past is not prologue: how to deliver value for money asset ... · common valuation metrics imply...

Asset Class Expected ReturnsWhy Are Expected Mainstream Asset Returns Paltry?

Past is Not Prologue: How to Deliver Value for Money

Via Robust Sources of Return

John M. WestPartner, Research Affiliates

Agenda

• Expected Returns for the Next Decade

• Pitfalls of chasing returns in funds and stocks

• Potential benefits of evidence-based strategies

• Q&A

US Market Returns, 1871-2019

Inflation

Equity 60/40 Bonds Cash CPI Equity 60/40 Bonds Cash

9.12% 7.73% 5.00% 3.51% 2.05% 6.93% 5.57% 2.89% 1.43%

Annualized Nominal Return Annualized Real Return

US Mainstream Assets Have Historically Provided Solid Returns

Source: Research Affiliates, LLC, based on data from the Robert Shiller Database.

Can we expect these high returns to persist in the future?

-4%

0%

4%

8%

12%

16%

-4%

0%

4%

8%

12%

16%

1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 2015 2018

Subsequent10-YearNominalReturn

StartingYield

U.S. Aggregate

Starting Yield Subsequent 10-Year Nominal Return

Correlation = 93%

30-Year Return = 5.9%

Source: Research Affiliates, LLC, based on data from Barclays. The yield-to-worst and total returns are of the Barclays Aggregate Index. As of December 31, 2019.

Bonds: Future Returns Follow Starting Yields

Source: Research Affiliates, LLC, based on data from Bloomberg and Shiller. The index and inception date is the S&P 500 (January 1926). Earnings yield

is computed as the inverse of the CAPE ratio. For more information, please visit http://www.researchaffiliates.com/en_us/asset-allocation.html. As of

December 31, 2019.

Equities: Future Returns Follow Starting Earnings Yields

-5%

0%

5%

10%

15%

20%

25%

1.6%

3.1%

6.3%

12.5%

25.0%

1926 1937 1948 1959 1970 1981 1992 2003 2014

Subsequent10-YearNominalReturn

StartingYield

U.S.

Starting Yield 10-Year Subsequent Return

Correlation = 74%

Source: Research Affiliates, LLC, based on data from Robert Shiller and the Federal Reserve Economic Data (FRED). US Valuation Metrics referenced above are presented as of the first date that data is available. As of December 31, 2019.

Common Valuation Metrics Imply Overvaluation

-80%

-40%

0%

40%

80%

120%

160%

200%

1871 1895 1919 1943 1967 1991 2015

CurrentValue as

Comparedto FullPeriod

Average

Current Levels of U.S. Valuation Metrics vs. Their Long-Term Averages

Shiller P/E Market Cap to GDP Tobin's Q Hussman's PE

Source: Research Affiliates, LLC, based on data from MSCI Inc., Bloomberg, and Barclays. Please see important information at the end of this presentation regarding simulated data. Return expectations as of December 31, 2019.

Comparing the Current Equity Forecast to History

60/40 portfolios are represented as 60% core equity index and 40% Treasury 5-7 Year bond index for each specific country. For the US, the Barclays Aggregate is used in lieu of the 5-7 Year Treasury. Source: Research Affiliates, LLC, based on data from Ibbotson, Shiller, Bloomberg, FactSet, MSCI Inc., and Barclays. Please see important information at the end of this presentation regarding simulated data. As of December 31, 2019.

Mainstream Asset Classes Offer Less Than Most Investors Expect

United States Germany

JapanUnited Kingdom United States

Germany

Japan

United Kingdom

Global 60 / 40

0%

2%

4%

6%

8%

10%

0% 5% 10% 15% 20% 25%

ExpectedReturns

(UnhedgedUSD)

Volatility

Mainstream Stocks and Bonds

Bonds Equities Portfolios

2.3%

5.0% 4.8%

5.9%

3.6%

0%

8%

UnitedStates

Germany Japan UnitedKingdom

Global60/40

ExpectedReturns

(UnhedgedUSD)

Mainstream 60/40 Portfolios*

Return Chasing Can Exacerbate the Return Gap

* Morningstar Research shows 43% of core equity funds at end-2005 no longer exist at end-2015. Source: Research Affiliates, LLC, based on Lipper data

for US large capitalization mutual funds. Mutual fund returns are net of fees. Chart has been recreated but based on Burton G. Malkiel, 2005, “Reflections on the Efficient Market Hypothesis: 30 Years Later,” The Financial Review, p. 40.

Active Management: Excess Returns Are Difficult to Achieve

149 153

212198

176

125

54 56

-3% or less -2% to -3%

-1% to -2%

0 to -1% 0 to 1% 1% to 2% 2% to 3% 3% ormore

Numberof Funds

Excess Returns of Surviving U.S. Large Cap Mutual Funds(Dec 2008–Dec 2018)

There were ~1000 funds that failed, and probably fell into these bins

These results span the ~57%* of funds that survived the decade, and misses the many hundreds of funds that failed!

Underperformers46%

Outperformers11%

Market Equivalent43%

Source: Research Affiliates, using data from the CRSP Mutual Funds Database and Morningstar Direct, 1/1991 – 6/2013. The buy-and-hold return is the

geometric average return over the sample period. The dollar-weighted return is the category IRR (inclusive of all category mutual funds weighted by

their total assets).

Hsu, Myers, and Whitby, “Timing Poorly: A Guide to Generating Poor Returns While Investing in Successful Strategies,” Journal of Portfolio Management (Winter 2016).

Most Fund Investors Are Trend Chasers!

Source: Research Affiliates, LLC, based on data from FactSet as of 9/30/2019. Market cap for countries represents the sum of the market caps for their constituents in the Morningstar Global Markets Index. Market caps for Facebook, Apple, Netflix, Microsoft, Amazon, & Google are excluded from the United States. The total market capitalization for the United States is $25.8 trillion, which is cut off at $6.0 trillion in this graph for scaling purposes.

How Expensive are FANMAG (Facebook, Apple, Netflix, Microsoft, Amazon, & Google)?

Source: Research Affiliates, LLC, based on data from FactSet as of 9/30/2019. Market cap for sectors represents the sum of the market caps for their constituents in the Russell 1000 Index. Market caps for Facebook, Apple, Netflix, Microsoft, Amazon, & Google are excluded from the Technology and Consumer Cyclical sector.

How Expensive are FANMAG (Facebook, Apple, Netflix, Microsoft, Amazon, & Google)?

Source: Research Affiliates, LLC, based on data from Worldscope/Datastream. Based on research published in, “The winner’s curse: Too Big to Succeed?” by Arnott and Wu, 2012. “Global top dog” refers to the largest company in simulated cap-weighted index each year by market capitalization. Please see important information at the end of this presentation regarding simulated data.

“Top Dogs” Vanish Because They Underperform!

How Do “Top Dogs” Impact Index Performance?

“Top Dog” Portfolios Underperform the Market

• Source: Research Affiliates based on Data from Worldscope and Datastream. Data from 1/1/1980-6/30/2019. “Global top dog” refers to the largest company in the index each year by market capitalization. “Global top ten” refers to the top ten companies in a simulated cap-weighted index each year by market capitalization. Please see important information at the end of this presentation regarding simulated data.

Can Evidence-based Investing Solve the Return Gap?

Factor Investing Within Asset ClassesEvery investor should ask five questions before investing in a strategy:

1.Why does the strategy work?

2.Has the strategy worked over long and varying time periods net of changes in valuation?

3.Does the strategy produce similar results across different regions?

4.Does the strategy produce similar results across slightly different definitions (e.g., P/B vs. P/S)?

5.Is the strategy investable in the real world net of costs?

Why Does The Factor Work?Factor Factor Premium Rationale

ValuePerformance chasers under-own value securities (preferring fast-growing glamour stocks instead).

Low VolatilityPreference for gambling leads investors to over-own high volatility securities as “lottery tickets.”

Momentum Uninformed investors are slow to react to new information about a company.

QualityInvestors are drawn to the glamour of empire-building companies and underappreciate conservative capital allocators with wide economic moats.

SizeAll of the factor premiums above tend to work better in small capitalization markets because these markets tend to be less efficient and experience larger pricing errors.

Is The Strategy Consistent Across Regions?

• Source: Research Affiliates, LLC, using data from CRSP/Compustat and Worldscope/Datastream as of 6/30/2019. Strategies are categorized as working if their Sharpe ratios exceed the Sharpe ratio of the appropriate cap-weighted index. Data begins in 1968 (US), 1989 (Developed ex US, Developed), and 2002 (Global, EM). Factor strategies shown are simulated versions of the RAFI Single Factor indices. Please see important information at the end of this presentation regarding simulated data.

Strategy Sharpe Ratios

US Developed exUS Developed Emerging GlobalRegions That

Worked

0.53 0.43 0.61 0.70 0.63

✔ ✔ ✔ ✔ ✔0.57 0.48 0.66 0.70 0.78

✔ ✔ ✔ ✔ ✔0.50 0.40 0.59 0.59 0.66

✔ ✔ ✔ ✔ ✔0.46 0.32 0.48 0.54 0.52

✔ ✔ ✔ ✔ ✔0.49 0.36 0.52 N/A N/A

✔ ✔ ✔Cap 0.35 0.16 0.32 0.47 0.46

5 out of 5

5 out of 5

5 out of 5

5 out of 5

3 out of 3

Value

Low Volatility

Quality

Momentum

Size

Is The Strategy Consistent Across Definitions?

• Source: Research Affiliates, LLC, using data from CRSP/Compustat and Datascope/Worldstream as of 6/30/2019. Annualized trading costs are estimated as the market impact of transactions, assuming $10B in AUM. For descriptions of the strategies shown, please see https://interactive.researchaffiliates.com/smart-beta.html. Strategy returns and characteristics are simulated. Please see important information at the end of this presentation regarding simulated data.

Strategy Definitions - Developed Market

Value Low Volatility Quality Momentum

Price to Sales Volatility Operating Profitability Standard MomentumPrice to Dividends Country Beta ROA Idiosyncratic MomentumPrice to Book Global Beta ROE Fresh MomentumPrice to Cash Flow 3-Factor Beta Low Asset Growth

Low Book Growth

Total 4 out of 4 4 out of 4 5 out of 5 3 out of 3

Definitions That Didn’t Work:

Definitions That Worked:

Is The Factor Investable Net of Costs?


1989 - 2019 Historical Annualized Excess Returns –Developed Markets


2.44%

1.68%1.92%

2.17%

2.50%

1.49%1.72%

1.56%

1.91%

0.62%

2.31%

0.32%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

All Smart BetaStrategies

MultifactorStrategies

Value Strategies Low VoilatilityStrategies

QualityStrategies

MomentumStrategies

Gross of Trading Costs Net of Trading Costs

Smart Beta Takeaways

• A handful of factor/smart beta equity strategies are “robust.”

• It is reasonable to project that smart beta and factor returns will be highly cyclical.

• For a successful investor experience, establish beliefs and “buy the range.”

Hobbled by Benchmarks

• Start with a very diversified asset class opportunity set.

• Apply the substantial body of research on robust return drivers, typically applied in long short, in a long-only setting to liquid asset classes.

Asset Class Opportunity Set

Based on results from “Hobbled by Benchmarks” by Mike Aked, Rob Arnott, Omid Shakernia, and Jonathan Treussard, published in The Journal of Portfolio Management Multi-Asset Strategies Special Edition (December 2017).

Asset Type Asset Classes

Stocks (7) US Large, US Large Value, US Large Growth, US Small, Dev ex-US, Emerging Markets, REITs

Bonds (9)BarCap Aggregate, Long Treasuries, Intermediate Credit, Global Agg ex-US, TIPS, High Yield, Leveraged Loans, EM Bonds, and EM Local Bonds

Strategy Benchmarks

Based on results from “Tactical and Tax Aware GTAA” by Michael Aked, Robert Arnott, Paul Bouchey, Tianchuan Li and Omid Shakernia. Journal of Portfolio Management 2018.

• Conservative – equal weight all bond asset classes and REITs

• Moderate – equal weight all 16 asset classes

• Aggressive – Equal Weight all Stock asset classes plus High-yield bonds, EM bonds and EM Local Currency Bonds

Factors Rationale Signal

Momentum Investors initially underreact to surprises

Trailing 1-year excess return with banding

Value (Price Reversal)

Consistent with long horizon mean reversion, prices will revert toward normalized valuation ranges

Negative of the trailing five-year annualized return

Carry The expected return if valuation is held constant

Yield plus growth, growth is specific to each asset class

Factor Investing Across Asset Classes

Based on results from “Tactical and Tax Aware GTAA” by Michael Aked, Robert Arnott, Paul Bouchey, Tianchuan Li and Omid Shakernia. Journal of Portfolio Management 2018.

1980 – 2017 Results

Sources: Research Affiliates LLC, and Parametric Portfolio Associates, LLC, using data from Bloomberg, Robert Shiller’s Online Data, Moody’s and REIT.com.

Conservative Moderate AggressiveBenchmark Strategy Benchmark Strategy Benchmark Strategy

Pretax Total Return 9.05% 9.69% 10.10% 11.37% 11.06% 12.52%

Volatility 5.97% 6.18% 8.63% 9.20% 12.85% 13.07%

Sharpe Ratio 0.78 0.85 0.66 0.76 0.52 0.62

1980 – 2017 After-Tax Results

Sources: Research Affiliates LLC, and Parametric Portfolio Associates, LLC, using data from Bloomberg, Robert Shiller’s Online Data, Moody’s and REIT.com.

0.64%

1.27%1.46%

0.84%

1.46%

1.96%

0.78%

1.35%

2.02%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

Conservative Moderate Aggressive

Pre-Tax Excess Return After Tax Excess return Postliquidation Excess Returns

Applying factor lessons within equities and across asset classes• A rules-based framework distills decades of learnings.

• Allows for efficient implementation and customization in pursuit of multiple structural sources of return.

• These practices result in a reliable investment approach and a clear framework for coaching clients, building trust, and managing expectations.

Key Takeaways and Questions

Key Takeaways

• The link between starting valuations and subsequent returns is powerful.

• Chasing returns can be very costly. High valuations can go higher, but not indefinitely.

• With proper advisor guidance, evidence suggests 1% excess returns can be harvested within and across asset classes using systematic strategies.

Questions?

Thank you!

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past is not prologue: how to deliver value for money asset ... · common valuation metrics imply...

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