Today’s US-led global expansion has a reasonable probability of becoming the longest economic expansion on record, in excess of 120 months. Although the age of the expansion often prompts questions of sustainability, we would stress that previous expansions typically have not died of old age.
On the contrary, there is ample evidence that the global landscape is better, stronger, and faster today than at any previous point in the current expansion.
Lest we be accused of unbridled enthusiasm, here is a note of caution. Data suggests that while some of the strongest returns have occurred during the later stages of an economic expansion, these returns have often grown more idiosyncratic, volatile, and negatively skewed as the cycle ages. In our view, these patterns create a strong rationale for greater selectivity and risk management.
Broad participation and synchronized geographically. Growth acceleration may have peaked, but recent easy financial conditions and fiscal prospects have also been supportive.
Diminishing excess capacity may support prices longer-term, though the adjustment higher is likely to be gradual and country specific as endogenous factors reassert influence.
Global central banks enter an important era of policy transition requiring precise communication on rate and balance sheet normalization. Leadership changes remain top of mind.
The possibility of pro-cyclical US policy has continued to intrigue markets, but the news cycle of near-constant controversy and legislative bottlenecks are blocking meaningful initiatives.
Geopolitical risk dominates, followed by the pace of US hikes, Brexit turbulence, Chinese macro stability, lofty valuations, and diminished market liquidity.
Source: International Monetary Fund, Haver, and GSAM. Number visuals on the left represent the percent of the 193 UN member countries with economies that are experiencing positive year-over-year Gross Domestic Product (GDP) growth (94%) and the percent of UN member countries with economies that are experiencing both positive and accelerating year-over-year GDP growth (61%). 2017 numbers refer to forecasts from the International Monetary Fund. The economic and market forecasts presented herein have been generated by GSAM for informational purposes as of the date of this presentation. They are based on proprietary models and there can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this presentation. Right side line chart shows trailing 30 month volatility of the Markit Global Composite Purchasing Managers’ Index monthly from 2000 to August 2017. Composite refers to a weighted aggregation of manufacturing and services sectors. PMI surveys based on questionnaire responses from panels of senior purchasing executives (or similar). Respondents are asked to state whether business conditions for a number of variables have improved, deteriorated or stayed the same compared with the previous month, as well as to provide reasons for any changes. A reading of over 50 indicates expansion; a reading of less than 50 indicates contraction. Please see additional disclosures at the end of this presentation. Volatility refers to standard deviation.
We expect more of the same. We believe the pace of the recovery has likely peaked, but growth trends should persist as more developed and emerging markets participate. Central banks remain accommodative.
We believe European balance sheet growth may slow and its US equivalent may shrink, albeit at a glacial pace, with markets also intensely focused on the evolution of rate policy. Expansions have not typically died of old age, but Federal Reserve policy has frequently been a counter-cyclical force.
Economic data points to the persistence of the current economic expansion, though risks have increased in the area of reduced labor capacity. Late stage economic cycles generally have been accretive to risk assets, even though broader return dispersion has typically pointed toward greater selectivity and dynamism.
Top Section Notes: As of August 2017. Chart shows the 3 month rolling average of monthly central bank net asset purchases in billions of USD from 2009 through 2019. The economic and market forecasts presented herein are for informational purposes as of the date of this presentation. There can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this presentation. Bottom Section Notes: As of August 31, 2017. The chart shows quarterly data of the unconditional probability of a US recession in the next 9 quarters from January 1981 to June 2017, the latest available data. The lines show the amount of time from current levels (33%) it has historically taken to enter a recession, as defined by the National Bureau of Economic Research. The economic and market forecasts presented herein have been generated by GSAM for informational purposes as of the date of this presentation. They are based on proprietary models and there can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this presentation.
Equities remain our preferred asset class, but the 2017 run-up has further tempered our return expectations globally. Earnings growth is likely to be the primary driver in light of full valuations.
The market appears to be underpricing the pace of Fed hikes and overpricing the value of weaker inflation data. Government debt may be a less effective hedge.
Tight spreads and higher leverage reflect late-cycle conditions, leaving us cautious on credit spreads. We believe it is still too early to de-risk, but appropriate to amplify selectivity.
Euro strength largely reflects the repricing of central bank policy and better-than-expected European growth. We believe the US Dollar appears cyclically cheap.
Low volatility reflects the strong macro backdrop, but may be highly vulnerable to exogenous shocks, especially in the form of political catalysts and geopolitical tensions.
Source: NBER, Bloomberg, and GSAM. Data from January 1928 to August 2017, the largest available dataset for the S&P 500 Index. Chart shows S&P 500 Index total returns for the 12 month period 2-years prior and the 12 month period 1-year prior to the start of a recession. Recession periods are defined by the National Bureau of Economic Research. “Bearish” refers to remaining cautious. Past performance does not guarantee future results, which may vary.
Absent a shift in macro drivers, we believe macro conditions remain supportive of risk assets, even as valuations suggest moderate return potential and increased tail risk.
Fundamentals have trumped regional issues and headline risk, resulting in exceptionally low volatility. At the same time, markets remain susceptible to a diverse range of shocks. The rapid speed at which market regimes can shift calls for a preemptive approach to portfolio design.
With volatility hovering near its first (1%) historical percentile for most of 2017, the probability of an increase in vol seems quite high. While higher volatility is often associated with lower returns, it is not always so. Higher volatility upon the exit of a low-vol period such as the present has been associated with positive two-year returns 82% of the time.
Top Section Notes: Top panel chart shows S&P 500 Index rolling annualized 60-day volatility from January 1928 to August 2017 and labels various market events that occurred when volatility moved significantly higher ending low volatility periods. These events are illustrative examples. Volatility is measured by annualizing the standard deviation of daily S&P 500 Index total returns. The right bar chart is for illustrative purposes only and analyzes all 11 events that have ended sustained low volatility periods since 1928. Sustained low volatility periods refer to periods when the 2 year moving average of S&P 500 volatility dipped into or below its 33rd percentile (bottom third of its history). Please see additional disclosures at the end of this document for event descriptions. Past performance does not guarantee future results, which may vary. Bottom Section Notes: Chart shows the historically observed range of outcomes for the growth of $100 invested in S&P 500 Index total returns over a two year period during and after sustained periods of low volatility. Please see end notes for event date descriptions. Analysis relies on a Bloomberg dataset of S&P 500 daily total returns from 1928 to 2016. Volatility refers to standard deviation of S&P 500 index total returns. The shaded range of historically observed outcomes is based on the consistently highest and lowest observed return outcome during low volatility markets and after low volatility markets ended. GROWTH OF $100: A graphical measurement of a portfolio's gross return that simulates the performance of an initial investment of $100 over the given time period. Indices are unmanaged. The figures for the index reflect the reinvestment of all income or dividends, as applicable, but do not reflect the deduction of any fees or expenses which would reduce returns. Investors cannot invest directly in indices. Probability of outcomes after exiting low volatility represents the probability of a positive or negative return two years after exiting a low volatility market.
The impasse in Washington may have led many investors to rule out tax cuts.
The initial surge of stocks with the highest sensitivity to tax policy changes has since given way to parity with the broader market. While the timing and magnitude of potential tax legislation remains uncertain, we believe the market could respond favorably to any legislative clarity.
Source: Bloomberg, Goldman Sachs Global Investment Research, and GSAM.
Even a modest change in the status quo could be positive for equities.
In our view, a reduction of the highest corporate tax rate from 35% to 20% could boost earnings for US large cap stocks by $10. For US small cap stocks, we believe the positive impact may be even greater, with the Russell 2000’s median effective tax rate at 32% and the S&P 500’s at 26%.
Source: S&P Capital IQ, Goldman Sachs Global Investment Research, and GSAM.
Top Section Notes: As of August 31, 2017. Chart shows the relative performance of a portfolio of high tax rate S&P 500 stocks versus the broader S&P 500 Index to represent how the market may be pricing the probability for corporate tax reform. Hypothetical S&P 500 High Corporate Tax Rate Stock Portfolio allocation (an illustrative portfolio of high corporate tax rate equities): an equal weight blend of the 50 S&P 500 Index equities with the highest 10-year median corporate tax rate as of August 31, 2016. The 10-year median corporate tax rate refers to the median effective corporate tax rate paid over the last 10 years. These illustrative results do not reflect any GSAM product and are being shown for informational purposes only. No representation is made that an investor will achieve results similar to those shown. The performance results are based on historical performance of the indices used. The result will vary based on market conditions and your allocation. GROWTH OF $100: A graphical measurement of a portfolio's gross return that simulates the performance of an initial investment of $100 over the given time period. The example provided does not reflect the deduction of investment advisory fees and expenses which would reduce an investor's return. Please be advised that since this example is calculated gross of fees and expenses the compounding effect of an investment manager's fees are not taken into consideration and the deduction of such fees would have a significant impact on the returns the greater the time period and as such the value of the $100 if calculated on a net basis, would be significantly lower than shown in this example. Past performance does not guarantee future results, which may vary. Bottom Section Notes: As of August 2017. Chart shows the House Republican tax reform proposal and the estimated impact a corporate tax rate cut of this size may have on earnings of the S&P 500 Index. EPS refers to Earnings per Share. The economic and market forecasts presented herein are for informational purposes as of the date of this document. There can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this document.
A range of indicators suggest the expansion is healthy across developed markets.
Economic fundamentals have improved broadly across Europe and other parts of the developed world. The trend is especially evident when comparing the present to early 2012, a time of skepticism that global fundamentals could justify higher rates.
Source: GSAM and Bloomberg.
Earnings momentum is positive and improving in developed markets outside the US.
The trend of upward earnings revisions in 2017 is a contrast to the flattish or modest downward revisions seen in the last five years. This positive trend helps explain the 2017 outperformance of developed markets versus US equities.
Source: Datastream, Goldman Sachs Global Investment Research, and GSAM.
Top Section Notes: 2Q 2012 was chosen to capture a 5 year change and ‘Current’ is represented by the most recent available quarter end data as of 2Q 2017. Eurozone Non-Financial Corporate Lending tracks the % change year-over-year in the outstanding amount of credit or loans extended to businesses and consumers during the Q2 2012 and as of Q2 2017, or latest available. Eurozone employment is the % change year-over-year in ECB Eurozone employment during the Q2 2012 and as of Q2 2017, or latest available. Spanish Real Estate represents the Spain Real Estate Activities Index reported by Bloomberg during Q2 2012 and as of Q2 2017, or latest available. French Consumer Confidence is reported by the EU and represents the Economic Sentiment Indicator. Bottom Section Notes: As of August 2017. EPS Estimates refers to the MSCI EAFE Index Bloomberg consensus earnings per share estimates for the forward 12-months. International securities entail special risks such as currency, political, economic, and market risks.
Synchronized emerging market growth has often pointed to longer and more sustainable market cycles.
EM economic recoveries in our view can find strength in numbers. When EM economies move together, this can be a sign of the health and sustainability of the expansion.
Source: Goldman Sachs Global Investment Research and GSAM.
What emerging markets investors own has often been more important than where the asset is located.
Decomposing MSCI Emerging Markets Index returns over the last three years reveals that security selection historically has been a more significant driver of performance than top-down, country-level trends. We believe this trend will continue in the current market environment.
Source: Factset, Goldman Sachs Global Investment Research, and GSAM.
Top Section Notes: Data from Q3 1992 to Q3 2017. Chart compares the length of economic recoveries in the emerging markets (EM) with the degree to which that recovery is synchronized across countries. Length of recovery is measured in quarters. The degree to which the recovery is synchronized across EM is measured by the real GDP growth rate differential between the EM country with the 90th percentile growth rate and the 10th percentile growth rate. This differential is inverted on the axis. The dotted arrow line does not represent a forecast and is for illustrative purposes only. Bottom Chart Notes: As of August 31, 2017. Chart shows individual stock and country market returns over the last 3 years. Country markets refer to the indices that represent the entire equity markets of each EM country. Individual stocks refer to the collective stocks across the indices of every EM country market. Emerging markets securities may be less liquid and more volatile and are subject to a number of additional risks, including but not limited to currency fluctuations and political instability. Past performance does not guarantee future results, which may vary.
The explosion in unstructured data is expanding inputs, including from new sources such as the Internet of Things.
Cloud-based computing is enabling machines and other physical devices to communicate. The interconnectivity enabled by the Internet of Things and related phenomena is driving exponential growth in unstructured data. Harnessing this digital deluge is an opportunity for every industry.
Source: McKinsey and GSAM.
Converting unstructured data into investment insight requires both capacity and judgement.
The democratization of data provides access to enormous amounts of information on virtually every public company. Collecting and interpreting this data requires a sound process. We believe combining human judgement with economically motivated design and technological prowess may achieve a repeatable informational advantage.
Top Section Notes: For illustrative purposes only. “Internet of Things” refers to the interconnection via the internet of computing devices embedded in everyday objects. Text data points refer to research done by McKinsey. Bottom Section Notes: For illustrative purposes only.
Current trends look sustainable, but the credit cycle bears close watch.
Even amid a healthy global economic expansion, credit indicators give reason for caution. Spreads in US investment grade (IG) credit (to take one prominent example) are near all-time lows, while leverage, as measured by net debt to EBITDA, has crept up to 10 year highs.
Source: Barclays Live and GSAM.
Credit beta frequently exposes investors to sub-optimal compositions of risk and return.
The corporate bond market has flipped the old risk-reward proposition on its head, providing investors in the weakest decile of corporate fundamentals with higher volatility and lower returns. As the cycle ages, we believe investors should be wary of the challenges often associated with the bottom decile.
Source: Citi and GSAM.
1. Analysis uses the Citi US Broad Investment-Grade Index (USBIG Index) screened to remove all bonds with issuances less than $750 million in par value and issuers with less than $2 billion in total outstanding debt.
Top Section Notes: As of August 2017. Spread refers to Option Adjusted Spread of the asset class, the difference in yield between a US Treasury bond and a bond with the same maturity but different credit quality. +/- 1 Standard Deviation refers to a one standard deviation band around the mean value. US High Yield refers to the Bloomberg Barclays US Corp High Yield Index. Euro High Yield refers to the Bloomberg Barclays Pan-European High Yield Index. US Investment Grade refers to the Bloomberg Barclays Investment-Grade Corporate Bond Index. Euro Investment Grade refers to the Bloomberg Barclays Pan-European Aggregate Corporate Index. Emerging Market Debt (USD) refers to the Bloomberg Barclays Emerging Markets USD Aggregate Index. Calculations of the median and standard deviation of each asset class’ credit spread are based on data from the inception of each index to present. The inception points of each index are January 1994, August 2000, January 1980, August 2000, and August 2000 for US High Yield, Euro High Yield, US Investment Grade, Euro Investment Grade, and Emerging Market Debt (USD) respectively. EBITDA refers to Earnings Before Interest, Taxes, Depreciation, and Amortization. Net debt refers to total debt less cash. Bottom Section Notes: As of Q2 2017. The chart filters this liquidity screened USBIG Index into deciles based on two fundamental characteristics: operating margin and leverage (measured by debt-to-enterprise value). The percentile ranking of each issue is based on a 50-50 mixed rank of these two indicators where high margins and low leverage would categorize an issue in the 1st decile while low margins and high leverage would categorize an issuer in the 10th decile. When only a single indicator is available, that single indicator will be used to calculate the issuer's composite rank. Issuers are ranked relative to their respective industry. Both volatility and return figures refer to annualized return and volatility based on the last 10 years of index data from 2007 to present. Volatility is the annualized standard deviation of monthly returns. Past performance does not guarantee future results, which may vary.
Either stocks or bonds have been under pressure about half the time in recent decades
Investors’ experience has often contrasted with the recent low market volatility. We believe investors should keep the inevitability of challenging market environments (like periods of rising rates or falling equity prices) in mind as they construct investment portfolios.
Source: GSAM and Bloomberg.
In challenging market environments, alternative strategies have often been attractive.
In periods when rates rose and when equity returns were negative, category leadership was variable— leaders became losers and vice versa. The dynamic nature of the current market environment underscores the logic of diversifying across strategy types.
Source: GSAM and Bloomberg.
Top Section Notes: Analysis from December 31, 1997 to August 31, 2017. S&P 500 represents the S&P 500 Total Return Index. Challenging environments are equity bear markets and rising rate periods. Bear markets are defined as periods in which the S&P 500 realized at least a 15% pullback. Rising rate periods represent the four longest periods during which the US 10-Year Treasury rate rose. Bottom Section Notes: Analysis from December 31, 1997 to August 31, 2017 with rising rate and equity bear market periods matching the top section. Please see end notes for period date ranges. Alternative substrategies represent an equal weight blend of their respective HFRI and HFRX substrategy indices: Equity Long/Short represents HFRI/HFRX Equity Hedge, Event Driven represents HFRI/HFRX Event Driven, Relative Value represents HFRI/HFRX Relative Value, Tactical Trading represents HFRI/HFRX Macro. US Aggregate Bonds represents the Bloomberg Barclays US Aggregate Bond Index. These illustrative results do not reflect any GSAM product and are being shown for informational purposes only. No representation is made that an investor will achieve results similar to those shown. The performance results are based on historical performance of the indices used. The result will vary based on market conditions and your allocation. Investments in Alternatives expose investors to risks that have the potential to result in losses. These strategies involve risks that may not be present in more traditional (e.g., equity or fixed income) securities. See additional disclosures in Appendix.
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