks. Netherlands (AEX) is overweight Technology, underweight Banks. Ireland (ISEQ) is overweight Airlines (Ryanair) which is, in effect, underweight Energy. And for major equity indexes outside the euro area: The U.K. (FTSE100) is effectively underweight the pound. Switzerland (SMI) is overweight Healthcare, underweight Energy. Sweden (OMX) is overweight Industrials. Denmark (OMX20) is overweight Healthcare and Industrials. Norway (OBX) is overweight Energy. The U.S. (S&P500) is overweight Technology, underweight Banks. Overweight: France, Ireland, U.K., Switzerland and Denmark. Neutral: Germany, Netherlands. Underweight: Italy, Spain, Sweden and Norway. In terms of change, it means upgrading Germany (DAX) to neutral and downgrading Italy (MIB) and Spain (IBEX) to underweight. Dhaval Joshi, Senior Vice President Chief European Investment Strategist dhaval@bcaresearch.com 1 Please see the European Investment Strategy Weekly Report "Are Bonds A Greater Risk Than Equities", January 28, 2018 available at eis.bcaresearch.com. 2 Please see the European Investment Strategy Weekly Report "The Cobweb Theory And Market Cycles", January 11, 2018 available at eis.bcaresearch.com. Fractal Trading Model* There is a lot of optimism already priced into the South African rand, making it vulnerable to a countertrend reversal. Therefore, this week's recommended trade is to go long USD/ZAR with a profit-target of 6% and a symmetrical stop-loss. In other trades, short S&P500/long Eurostoxx50 hit its stop-loss, while short Japanese energy and short palladium moved comfortably into profit. For any investment, excessive trend following and groupthink can reach a natural point of instability, at which point the established trend is highly likely to break down with or without an external catalyst. An early warning sign is the investment's fractal dimension approaching its natural lower bound. Encouragingly, this trigger has consistently identified countertrend moves of various magnitudes across all asset classes. Chart I-11 USD/ZAR USD/ZAR The post-June 9, 2016 fractal trading model rules are: When the fractal dimension approaches the lower limit after an investment has been in an established trend it is a potential trigger for a liquidity-triggered trend reversal. Therefore, open a countertrend position. The profit target is a one-third reversal of the preceding 13-week move. Apply a symmetrical stop-loss. Close the position at the profit target or stop-loss. Otherwise close the position after 13 weeks. Use the position size multiple to control risk. The position size will be smaller for more risky positions. * For more details please see the European Investment Strategy Special Report "Fractals, Liquidity & A Trading Model," dated December 11, 2014, available at eis.bcaresearch.com Fractal Trading Model Recommendations Equities Bond & Interest Rates Currency & Other Positions Closed Fractal Trades Trades Closed Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Interest Rate Chart II-5Indicators To Watch ##br##- Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch ##br##- Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch ##br##- Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-8Indicators To Watch ##br##- Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations

Neutral Prior to our midsummer upgrade to neutral, our key concern for the S&P chemicals index was that perennial overcapacity would put a ceiling on margin improvement. Since then surging global demand growth has driven producer prices sky high (second panel), in line with our expectations. More surprising is the newly-found industry discipline which has thus far refrained from splurging on new capacity (third panel), likely assisted by a wave of consolidation in the space. The upshot is that our productivity proxy has perked up to its highest level in nearly a decade, as have sell-side earnings expectations. While it remains too early for us to turn bullish, the outlook has certainly brightened for chemicals; maintain a neutral stance. The ticker symbols for the stocks in this index are: BLBG: S5CHEM - APD, ARG, CF, DOW, EMN, ECL, DD, FMC, IFF, LYB, MON, MOS, PPG, PX, SHW. The Chemicals Bear Market Has Ended The Chemicals Bear Market Has Ended

Neutral In yesterday’s Weekly Report, we outlined that the most cyclical parts of the S&P industrials index with high foreign sales content would benefit disproportionately from our stable-to-mildly sanguine EM/China view. While the broad machinery index fits the bill, the industrial machinery sub index less so, and we recommend monetizing gains of 4% since inception and moving to the sidelines while redeploying profits into the more cyclical S&P construction machinery & heavy truck index. One key determinant of the relative move of these indexes is the U.S. dollar. The greenback troughed in 2011 and since then the more “defensive”, less globally-exposed S&P industrials machinery index left their brethren in the dust (top panel). Now that the U.S. dollar has peaked, the catch up phase in the S&P construction machinery & heavy truck index that is already underway will likely gain momentum (bottom panel). Bottom Line: Book profits of 4% in the S&P industrial machinery index and downgrade to a benchmark allocation while staying overweight construction machinery; please see yesterday’s Weekly Report for more details. The ticker symbols for the stocks in this index are: BLBG: S5INDM - ITW, IR, SWK, PH, FTV, DOV, PNR, XYL, SNA, FLS. Take Profits In Industrial Machinery Take Profits In Industrial Machinery

Highlights Portfolio Strategy A stable China, a depreciating U.S. dollar, rising commodity prices and sustained synchronized global growth signal that the industrials complex, especially the most cyclical part, remains on a solid footing. Deteriorating profit prospects warn that investors should refrain from paying a premium valuation for industrial machinery; take profits and move to the sidelines. Recent Changes S&P Industrial Machinery - Book profits of 4% and downgrade to neutral today. S&P Construction Machinery & Heavy Truck - Stop triggered last week, remove from the high-conviction list for a 10% gain. Small Caps / Large Caps - Downgrade alert in a recent Insight. Table 1 Corporate Pricing Power Update Corporate Pricing Power Update Feature The S&P 500 smashed through the 2,800 mark last week, as corporate profits continued to deliver, the U.S. dollar took a dive and global economic data releases held their own. Stars could not be more aligned for a euphoric blow off phase, with equity bourses the world over already registering annual-like returns in but a few short weeks. While stocks have more room to run, especially versus bonds, on a cyclical time frame, tactically the likelihood of a short-term healthy pullback is increasing. Last week we identified five indicators we are closely monitoring that are signaling an overstretched market.1 This week we update our Complacency-Anxiety Indicator that also catapulted to all-time highs and breached the one standard deviation above the historical mean mark (Chart 1). This confirms that a Q1 setback remains likely, and our strategy since December 18 has been to monetize gains in tactical trades and institute stops to the high flyers in our high-conviction call list. Were a 5-10% correction to materialize, we would "buy the dip" as we do not foresee a recession in the coming 9-12 months. While consumer price inflation is nowhere to be found, corporate selling prices are climbing at a brisk pace. The U.S. dollar debasement and related commodity reflex rebound, especially in oil prices, are the culprits, and the latter will likely assist even the CPI basket and morph into an inflationary impulse as we posited in late-November (please see the bottom two panels of Chart 1B). Already, inflation expectations are headed higher. Chart 2 updates our corporate sector pricing power proxy and our diffusion index. It also updates the business sector's overall wage inflation and associated diffusion index from the latest BLS employment report. The middle panel of Chart 2 shows the Atlanta Fed Wage Growth Tracker and that measure of wage inflation has converged down to the AHE reading, suffering a 100bps drop in the past year. Chart 1Complacency Reigns Complacency Reigns Complacency Reigns Chart 2Margin Expansion Phase Is Intact Margin Expansion Phase Is Intact Margin Expansion Phase Is Intact Corporate pricing power is upbeat at a time when wages are decelerating. Taken together, our margin proxy indicator suggests that the ongoing profit margin expansion phase has more upside (bottom panel, Chart 2). Table 2 shows our updated industry group pricing power gauges, which we calculate from the relevant CPI, PPI, PCE and commodity growth rates for each of the 60 industry groups we track. Table 2 also highlights shorter-term pricing power trends and each industry's spread to overall inflation. Table 2Industry Group Pricing Power Corporate Pricing Power Update Corporate Pricing Power Update 78% of the industries we cover are lifting selling prices, and 45% are doing so at a faster clip than overall inflation. Importantly, inflation rates have increased since our late-September update. The outright deflating sectors dropped by two to 13 since our last update. Encouragingly, only 7 industries are experiencing a downtrend in selling price inflation, or 5 fewer than our most recent report. Impressively, deep cyclicals/commodity-related industries dominate the top ranks, occupying 8 out of the top 10 slots (top panel, Chart 3). A softening greenback and rising global end demand explain the commodity complex's sustained ability to increase prices. In contrast, tech, telecom and consumer discretionary sectors populate the bottom ranks of Table 2. Netting it out, accelerating corporate sector pricing power will continue to bolster top line growth in 2018. Tack on high operating leverage kicking into higher gear at this stage of the cycle and still muted wage inflation and profit margins and EPS growth will remain upbeat. With regard to cyclicals versus defensives, diverging pricing power (Chart 3) and wage growth trends (Chart 4) suggest that cyclicals continue to have the upper hand compared with defensives (Chart 5). Chart 3Deep Cyclicals... Deep Cyclicals... Deep Cyclicals... Chart 4...Have The Upper Hand... ...Have The Upper Hand... ...Have The Upper Hand... Chart 5...Vs. Defensives ...Vs. Defensives ...Vs. Defensives This week we update our view on a deep cyclical sector and modestly tweak our intra-sector positioning. Industrials And China We lifted the S&P industrials sector to an above benchmark allocation in early October via boosting the S&P construction machinery & heavy truck sub index to overweight.2 Synchronized global growth, a capex upcycle, firming capital goods final demand, and the U.S. dollar's fall coupled with the commodity price rebound all pointed to a bright outlook for U.S. capital goods producers. Currently, all these forces remain in play and continue to bolster industrials stocks' profit prospects. However, the emerging market (EM)/Chinese economic backdrop deserves closer scrutiny. Why? Because the most cyclical parts of the industrials complex are levered to the EM in general and China in particular. These high operating leverage businesses also drive relative profit and stock performance, signaling that China's economic growth might or ails determine the overall fortunes of U.S. capital goods producers. While Chinese economic data are currently a mixed bag and we take them with a big grain of salt, global high-frequency financial market data are emitting an unambiguously positive signal. First, BCA's FX strategist, Mathieu Savary, brought to our attention that the extremely economic-sensitive Canadian TSX Venture Exchange Index is in a V-shaped recovery.3 Highly speculative basic resources issues dominate this Index and help explain the tight positive correlation with Chinese output (top panel, Chart 6). Second, the ultimate economic-sensitive indicator, Dr. Copper, is also in a violent upswing, heralding that China will be, at least, stable in 2018 (middle panel, Chart 6). Third, high-beta Australian materials stocks have been in an upward trajectory since the early 2016 trough both versus the MSCI All-Country World Index and the broad Australian market, sniffing out improving Chinese-related commodity demand (bottom panel, Chart 6). Similarly, upbeat non-Chinese economic data suggest that China's economic prospects are far from faltering. Australia's close economic ties with China signal that taking a pulse of the Australian economic juggernaut reveals the state of China's economic affairs. Down Under employment growth has been brisk of late, with annual job creation running at a 3.3% clip, a rate last hit in the mid-2000s when China's economy was roaring and the commodity super-cycle was in full swing (second panel, Chart 7). Australian CEO confidence as well as consumer confidence are pushing decade highs, and the manufacturing PMI survey recently shot to a 16 year high (third panel, Chart 7). Chart 6China Is##BR##Alright China Is Alright China Is Alright Chart 7Australian Indicators Confirm:##BR## China Is Stable Australian Indicators Confirm: China Is Stable Australian Indicators Confirm: China Is Stable All of this suggests that China will likely remain stable in 2018, barring a policy mistake a la the August 11, 2015 currency devaluation. The upshot is that industrials EPS and equities have more room to run. On that front, both our Cyclical Macro Indicator and our profit growth model corroborate that the path of least resistance for relative share prices is higher (Chart 8). U.S. dollar debasing is synonymous with capital goods producers' top line growth acceleration, as a large part of total revenues are sourced from abroad. The near 20 percentage point fall in the trade-weighted U.S. dollar since 2015 suggests that more global market share gains are in store for U.S. industrials (Chart 9). Global growth is also joined at the hip with the greenback's depreciation. Synchronized global growth along with our derivative coordinated global capex growth 2018 theme, will likely serve as catalysts for a sustained breakout in relative share prices (Chart 10). Chart 8EPS Model And CMI Flash Green EPS Model And CMI Flash Green EPS Model And CMI Flash Green Chart 9Industrials Love A Cheap Greenback Industrials Love A Cheap Greenback Industrials Love A Cheap Greenback Chart 10Levered To Global Growth Levered To Global Growth Levered To Global Growth Adding it up, a stable China is music to the ears of industrials executives. Tack on a depreciating U.S. dollar, rising commodity prices and sustained synchronized global growth and the most cyclical parts of the industrials complex will continue to lead the pack. Bottom Line: Stay overweight the S&P industrials index, but selectivity is warranted. Take Profits In Industrial Machinery We outlined above that the most cyclical parts of the S&P industrials index with high foreign sales content would benefit disproportionately from our stable-to-mildly sanguine EM/China view. While the broad machinery index fits the bill, the industrial machinery sub index less so, and we recommend monetizing gains of 4% since inception and moving to the sidelines. Chart 11 shows the relative performance of the two key drivers of the S&P machinery index: industrial machinery and construction machinery & heavy truck sub-indexes. While these indexes moved hand-in-hand since the mid-1990s, early this decade this tight positive correlation fell apart. One key determinant of the relative move of these indexes is the U.S. dollar. The greenback troughed in 2011 and since then the more "defensive", less globally-exposed S&P industrials machinery index left their brethren in the dust (bottom panel, Chart 11). Now that the U.S. dollar has peaked, the catch up phase in the S&P construction machinery & heavy truck index that is already underway will likely gain momentum (top panel, Chart 11). Beyond the depreciating currency, at the margin, softening S&P industrial machinery operating metrics argue for pruning exposure in this index. Both the Empire and Philly Fed new orders surveys have petered out, suggesting that industry new order growth will likely continue to lose steam (middle panel, Chart 12). In fact, a weak industrial machinery new orders-to-inventories ratio is also warning that sell-side analysts' relative profits forecasts are too optimistic (bottom panel, Chart 12). Chart 11Catch Up Phase Catch Up Phase Catch Up Phase Chart 12Waning End-Demand Waning End-Demand Waning End-Demand Drilling deeper into industry operating metrics is revealing. While shipments have held their own and moved mostly sideways similar to new orders, inventory accumulation is worrying. Industry inventories have risen by over 30% during the past three years (Chart 13). Simultaneously, industrial machinery backlogs have drifted steadily lower. Given the supply build up, any hiccup in demand, even a minor one, could prove very deflationary and heavily weigh on industry profitability. With regard to valuations, Chart 14 shows that both on a relative trailing price-to-sales and relative forward price-to-earnings ratio basis, the index is trading one standard deviation above the historical mean. The moderating industry demand backdrop suggests that relative valuations are expensive. Chart 13Inventory Liquidation Risk Inventory Liquidation Risk Inventory Liquidation Risk Chart 14Why Pay A Premium? Why Pay A Premium? Why Pay A Premium? Adding it all up, deteriorating profit prospects warn that investors should refrain from paying a premium valuation for the S&P industrial machinery index. Bottom Line: Book profits of 4% in the S&P industrial machinery index and downgrade to a benchmark allocation. We also recommend redeploying profits from our downgrade in the S&P industrial machinery index to their more cyclical machinery siblings the S&P construction machinery & heavy truck index, thus sustaining the overall overweight exposure in the broad S&P industrials sector. Housekeeping Last week we instituted a risk management tool for our 2018 high-conviction list: setting a stop once a call has cleared the 10% return mark.4 This past week, the S&P construction machinery & heavy truck index hit the trailing stop at the 10% mark, and thus we are booking gains and removing this index from the high-conviction list. While our confidence is not as high as in late-November given the parabolic move in this index and rising chance of a tactical overall equity market pullback, from a cyclical perspective we continue to recommend a core overweight in this industrials sector powerhouse. Anastasios Avgeriou, Vice President U.S. Equity Strategy anastasios@bcaresearch.com 1 Please see BCA U.S. Equity Strategy Weekly Report, "Too Good To Be True?" dated January 22, 2018, available at uses.bcaresearch.com. 2 Please see BCA U.S. Equity Strategy Weekly Report, "Earnings Take Center Stage," dated October 2, 2017, available at uses.bcaresearch.com. 3 Please see BCA Foreign Exchange Strategy Weekly Report, "Health Care Or Not, Risks Remain," dated March 24, 2017, available at fes.bcaresearch.com. 4 Please see BCA U.S. Equity Strategy Weekly Report, "Too Good To Be True?" dated January 22, 2018, available at uses.bcaresearch.com. Current Recommendations Current Trades Size And Style Views Favor value over growth. Stay neutral small over large caps (downgrade alert).

Dear Client, In addition to this Special Report written by my colleagues Mark McClellan and Brian Piccioni, we are sending you an abbreviated weekly report. Best regards, Peter Berezin, Chief Global Strategist Global Investment Strategy Highlights Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. Technological advance in the past has not prevented improving living standards or led to ever rising joblessness over the decades, but pessimists argue that recent advances are different. The issue is important for financial markets. If structural factors such as automation are holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. We see no compelling evidence that the displacement effect of emerging technologies is any stronger than in the past. Robot usage has had a modest positive impact on overall productivity. Despite this contribution, overall productivity growth has been dismal over the past decade. If automation is increasing 'exponentially' and displacing workers on a broad scale as some claim, one would expect to see accelerating productivity growth, robust capital spending and more violent shifts in occupational shares. Exactly the opposite has occurred. Periods of strong growth in automation have historically been associated with robust, not lackluster, wage gains, contrary to the consensus view. The Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. This and other evidence suggest that it is difficult to make the case that robots will make it tougher for central banks to reach their inflation goals than did previous technological breakthroughs. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. Feature Recent breakthroughs in technology are awe-inspiring and unsettling. These advances are viewed with great trepidation by many because of the potential to replace humans in the production process. Hype over robots is particularly shrill. Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. In the first in our series of Special Reports focusing on the structural factors that might be preventing central banks from reaching their inflation targets, we demonstrated that the impact of Amazon is overstated in the press. We estimated that E-commerce is depressing inflation in the U.S. by a mere 0.1 to 0.2 percentage points. This Special Report tackles the impact of automation. We are optimistic that robot technology and artificial intelligence will significantly boost future productivity, and thus reduce costs. But, is there any evidence at the macro level that robot usage has been more deflationary than technological breakthroughs in the past and is, thus, a major driver of the low inflation rates we observe today across the major countries? The question matters, especially for the outlook for central bank policy and the bond market. If structural factors are indeed holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. However, if low inflation simply reflects long lags between wages and the tightening labor market, then inflation may suddenly lurch to life as it has at the end of past cycles. The bond market is not priced for that scenario. Are Robots Different? A Special Report from BCA's Technology Sector Strategy service suggested that the "robot revolution" could be as transformative as previous General Purpose Technologies (GPT), including the steam engine, electricity and the microchip.1 GPTs are technologies that radically alter the economy's production process and make a major contribution to living standards over time. The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks," and this encompasses a broad range of machines: From the Jacquard Loom, which was invented over 200 years ago, on to Numerically Controlled (NC) mills and lathes, pick and place machines used in the manufacture of electronics, Autonomous Vehicles (AVs), and even homicidal robots from the future such as the Terminator. Our Technology Sector report made the case that there is nothing particularly sinister about robots. They are just another chapter in a long history of automation. Nor is the displacement of workers unprecedented. The industrial revolution was about replacing human craft labor with capital (machines), which did high-volume work with better quality and productivity. This freed humans for work which had not yet been automated, along with designing, producing and maintaining the machinery. Agriculture offers a good example. This sector involved over 50% of the U.S. labor force until the late 1800s. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," contributed to a massive rise in output-per-man hour. The number of hours worked to produce a bushel of wheat fell by almost 98% from the mid-1800s to 1955. This put a lot of farm hands out of work, but these laborers were absorbed over time in other growing areas of the economy. It is the same story for all other historical technological breakthroughs. Change is stressful for those directly affected, but rising productivity ultimately lifts average living standards. Robots will be no different. As we discuss below, however, the increasing use of robots and AI may have a deeper and longer-lasting impact on inequality. Strong Tailwinds Chart 1Robots Are Getting Cheaper Robots Are Getting Cheaper Robots Are Getting Cheaper Factory robots have improved immensely due to cheaper and more capable control and vision systems. As these systems evolve, the abilities of robots to move around their environment while avoiding obstacles will improve, as will their ability to perform increasingly complex tasks. Most importantly, robots are already able to do more than just routine tasks, thus enabling them to replace or aid humans in higher-skilled processes. Robot prices are also falling fast, especially after quality-adjusting the data (Chart 1). Units are becoming easier to install, program and operate. These trends will help to reduce the barriers-to-entry for the large, untapped, market of small and medium sized enterprises. Robots also offer the ability to do low-volume "customized" production and still keep unit costs low. In the future, self-learning robots will be able to optimize their own performance by analyzing the production of other robots around the world. Robot usage is growing quickly according to data collected by the International Federation of Robotics (IFR) that covers 23 countries. Industrial robot sales worldwide increased to almost 300,000 units in 2016, up 16% from the year before (Chart 2). The stock of industrial robots globally has grown at an annual average pace of 10% since 2010, reaching slightly more than 1.8 million units in 2016.2 Robot usage is far from evenly distributed across industries. The automotive industry is the major consumer of industrial robots, holding 45% of the total stock in 2016 (Chart 3). The computer & electronics industry is a distant second at 17%. Metals, chemicals and electrical/electronic appliances comprise the bulk of the remaining stock. Chart 2Global Robot Usage Global Robot Usage Global Robot Usage Chart 3Global Robot Usage By Industry (2016) The Impact Of Robots On Inflation The Impact Of Robots On Inflation As far as countries go, Japan has traditionally been the largest market for robots in the world. However, sales have been in a long-term downtrend and the stock of robots has recently been surpassed by China, which has ramped up robot purchases in recent years (Chart 4). Robot density, which is the stock of robots per 10 thousand employed in manufacturing, makes it easier to compare robot usage across countries (Chart 5, panel 2). By this measure, China is not a heavy user of robots compared to other countries. South Korea stands at the top, well above the second-place finishers (Germany and Japan). Large automobile sectors in these three countries explain their high relative robot densities. Chart 4Stock Of Robots By Country (I) Stock Of Robots By Country (I) Stock Of Robots By Country (I) Chart 5Stock Of Robots By Country (II) (2016) The Impact Of Robots On Inflation The Impact Of Robots On Inflation While the growth rate of robot usage is impressive, it is from a very low base (outside of the automotive industry). The average number of robots per 10,000 employees is only 74 for the 23 countries in the IFR database. Robot use is tiny compared to total man hours worked. In the U.S., spending on robots is only about 5% of total business spending on equipment and software (Chart 6). To put this into perspective, U.S. spending on information, communication and technology (ICT) equipment represented 35-40% of total capital equipment spending during the tech boom in the 1990s and early 2000s.3 Chart 6U.S. Investment In Robots U.S. Investment In Robots U.S. Investment In Robots The bottom line is that there is a lot of hype in the press, but robots are not yet widely used across countries or industries. It will be many years before business spending on robots approaches the scale of the 1990s/2000s IT boom. A Deflationary Impact? As noted above, we view robotics as another chapter in a long history of technological advancements. Pessimists suggest that the latest advances are different because they are inherently more threatening to the overall job market and wage share of total income. If the pessimists are right, what are the theoretical channels though which this would have a greater disinflationary effect relative to previous GPT technologies? Faster Productivity Gains: Enhanced productivity drives down unit labor costs, which may be passed along to other industries (as cheaper inputs) and to the end consumer. More Human Displacement: The jobs created in other areas may be insufficient to replace the jobs displaced by robots, leading to lower aggregate income and spending. The loss of income for labor will simply go to the owners of capital, but the point is that the labor share of income might decline. Deflationary pressures could build as aggregate demand falls short of supply. Even in industries that are slow to automate, just the threat of being replaced by robots may curtail wage demands. Inequality: Some have argued that rising inequality is partly because the spoils of new technologies over the past 20 years have largely gone to the owners of capital. This shift may have undermined aggregate demand because upper income households tend to have a high saving rate, thereby depressing overall aggregate demand and inflationary pressures. The human displacement effect, described above, would exacerbate the inequality effect by transferring income from labor to the owners of capital. 1. Productivity It is difficult to see the benefits of robots on productivity at the economy-wide level. Productivity growth has been abysmal across the major developed countries since the Great Recession, but the productivity slowdown was evident long before Lehman collapsed (Chart 7). The productivity slowdown continued even as automation using robots accelerated after 2010. Chart 7Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Some analysts argue that lackluster productivity is simply a statistical mirage because of the difficulties in measuring output in today's economy. We will not get into the details of the mismeasurement debate here. We encourage interested clients to read a Special Report by the BCA Global Investment Strategy service entitled "Weak Productivity Growth: Don't Blame The Statisticians." 4 Our colleague Peter Berezin makes the case that the unmeasured utility accruing from free internet services is large, but so was the unmeasured utility from antibiotics, radio, indoor plumbing and air conditioning. He argues that the real reason that productivity growth has slowed is that educational attainment has decelerated and businesses have plucked many of the low-hanging fruit made possible by the IT revolution. Cyclical factors stemming from the Great Recession and financial crisis are also to blame, as capital spending has been slow to recover in most of the advanced economies. Some other factors that help to explain the decline in aggregate productivity are provided in Appendix 1. Nonetheless, the poor aggregate productivity performance does not mean that there are no benefits to using robots. The benefits are evident at the industrial level, where measurement issues are presumably less vexing for statisticians (i.e., it is easier to measure the output of the auto industry, for example, than for the economy as a whole). Chart 8 plots the level of robot density in 2016 with average annual productivity growth since 2004 for 10 U.S. manufacturing industries (robot density is presented in deciles). A loose positive relationship is apparent. Chart 8U.S.: Productivity Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation Academic studies estimate that robots have contributed importantly to economy-wide productivity growth. The Centre for Economic and Business Research (CEBR) estimated that labor productivity growth rises by 0.07 to 0.08 percentage points for every 1% rise in the rate of robot density.5 This implies that robots accounted for roughly 10% of the productivity growth experienced since the early 1990s in the major economies. Another study of 14 industries across 17 countries by the Centre for Economic Performance (CEP) found that robots boosted annual productivity growth by 0.36 percentage points over the 1993-2007 period.6 This is impressive because, if this estimate holds true for the U.S., robots' contribution to the 2½% average annual U.S. total productivity growth over the period was 14%. To put the importance of robotics into historical context, its contribution to productivity so far is roughly on par with that of the steam engine (Chart 9). It falls well short of the 0.6 percentage point annual productivity contribution from the IT revolution. The implication is that, while the overall productivity performance has been dismal since 2007, it would have been even worse in the absence of robots. What does this mean for inflation? According to the "cost push" model of the inflation process, an increase in productivity of 0.36% that is not accompanied by associated wage gains would reduce unit labor costs (ULC) by the same amount. This should trim inflation if the cost savings are passed on to the end consumer, although by less than 0.36% because robots can only depress variable costs, not fixed costs. There indeed appears to be a slight negative relationship between robot density and unit labor costs at the industrial level in the U.S., although the relationship is loose at best (Chart 10). Chart 9GPT Contribution To Productivity The Impact Of Robots On Inflation The Impact Of Robots On Inflation Chart 10U.S.: Unit Labor Costs Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation In theory, divergences in productivity across industries should only generate shifts in relative prices, and "cost push" inflation dynamics should only operate in the short term. Most economists believe that inflation is a purely monetary phenomenon in the long run, which means that central banks should be able to offset positive productivity shocks by lowering interest rates enough that aggregate demand keeps up with supply. Indeed, the Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. Also, note that inflation is currently low across the major advanced economies, irrespective of the level of robot intensity (Chart 11). From this perspective, it is hard to see that robots should take much of the credit for today's low inflation backdrop. Chart 11Inflation Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation 2. Human Displacement A key question is whether robots and humans are perfect substitutes. If new technologies introduced in the past were perfect substitutes, then it would have led to massive underemployment and all of the income in the economy would eventually have migrated to the owners of capital. The fact that average real household incomes have risen over time, and that there has been no secular upward trend in unemployment rates over the centuries, means that new technologies were at least partly complementary with labor (i.e., the jobs lost as a direct result of productivity gains were more than replaced in other areas of the economy over time). Rather than replacing workers, in many cases tech made humans more productive in their jobs. Rising productivity lifted income and thereby led to the creation of new jobs in other areas. The capital that workers bring to the production process - the skills, know-how and special talents - became more valuable as interaction with technology increased. Like today, there were concerns in the 1950s and 1960s that computerization would displace many types of jobs and lead to widespread idleness and falling household income. With hindsight, there was little to worry about. Some argue that this time is different. Futurists frequently assert that the pace of innovation is not just accelerating, it is accelerating 'exponentially'. Robots can now, or will soon be able to, replace humans in tasks that require cognitive skills. This means that they will be far less complementary to humans than in the past. The displacement effect could thus be much larger, especially given the impressive advances in artificial intelligence. However, Box 1 discusses why the threat to workers posed by AI is also heavily overblown in the media. The CEP multi-country study cited above did not find a large displacement effect; robot usage did not affect the overall number of hours worked in the 23 countries studied (although it found distributional effects - see below). In other words, rather than suppressing overall labor input, robot usage has led to more output, higher productivity, more jobs and stronger wage and income growth. A report by the Economic Policy Institute (EPI)7 takes a broader look at automation, using productivity growth and capital spending as proxies. Automation is what occurs as the implementation of new technologies is incorporated along with new capital equipment or software to replace human labor in the workplace. If automation is increasing 'exponentially' and displacing workers on a broad scale, one would expect to see accelerating productivity growth, robust capital spending, and more violent shifts in occupational shares. Exactly the opposite has occurred. Indeed, the report demonstrates that occupational employment shifts were far slower in the 2000-2015 period than in any decade in the 1900s (Chart 12). Box 1 The Threat From AI Is Overblown Media coverage of AI/Deep Learning has established a consensus view that we believe is well off the mark. A recent Special Report from BCA's Technology Sector Strategy service dispels the myths surrounding AI.8 We believe the consensus, in conjunction with warnings from a variety of sources, is leading to predictions, policy discussions, and even career choices based on a flawed premise. It is worth noting that the most vocal proponents of AI as a threat to jobs and even humanity are not AI experts. At the root of this consensus is the false view that emerging AI technology is anything like true intelligence. Modern AI is not remotely comparable in function to a biological brain. Scientists have a limited understanding of how brains work, and it is unlikely that a poorly understood system can be modeled on a computer. The misconception of intelligence is amplified by headlines claiming an AI "taught itself" a particular task. No AI has ever "taught itself" anything: All AI results have come about after careful programming by often PhD-level experts, who then supplied the system with vast amounts of high quality data to train it. Often these systems have been iterated a number of times and we only hear of successes, not the failures. The need for careful preparation of the AI system and the requirement for high quality data limits the applicability of AI to specific classes of problems where the application justifies the investment in development and where sufficient high-quality data exists. There may be numerous such applications but doubtless many more where AI would not be suitable. Similarly, an AI system is highly adapted to a single problem, or type of problem, and becomes less useful when its application set is expanded. In other words, unlike a human whose abilities improve as they learn more things, an AI's performance on a particular task declines as it does more things. There is a popular misconception that increased computing power will somehow lead to ever improving AI. It is the algorithm which determines the outcome, not the computer performance: Increased computing power leads to faster results, not different results. Advanced computers might lead to more advanced algorithms, but it is pointless to speculate where that may lead: A spreadsheet from 2001 may work faster today but it still gives the same answer. In any event, it is worth noting that a tool ceases to be a tool when it starts having an opinion: there is little reason to develop a machine capable of cognition even if that were possible. Chart 12U.S. Job Rotation Has Slowed The Impact Of Robots On Inflation The Impact Of Robots On Inflation The EPI report also notes that these indicators of automation increased rapidly in the late 1990s and early 2000s, a period that saw solid wage growth for American workers. These indicators weakened in the two periods of stagnant wage growth: from 1973 to 1995 and from 2002 to the present. Thus, there is no historical correlation between increases in automation and wage stagnation. Rather than automation, the report argues that it was China's entry into the global trading system that was largely responsible for the hollowing out of the U.S. manufacturing sector. We have also made this argument in previous research. The fact that the major advanced economies are all at, or close to, full employment supports the view that automation has not been an overwhelming headwind for job creation. Chart 13 demonstrates that there has been no relationship between the change in robot density and the loss of manufacturing jobs since 1993. Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. Interestingly, despite a worsening labor shortage, robot density among Japanese firms is falling. Moreover, the Japanese data show that the industries that have a high robot usage tend to be more, not less, generous with wages than the robot laggard industries. Please see Appendix 2 for more details. Chart 13Global Manufacturing Jobs Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation The bottom line is that it does not appear that labor displacement related to automation has been responsible in any meaningful way for the lackluster average real income growth in the advanced economies since 2007. 3. Inequality That said, there is evidence suggesting that robots are having important distributional effects. The CEP study found that robot use has reduced hours for low-skilled and (to a lesser extent) middle-skilled workers relative to the highly skilled. This finding makes sense conceptually. Technological change can exacerbate inequality by either increasing the relative demand for skilled over unskilled workers (so-called "skill-biased" technological change), or by inducing companies to substitute machinery and other forms of physical capital for workers (so-called "capital-biased" technological change). The former affects the distribution of labor income, while the latter affects the share of income in GDP that labor receives. A Special Report appearing in this publication in 2014 focused on the relationship between technology and inequality.9 The report highlighted that much of the recent technological change has been skill-biased, which heavily favors workers with the talent and education to perform cognitively-demanding tasks, even as it reduces demand for workers with only rudimentary skills. Moreover, technological innovations and globalization increasingly allow the most talented individuals to market their skills to a much larger audience, thus bidding up their wages. The evidence suggests that faster productivity growth leads to higher average real wages and improved living standards, at least over reasonably long horizons. Nonetheless, technological change can, and in the future almost certainly will, increase income inequality. The poor will gain, but not as much as the rich. The fact that higher-income households tend to maintain a higher savings rate than low-income households means that the shift in the distribution of income toward the higher-income households will continue to modestly weigh on aggregate demand. Can the distribution effect be large enough to have a meaningful depressing impact on inflation? We believe that it has played some role in the lackluster recovery since the Great Recession, with the result that an extended period of underemployment has delivered a persistent deflationary impulse in the major developed economies. However, as discussed above, stimulative monetary policy has managed to overcome the impact of inequality and other headwinds on aggregate demand, and has returned the major countries roughly to full employment. Indeed, this year will be the first since 2007 that the G20 economies as a group will be operating slightly above a full employment level. Inflation should respond to excess demand conditions, irrespective of any ongoing demand headwind stemming from inequality. Conclusions Technological change has led to rising living standards over the decades. It did not lead to widespread joblessness and did not prevent central banks from meeting their inflation targets over time. The pessimists argue that this time is different because robots/AI have a much larger displacement effect. Perhaps it will be 20 years before we will know the answer. But our main point is that we have found no evidence that recent advances in robotics and AI, while very impressive, will be any different in their macro impact. There is little evidence that the modern economy is less capable in replacing the jobs lost to automation, although the nature of new technologies may be affecting the distribution of income more than in the past. Real incomes for the middle- and lower-income classes have been stagnant for some time, but this is partly due to productivity growth that is too low, not too high. Moreover, it is not at all clear that positive productivity shocks are disinflationary beyond the near term. The link between robot usage and unit labor costs over the past couple of decades is loose at best at the industry level, and is non-existent when looking across the major countries. The Fed was able to roughly meet its 2% inflation target in the 1990s and the first half of the 2000s, despite IT's impressive contribution to productivity growth during that period. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. The global output gap will shift into positive territory this year for the first time since the Great Recession. Any resulting rise in inflation will come as a shock since the bond market has discounted continued low inflation for as far as the eye can see. We expect bond yields and implied volatility to rise this year, which may undermine risk assets in the second half. Mark McClellan Senior Vice President The Bank Credit Analyst Brian Piccioni Vice President Technology Sector Strategy Appendix 1 Why Is Productivity So Low? A recent study by the OECD10 reveals that, while frontier firms are charging ahead, there is a widening gap between these firms and the laggards. The study analyzed firm-level data on labor productivity and total factor productivity for 24 countries. "Frontier" firms are defined to be those with productivity in the top 5%. These firms are 3-4 times as productive as the remaining 95%. The authors argue that the underlying cause of this yawning gap is that the diffusion rate of new technologies from the frontier firms to the laggards has slowed within industries. This could be due to rising barriers to entry, which has reduced contestability in markets. Curtailing the creative-destruction process means that there is less pressure to innovate. Barriers to entry may have increased because "...the importance of tacit knowledge as a source of competitive advantage for frontier firms may have risen if increasingly complex technologies were to increase the amount and sophistication of complementary investments required for technological adoption." 11 The bottom line is that aggregate productivity is low because the robust productivity gains for the tech-savvy frontier companies are offset by the long tail of firms that have been slow to adopt the latest technology. Indeed, business spending has been especially weak in this expansion. Chart 14 highlights that the slowdown in U.S. productivity growth has mirrored that of the capital stock. Chart 14U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity Appendix 2 Japan - The Leading Edge Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. The popular press is full of stories of how robots are taking over. If the stories are to be believed, robots are the answer to the country's shrinking workforce. Robots now serve as helpers for the elderly, priests for weddings and funerals, concierges for hotels and even sexual partners (don't ask). Prime Minister Abe's government has launched a 5-year push to deepen the use of intelligent machines in manufacturing, supply chains, construction and health care. Indeed, Japan was the leader in robotics use for decades. Nonetheless, despite all the hype, Japan's stock of industrial robots has actually been eroding since the late 1990s (Chart 4). Numerous surveys show that firms plan to use robots more in the future because of the difficulty in hiring humans. And there is huge potential: 90% of Japanese firms are small- and medium-sized (SME) and most are not currently using robots. Yet, there has been no wave of robot purchases as of 2016. One problem is the cost; most sophisticated robots are simply too expensive for SMEs to consider. This suggests that one cannot blame robots for Japan's lack of wage growth. The labor shortage has become so acute that there are examples of companies that have turned down sales due to insufficient manpower. Possible reasons why these companies do not offer higher wages to entice workers are beyond the scope of this report. But the fact that the stock of robots has been in decline since the late 1990s does not support the view that Japanese firms are using automation on a broad scale to avoid handing out pay hikes. Indeed, Chart 15 highlights that wage deflation has been the greatest in industries that use almost no robots. Highly automated industries, such as Transportation Equipment and Electronics, have been among the most generous. This supports the view that the productivity afforded by increased robot usage encourages firms to pay their workers more. Looking ahead, it seems implausible that robots can replace all the retiring Japanese workers in the years to come. The workforce will shrink at an annual average pace of 0.33% between 2020 and 2030, according to the Japan Institute for Labour Policy and Training. Productivity growth would have to rise by the same amount to fully offset the dwindling number of workers. But that would require a surge in robot density of 4.1, assuming that each rise in robot density of one adds 0.08% to the level of productivity (Chart 16). The level of robot sales would have to jump by a whopping 2½ times in the first year and continue to rise at the same pace each year thereafter to make this happen. Of course, the productivity afforded by new robots may accelerate in the coming years, but the point is that robot usage would likely have to rise astronomically to offset the impact of the shrinking population. Chart 15Japan: Earnings Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation Chart 16Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood Of Robots? The implication is that, as long as the Japanese economy continues to grow above roughly 1%, the labor market will continue to tighten and wage rates will eventually begin to rise. 1 Please see Technology Sector Strategy Special Report "The Coming Robotics Revolution," dated May 16, 2017, available at tech.bcaresearch.com 2 Note that this includes only robots used in manufacturing industry, and thus excludes robots used in the service sector and households. However, robot usage in services is quite limited and those used in households do not add to GDP. 3 Note that ICT investment and capital stock data includes robots. 4 Please see BCA Global Investment Strategy Special Report "Weak Productivity Growth: Don't Blame The Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 5 Centre for Economic and Business Research (January 2017) "The Impact of Automation." A Report for Redwood. In this report, robot density is defined to be the number of robots per million hours worked. 6 Graetz, G., and Michaels, G. (2015): "Robots At Work." CEP Discussion Paper No 1335. 7 Mishel, L., and Bivens, J. (2017): "The Zombie Robot Argument Lurches On," Economic Policy Institute. 8 Please see BCA Technology Sector Strategy Special Report "Bad Information - Why Misreporting Deep Learning Advances Is A Problem," dated January 9, 2018, available at tech.bcaresearch.com 9 Please see The Bank Credit Analyst, "Rage Against the Machines: Is Technology Exacerbating Inequality?" dated June 2014, available at bca.bcaresearch.com. 10 OECD Productivity Working Papers, No. 05 (2016) "The Best Versus the Rest: The Global Productivity Slowdown, Divergence Across Firms and the Role of Public Policy." 11 Please refer to page 8.

Underweight United Airlines spooked the market this week when they announced their plans to grow capacity by 4-6% per year until 2020; the stock fell by 11% that day and took the S&P airlines index down with it. Capacity additions of this magnitude force competitors to choose between matching or ceding market share. Either choice bodes poorly for airfare pricing, probably unwisely considering how consumer spending on airfares has already fallen off a cliff (second panel). Meanwhile, input prices have shot upward and have diverged sharply from airlines’ ability to pass through fuel costs (third panel). This means a reversal of the downward trend in margins remains well beyond the horizon (bottom panel). Investors should avoid the turbulence; stay underweight. The ticker symbols for the stocks in this index are: BLBG: S5AIRL - DAL, LUV, AAL, UAL, ALK. Capacity Additions Add Unwanted Headwinds Capacity Additions Add Unwanted Headwinds