A Tactical Investment Outlook as Global Growth Slows

Has There Been Enough Capitulation?

Our main tactical concern: there hasn’t been enough capitulation in risk assets (equities and credit) to reflect slower economic growth.

Whether or not the US is explicitly in a recession, we would expect a period of roughly zero growth in real terms would spur a bigger change in investors’ behavior. Credit yields are at 10-year-plus highs and equities have seen outflows, but we still see room for slower growth—and geopolitical considerations—to be priced into valuations. For investors with long time horizons, our view is more positive.

This view of risk-asset valuations raises a question: Is it possible to time markets? This is extremely hard to do, and establishing skill requires a long run of data. However, given that we’re in a more volatile, less trended environment today, there’s more of a strategic incentive to try.

Liquidity Concerns Are an Emerging Issue

Beyond directional outlooks for asset classes and factors, liquidity is a huge emerging issue that we don’t think is reflected in markets or asset allocations. It’s a topic that comes up increasingly in our dialogues with clients, driven by the confluence of very powerful forces:

The macro backdrop features less macro liquidity as central banks (try to) pivot from quantitative easing to quantitative tightening.

Institutional portfolios have become significantly less liquid as a result of the rotation into private assets over the past decade.

Liquidity in public markets has become more fragile.¹

One could also cite slower growth, the rupture of crypto markets, the return of the business cycle and potential geopolitical risks as contributors to liquidity risks. This backdrop isn’t enough to make us bearish, but investors should put more emphasis on liquidity than normal, making this a recurring focus that intrudes on tactical allocation questions.

The UK liability-driven investing crisis may be a canary in the coal mine in this regard, and investors should expect liquidity to be an increasingly dominant issue in asset allocation over the next year—particularly on the key strategic allocation question of public versus private assets, a point well addressed in upcoming research. In the sections to follow, we’ll lay out our tactical view on asset classes and factors (Display 1).

Historical analysis and current forecasts do not guarantee future results.
As of December 2, 2022
Source: AllianceBernstein (AB)

Equities: Capitulation Overhang, but Also Positive Forward Indicators

Stocks face an overhang on two fronts: a lack of capitulation by investors and by analysts in the face of slowing economic growth.

While bond funds saw large outflows earlier this year, net outflows for equities have been muted (Display 2). There have been outflows from European equities, which seems fair given the scale of the potential growth shock from risks to the energy supply, but there’s been no capitulation for global equities. So far in the fourth quarter, global equity funds have seen US$50 billion of inflows.

Historical analysis and current forecasts do not guarantee future results.
Chart shows cumulative weekly flow into all equity funds, bond funds and money market funds
As of November 9, 2022
Source: AB Bernstein Research, Emerging Portfolio Fund Research Global and AB

Historical analysis and current forecasts do not guarantee future results.
EPS: earnings-per-share
As of November 21, 2022
Source: MSCI, Thomson Reuters Datastream, Thomson Reuters I/B/E/S and AB

Historical analysis and current forecasts do not guarantee future results.
As of November 11, 2022
Source: Bloomberg; “Economic Policy Uncertainty Index," Economic Policy Uncertainty, http://www.policyuncertainty.com; Federal Reserve Economic Data (FRED), National Restaurant Association, Thomson Reuters Datastream, University of Michigan and AB

Historical analysis and current forecasts do not guarantee future results.
Chart shows the combined net purchases of overseas equities for US, UK, euro area (post 1997), Germany (1987–1997), France (1993–1997) and Japan (post 1997). Data derived from external sector portfolio investment data published in the financial accounts of central banks. The series is monthly flows smoothed over three months, annualised and normalised by the market cap of the Thomson Reuters Datastream World Index.
As of July 31, 2022
Source: Banque de France, Deutsche Bundesbank, ECB, Ministry of Finance Japan, Office for National Statistics, Thomson Reuters Datastream, US Fed and AB

Historical analysis and current forecasts do not guarantee future results.
As of October 20, 2022
Source: Robert Shiller’s database, Thomson Reuters Datastream and AB

Credit: Higher Yields Balanced with Caution on Slower Growth Impact

Our recent conversations with clients about credit from a multi-asset context reveal divided views. On one hand, nominal yields for both investment-grade and high-yield bonds are near the top of their range from the past decade—undeniably attractive to investors starved of return sources for many years. From a cross-asset perspective, however, there are differing views on whether enough of a slowdown is priced in from a tactical perspective.

In Display 7, we show credit spreads during previous recessions, and in that context the yield surge seems to have more to do with the underlying risk-free rate increase than spreads per se. We acknowledge that corporate balance sheets are currently in better health than they usually are when entering a period of slower growth. Also, in the US at least, debt has been refinanced at longer terms. However, growth is slowing down. We’re not saying spreads need to reach previous recessionary highs, given the other factors noted, but there is potential scope for them to move wider.

Historical analysis and current forecasts do not guarantee future results.
As of November 2, 2022
Source: FRED, Thomson Reuters Datastream and AB

Historical analysis and current forecasts do not guarantee future results.
IG: investment-grade
As of October 31, 2022
Source: FRED, Thomson Reuters Datastream and AB

Historical analysis and current forecasts do not guarantee future results.
As of October 31, 2022
Source: FRED, Thomson Reuters Datastream and AB

Treasury Inflation-Protected Securities (TIPS) vs. Nominal Bonds

The surge in yields prompts a question: Is it an attractive point to add government bonds? For investors targeting real return, there are two issues—whether the return is sufficient, even after expectations have been adjusted upward in coming months, and the role of duration if it’s less effective at diversifying equity beta. However, for investors with fixed nominal liabilities, 2022 could be a gamechanger that makes it easier to meet those liabilities.

For investors with real liabilities, we see the main role of high-grade fixed income as protecting against drawdowns. Admittedly, that didn’t work out well in 2022, but we do think this asset is important even if it’s less useful as a long-term diversifier of equity beta.³ In that drawdown mitigation role, we would favor short duration, given the flat-to-inverted yield curve.

Historically, US TIPS have tended to outperform nominal government bonds in periods of elevated inflation (Display 10), most notably in the early and late 1970s but also at certain points during the 1990s and—more recently—in 2021.

Historical analysis and current forecasts do not guarantee future results.
TIPS: Treasury Inflation-Protected Securities
As of October 31, 2022
Source: Thomson Reuters Datastream and AB

Historical analysis and current forecasts do not guarantee future results.
Data starts from January 1970 or earliest available date (indicated in Start Date column) and runs through September 2022. Equity index valuations are cyclically adjusted earnings yield (1/CAPE ratio). Bond valuation is based on yield. Relative valuation is measured as the relative 12-month forward earnings yield (1/price-to-earnings) relative to the broader US market. Z score of the 60/40 portfolio is calculated as 0.6*z score of US equities and 0.4* z score of US 10-year government bonds. Higher z score value indicates a higher premium to historic valuation.
As of September 30, 2022
Source: FRED, Global Financial Data, MSCI, Thomson Reuters Datastream and AB

Historical analysis and current forecasts do not guarantee future results.
Scenario One: Historic inflationary shocks that coincided with a sharp slowdown in real economic growth, with date ranges including 1Q:1970–4Q:1970, 1Q:1974–3Q:1975, 4Q:1979–4Q:1980, 1Q:1982–4Q:1982, and 3Q:1990–3Q:1991
Scenario Two: A narrower definition of inflationary shocks and low growth looking only at periods where real GDP growth was less than 1% and inflation was more than 4%. Those include: 1Q:1970–4Q:1970, 1Q:1974–3Q:1975, 2Q:1980–4Q:1980, 1Q:1982–4Q:1982, and 4Q:1990–2Q:1991
Scenario Three: Based on the changes in growth and inflation, this scenario focuses on the scenario one episodes but extends the time horizon to earlier quarters, when higher growth was beginning to slow and inflation starting to rise. This scenario includes only quarters where declining real growth coincided with rising inflation, including 3Q:1973–4Q:1974, 1Q:1979–1Q:1980, and 2Q:1990–4Q:1990
Analysis covers the period from January 1, 1970, through September 30, 1991
Source: AQR Capital Management, Global Financial Data, Kenneth R. French Data Library, Robert Shiller’s database, Thomson Reuters Datastream and AB

Equity Factor Exposures

Within equities, our strategic and tactical views on factors echo our broader views on asset classes over these different time horizons. Strategically, over a 10-year-plus horizon, we want to be long deep, or cyclical, value. This positioning is consistent with our more constructive view on risk assets, including equities, in the long term.

Value is our key strategic factor position globally and can be expressed through both long/short and long-only exposure. The pro-value view is supported by the combination of attractive valuations (value stocks remain cheap versus their long-term history) and a favorable macro outlook—specifically our expectation that nominal yields will be higher over the strategic horizon, and that longer-term inflation expectations haven’t adjusted upward yet.

Tactically, we would temper our exposure to deep value in favor of more defensive value measures, such as dividend yield. Again, this aligns with the greater tactical caution we discussed earlier: a tactically cautious view on equities and a preference for quality (investment-grade) within credit. We also see tactical exposures to low-volatility stocks and high-quality stocks as attractive. High-dividend, low-volatility and quality stocks are also attractively valued versus history and likely to outperform in the near term as the economy slows or enters recession.

These factor preferences are global; we’ll follow up with more granular analysis for regional factors. Unless otherwise stated, our views can be implemented using simple MSCI factor definitions and indices. These views are in many ways a natural extension of our broader views on asset allocation, but it may also be helpful to be explicit about how we think about factor positioning—we’ll do this in the rest of this section.

Value: Strategic Overweight but Tactical Caution

Our framework for forming factor views uses two key inputs: the macro environment and style valuations. The macro environment is the most important over a strategic horizon. Key variables include outlooks for the stage of the cycle, long and short rates, and inflation. Other macro and market variables matter over the long term, such as the changes in the yield curve, credit spreads, the equity risk premium, market volatility and policy uncertainty. We’ve studied these relationships empirically over long horizons and summarized them in Displays 13–15. We show more of these relationships in Displays 24–29 in the Appendix.

Note: table shows the annualized return for factor portfolios in different economic cycles from January 1990 to July 2018. Factor returns are defined as the long-short return of the top-bottom quintile from the 500 largest stocks in the MSCI World Index. Portfolios have been rebalanced quarterly and returns are on equal-weighted total return basis. Periods of the economic cycles are defined by the normalized seasonally adjusted composite leading indicator from the OECD. The universe of the indicator is based on the OECD + the six Major Non-member economies. We divide up the world into four phases, with an expensionary level (>100) and positive first differential of the leading indicator being classifed as an “expansion,” an expansionary level with negative first differential being a “slowdown,” a contraction level (<100) and positive first differential being classified as a “recovery,” and a contraction level with negative first differential being a “downturn.”
Note: t-stats are calculated using two samples t-test (Welch’s t-test) with unequal sample sizes and unequal variances
January 31, 1990, through July 31, 2018
Source: MSCI, OECD, Thomson Reuters Datastream and AB

Note: table shows the annualized return from factor portfolios in different rate environments from January 1990 to July 2018. Factor returns are defined as the long-short return of the top-bottom quintile from the 500 largest stocks in the MSCI World Index. Portfolios have been rebalanced quarterly and returns are on equal-weighted total return basis. The yield curve is calculated as the difference between 10-year and two-year rates. We take an equity market cap weighted average of national yields to form a global measure.
Note: t-stats are calculated using two samples t-test (Welch’s t-test) with unequal sample sizes and unequal variances
January 31, 1990, through July 31, 2018
Source: MSCI, Thomson Reuters Datastream and AB

Note: table shows the annualized return from factor portfolios in different inflation environments from January 1990 to July 2018. Factor returns are defined as the long-short return of the top-bottom quintile from the 500 largest stocks in the MSCI World Index. Portfolios have been rebalanced quarterly and returns are on equal-weighted total return basis. We take an equity market cap weighted average of core inflation yields to form a global measure.
Note: t-stats are calculated using two samples t-test (Welch’s t-test) with unequal sample sizes and unequal variances
January 31, 1990, through July 31, 2018
Source: MSCI, Thomson Reuters Datastream and AB

Historical analysis and current forecasts do not guarantee future results.
As of October 11, 2022
Source: Bloomberg and AB

Historical analysis and current forecasts do not guarantee future results.
Charts show the daily performance of cheap price-to-book stocks relative to expensive price-to-book stocks vs. the regional 5y5y inflation swap.
Data from January 1, 2015, through October 7, 2022
Source: Bloomberg, MSCI and AB

Historical analysis and current estimates do not guarantee future results.
Table shows the z scores vs. long-term average valuations for long-only factor baskets relative to global market. The universe is the largest 500 stocks in MSCI World Index, factors proxy MSCI definitions, and we take the median forward P/E multiple of each factor basket vs. the market as a valuation measure.
January 31, 1990, through October 31, 2022
Source: FactSet, MSCI and AB

Historical analysis and current forecasts do not guarantee future results.
Chart shows the median forward P/E of the stocks in the P/B factor basket vs. the market. The basket is rebalanced quarterly.
As of October 31, 2022
Source: FactSet, MSCI and AB

Tactical Tilt Toward Dividend Yield, Low Volatility and Quality

All three of these “defensive” factors fare very well in downturns and recessions, as can be seen clearly in Display 13 earlier. There’s valuation support, too—dividend yield is extremely cheap versus history; relative to the market, it’s by far the cheapest of the key global factors, including all value factors. As can be seen in Display 19 earlier, it’s trading at an extreme 2.7 standard deviations below long-term history (we’ll return to this below). Quality and low volatility, while not as extreme, are also trading at multiples below long-term history. We also show this in Displays 21–23, where all three factors have de-rated considerably versus the market on a forward price-to-earnings basis over the past couple years.

Historical analysis and current forecasts do not guarantee future results.
Chart shows the median forward P/E of the stocks in the dividend yield factor basket vs. the market. The baskets are rebalanced quarterly.
As of October 31, 2022
Source: FactSet, MSCI and AB

Note: table shows the annualized return from factor portfolios in different rate environments from January 1990 to July 2018. Factor returns are defined as the long-short return of the top-bottom quintile from the 500 largest stocks in the MSCI World Index. Portfolios have been rebalanced quarterly and returns are on equal-weighted total return basis. Short rates are two-year sovereign yields. We take an equity market cap weighted average of national yields to form a global measure.
Note: t-stats are calculated using two samples t-test (Welch’s t-test) with unequal sample sizes and unequal variances
January 31, 1990, through July 31, 2018
Source: MSCI, Thomson Reuters Datastream and AB

Note: table shows the annualized return from factor portfolios in different rate environments from January1990 to July 2018. Factor returns are defined as the long-short return of the top-bottom quintile from the 500 largest stocks in the MSCI World Index. Portfolios have been rebalanced quarterly and returns are on equal-weighted total return basis. The yield curve is calculated as the difference between 10-year and two-year rates. We take an equity market cap weighted average of national yields to form a global measure.
Note: t-stats are calculated using two samples t-test (Welch’s t-test) with unequal sample sizes and unequal variances
January 31, 1990, through July 31, 2018
Source: MSCI, Thomson Reuters Datastream and AB

Note: table shows the annualized return from factor portfolios in different credit cycle environments from January 1990 to July 2018. Factor returns are defined as the long-short return of the top-bottom quintile from the 500 largest stocks in the MSCI World Index. Portfolios have been rebalanced quarterly and returns are on equal-weighted total return basis. We use US BAA–AAA credit spread to define the credit cycle
Note: t-stats are calculated using two samples t-test (Welch’s t-test) with unequal sample sizes and unequal variances
January 31, 1990, through July 31, 2018
Source: MSCI, Thomson Reuters Datastream and AB

Note: table shows the annualized return from factor portfolios in different GDP cycles from January1990 to July 2018. Factor returns are defined as the long-short return of the top-bottom quintile from the 500 largest stocks in the MSCI World Index. Portfolios have been rebalanced quarterly and returns are on equal-weighted total return basis. Periods of expansion and recession are defined by the NBER. The analysis has been run until May 2010 (early recovery)—one year after the end of the last recession in June 2009.
Note: t-stats are calculated using two samples t-test (Welch’s t-test) with unequal sample sizes and unequal variances
January 31, 1990, through July 31, 2018
Source: MSCI, Thomson Reuters Datastream and AB

Note: table shows the annualized return from factor portfolios in different VIX cycles from January 1990 to July 2018. Factor returns are defined as the long-short return of the top-bottom quintile from the 500 largest stocks in the MSCI World Index. Portfolios have been rebalanced quarterly and returns are on equal-weighted total return basis. VIX cycles are defined using the three-month moving average of the index.
Note: t-stats are calculated using two samples t-test (Welch’s t-test) with unequal sample sizes and unequal variances
January 31, 1990, through July 31, 2018
Source: MSCI, Thomson Reuters Datastream and AB

Note: table shows the annualized return from factor portfolios in different policy uncertainty cycles from January 1997 to July 2018. Factor returns are defined as the long-short return of the top-bottom quintile from the 500 largest stocks in the MSCI World Index. Portfolios have been rebalanced quarterly and returns are on equal-weighted total return basis. The cycles are defined using the Global Economic Policy Uncertainty Index from www.policyucertainty.com, taking a three-month moving average.
Note: t-stats are calculated using two samples t-test (Welch’s t-test) with unequal sample sizes and unequal variances
January 31, 1990, through July 31, 2018
Source: MSCI; "Global Economic Policy Uncertainty Index," Economic Policy Uncertainty, http://www.policyuncertainty.com; Thomson Reuters Datastream and AB

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