Factors have delivered similar risk-adjusted performance as asset classes, but may perform worse going forward

Transcription

1 Are Factors Better and More Diversifying Than Asset Classes? (For the most part, we don t think so) February 2018 By: Maneesh Shanbhag, CFA Executive Summary - Factor investing promises outperformance at low cost. But to add value in a portfolio, it must deliver positive risk-adjusted returns and with low correlation to existing holdings. - Historically, pure factor exposures have earned similar risk-adjusted returns to buying and holding plain vanilla asset classes like stocks and bonds. Therefore, factors such as Value and Momentum should only be valuable in a portfolio if they are diversifying to these asset classes. - Most factors are not uniquely diversifying in a portfolio. Many have a bias to perform best at the same time as bonds or commodities, like low volatility and momentum strategies. - Instead of using factors in a portfolio, leveraging plain vanilla asset class exposure delivers the same portfolio improvements more reliably. Introduction Factoring investing is one of the hottest topics in investing today and one that we have studied and written about extensively 1. The promise is outperformance at low cost. Massive amounts of capital market data across stocks, bonds, commodities, currencies and other assets has been mined to show that rules such as buy cheap stocks (value) or buy past winners (momentum) have delivered risk-adjusted outperformance over time. There is now a so called zoo of factors, most of which are not underpinned by a structural or behavioral reason why they should deliver positive returns in the future. In fact, many factors have already been discredited through out-of-sample tests and real-world experience. And for the most tried and tested factors, like Value and Momentum, returns do not come easily as they can go through long periods of underperformance (10+ years). This is no different than owning a single asset class like stocks or bonds. We aim to answer two questions in this thought piece: 1. Should factors deliver higher risk-adjusted returns than asset classes? 2. Are factors uniquely diversifying in a portfolio of multiple asset classes? If factor returns can be expected to be better than those of asset classes and are more diversifying, then investors should hold a lot of exposure to these sources of return. If, on the other hand, factor returns are no better than asset classes, on a risk-adjusted basis, and also highly correlated, then they are at best substitutes for asset class exposure. If this were the case, one could simply leverage up the similar asset class, with lower complexity, and achieve the same portfolio effect as owning the factor exposure. In this paper we will explore these questions, specifically focused on the equity factors of Value, Momentum, Quality and Low Volatility. Factors have delivered similar risk-adjusted performance as asset classes, but may perform worse going forward Factor risk-adjusted returns similar to asset classes All sources of return come with risk. Asset classes, like stocks and bonds, deliver a return in exchange for taking risk. Over time, they have delivered excess returns over cash in approximately 6 of annual periods. This translates into Sharpe ratios of around 0.3. Should factor strategies be better? The few 1 1

2 Excess Return Drawdown fundamentally sound factors, like Value and Momentum, are based on behavioral biases, structural constraints, or risk transfers. There should be compensation over the long-term for assuming these risks. At the same time, factor strategies are quantitative, rules-based and transparent. This makes them relatively easy to implement, though not as reliably as buying and holding an asset class. We know that anything that is easily copied in investing should not produce exceptional risk-adjusted returns since markets are competitive and zero sum. Therefore, it is logical that, at best, factor strategies should deliver similar riskadjusted returns as asset classes. We use factor return histories from the Ken French data library to empirically show factor performance beside asset classes. Different methods for constructing factor portfolios will show slightly different results but we think this dataset is representative for the most common strategies. The table below summarizes the historical returns of 3 asset classes with histories back to 1970 beside the performance of the 4 most popular equity factors Value, Momentum, Quality, and Low Volatility. All returns have been adjusted to 1 volatility. We can see that the factors delivered similar Sharpe ratios (risk-adjusted return) as the asset classes, mostly in a range from Asset Classes Factor Premia S&P 500 Treasuries Gold Value Momentum Quality Low Volatility Return 3.8% 4.4% 1.9% 3.7% 4.6% 3.9% 3. Volatility 10.1% 10.5% 9.8% 10.3% 10.1% 10.1% 10.2% Sharpe Ratio Source: Ken French Data Library, Bloomberg, Greenline Partners analysis. The risk with factors is that their results will be materially worse than the historical data show due to potential crowding. Some have discussed why this is not the case. We think the lack of consistency of factor returns, as we will show below, is enough to keep from crowding out returns entirely. But we also think it is only prudent and reasonable to expect the return premium from these strategies to be lower going forward as billions of dollars are now exploiting them. Factor drawdowns similar to those of asset classes Another way to show similar risk-adjusted performance of factors and asset classes is by looking at their historical drawdowns. The chart below compares the S&P 500 to the Value premium (both adjusted to 1 volatility). We can see both suffer 30+% drawdowns. This same pattern is true for all factors and asset classes and is characteristic of a return stream with a Sharpe ratio around % -1-15% -2-25% -3-35% -4-45% -5 Factors have similar downside risk to asset classes Equities Value Source: Ken French Data Library, Bloomberg, Greenline Partners analysis. Data from Jan 1970-Sept

3 Excess Return over Cash (annualized) In addition to drawdowns, we look at longer periods. All factors can go through many years of consecutive underperformance, just like asset classes. Below we compare the rolling 10-year returns of equities and the Value premium. We can see that both return streams have experienced multiple 10+ year periods without earning a return. Most investors are well aware of the lost decade for the S&P 500 from Investors are less aware of the lost decade for Value from 2008-present as we can see from the yellow line. 2 Factors have long periods of underperformance, like asset classes 15% 1 5% -5% years of underperformance S&P 500 Value Source: Ken French Data Library, Bloomberg, Greenline Partners analysis. Data from Jan 1927-Sept In terms of risk-adjusted returns, factors are at best similar to asset classes. Therefore, one should not want a portfolio of factors over simply holding assets as both deliver similar returns. On the other hand, if factor strategies are uniquely diversifying to traditional asset classes, then they could improve diversification in a portfolio. The chart above shows returns from Value are diversifying to equities. But this is not true for all factors and leads to our next question of whether equity factors, broadly speaking, are uniquely diversifying compared to other asset classes, like bonds and commodities. Most factors deliver returns at similar times as traditional assets like bonds and commodities A source of return is useful in a portfolio if it is diversifying and/or can improve returns. One could lever up any diversifying return stream if they want to increase risk-adjusted returns, whether that return stream is an asset class or a factor strategy. Factor strategies have been statistically uncorrelated to each other and asset classes. The table below shows the correlations of Value, Momentum, Quality, and Low Volatility factors to each other based on data from January 1970-Dec We can see the average cross correlation is near zero. But this does not mean they are fundamentally uncorrelated to asset classes and therefore to most portfolios. Correlation Value Momentum Quality Low Vol Value 1.00 Momentum Quality Low Vol Source: Ken French Data Library. Data from Jan 1970-Dec Statistical correlations are unstable and not reliable for portfolio construction as all investors experienced most acutely in As is true with asset classes, the correlations of factor strategies to each other and 3

4 Rolling 3yr Correlation to asset classes fluctuates wildly. Below is the rolling 3-year correlation for equity Momentum to the S&P 500. While the average correlation is slightly below 0, it fluctuates from -0.8 to almost +0.8 over time Correlation of Momentum to equities is unstable Average = Source: Ken French Data Library, Bloomberg. Data from Jan 1970-Sept We think scenario analysis is more useful for understanding when factors should be expected to perform well versus poorly. We use the growth/inflation framework here to assess similarities between factor returns and assets classes to see whether there is diversification power or not. Sector tilts explain much of the environmental bias in equity factor returns As we have discussed in past writings, asset class performance is reliable in different economic environments of rising/falling Growth and Inflation. That is, stocks tend to perform best when growth expectations are rising while bonds tend to perform poorly in these same environments. The appendix contains a refresher on this topic. We think factor strategy returns are also biased to perform in certain environments for similar fundamental reasons. Some of the biases in factors are desired. For example, when Value outperforms the broad market during a drawdown by avoiding the most overvalued securities, this is desired. This pattern of performing well during the drawdown but trailing during the prior run up in prices shows up as a bias to falling Growth (i.e. a recession) since this is the most common cause of stock prices falling. Another reason for bias is persistent sector over- and underweights relative to broad indices. These sector tilts on the other hand are generally not desired because they should not be return enhancing. For example, in 2016 we wrote a paper on how low volatility strategies behaved like bonds because of their overweight to defensive sectors like Utilities and Food Staples. 2 This overweight makes sense since sectors like Utilities and Food Staples have less earnings volatility and therefore lower price volatility as well. This persistent sector tilt causes Low Volatility strategies to outperform when rates are falling and underperform when rates are rising. The chart below shows the sector over- and underweights of this strategy relative to the market cap weighted S&P 500 index since We can see that a Low Volatility index is persistently overweight defensive sectors. 2 Low Volatility Investing Is Just a Bet on Falling Interest Rates, May

5 Excess Return over Historical Avg Sector weight relative to index Low Volatility strategy always overweights bond-like sectors Cyclical Defensive Commodity Cyclical sectors include Discretionary, Financials, Industrials, and Technology. Defensive sectors include Healthcare, Staples, Utilities and Telecom. Commodity sectors include Energy and Materials. Source: Bloomberg. Low Volatility index based on the SPLV ETF. Data from Jan 2011-Dec As another example, Value strategies tend to overweight businesses with large asset bases and therefore low price-to-book ratios like financials and energy companies. And businesses like energy companies tend to have high earnings volatility and therefore the market prices them with lower price-to-earnings ratios. Both energy and financials sectors tend to perform well with rising rates (rising growth with the former, and rising inflation with the later) resulting in a bias for Value strategies. The charts below show the environments when each of these factors outperformed or underperformed the broad equity market. The first chart below splits history into periods of Rising versus Falling economic growth. See how all strategies outperformed together when Growth conditions were weakening. This bias is diversifying to equities and partly explained by these strategies avoiding the expensive and low quality securities that tend to perform best in a bubble. 25% 2 15% 1 5% -5% -1-15% All factors benefited from falling growth Diversifying to equities Equities Value Premium Momentum Premium Quality Premium Low Volatility Premium -2 Rising Growth Falling Growth Source: Ken French Data Library, Greenline Partners analysis. Data from Jan 1970-Dec

6 Excess Return over Historical Avg The next chart shows performance for the same factors, with history divided into periods of Rising versus Falling inflation. Here, all strategies except Value, outperformed when inflation was falling. Value was neutral to shifts in inflation and most diversifying to equities. This means Momentum, Quality, and Low Volatility are correlated to equities when inflation is the biggest driver of markets. Said another way, these same strategies have a bond-like nature and perform best with falling rates. For Low Volatility and Quality strategies, this should be less of a surprise since these strategies tend to overweight bond-like, defensive sectors. 8% 6% 4% Only value factor is diversifying to equities in inflation Only Value is Diversifying to equities 2% -2% -4% Equities Value Premium Momentum Premium Quality Premium Low Volatility Premium -6% -8% -1 Rising Inflation Falling Inflation Source: Ken French Data Library, Greenline Partners analysis. Data from Jul 1970-Dec Moving average momentum strategies: different strategy, but still similar to other assets over the long run Momentum is different from the other factors in that it is not sector tilts that drive when it performs best but rather the type of market environment, which is also connected to Growth and Inflation. As the name implies, Momentum aims to ride market trends and side step sustained losses in out-of-favor securities, sectors, and markets. But it is also well known that these strategies consistently miss market turning points. To illustrate, we look at a moving average strategy applied to the US equities. This is admittedly different from the Momentum strategy applied to individual equities, but we show that these rules-based strategies, like the ones we analyzed above, also have economic biases that make them correlated to holding asset classes. We know equities tend to drawdown during either falling Growth (recessionary environment) or rising Inflation environments. An asset that performs best in both of these environments is gold. To see how similar both are, we simulate a 10-month moving average strategy applied to the S&P 500 where the strategy sits in cash when the index is below this moving average. The chart below shows the rolling 10- year outperformance for a 10-month moving average strategy applied to the S&P 500 compared to gold. Both strategies deliver performance at the same time, over longer periods. 6

7 Drawdown Total Return Excess Return (annualized) 25% Momentum performs best when gold does 2 15% 1 5% -5% -1-15% Gold Source: Bloomberg, Greenline Partners analysis. Data from Jul 1928-Dec Momentum We also compare two portfolios using either a moving average strategy or gold. The first is the S&P 500 that moves into cash when the total return index falls below its 10-month moving average. And the second is a mix of 7 S&P 500 and 3 gold to target the same risk and return characteristics. We can see both portfolios have similar long-term performance. But the trend following strategy performed best since 2000 when there were multiple large market drawdowns but underperformed for the 25 years prior when there were fewer such events S&P 500 S&P + Gold 10 MMA Overlay Historical Performance S&P 500 S&P + Gold 10 MMA Overlay Source: Bloomberg, Greenline Partners analysis. Data from Jan 1970-Dec

8 Excess Return (rolling 12-month) S&P 500 S&P + Gold S&P w/ 10 MMA Return 10.5% 10.4% 10.7% Volatility 15.1% % Sharpe Ratio Return 11.4% % Volatility 15.7% 12.9% 12.4% Sharpe Ratio Return 9.7% 8.8% 10.9% Volatility 14.4% 11.1% 10.2% Sharpe Ratio Both strategies look better than buying and holding the S&P 500 historically. But this period by period analysis makes us wonder whether the current popularity of momentum strategies is overly influenced by recent performance. Expect multi-factor strategies to be no better than single asset classes Single factor strategies can go through long stretches of underperformance as we have shown. Combining multiple, uncorrelated factors into a single portfolio is being done with the aim of delivering returns more consistently. But we have shown that many of these strategies have similar biases to economic environments. Momentum, Low Volatility, and Quality strategies have all performed best when bonds do well. Combining all of these factors together should create a portfolio that behaves like Treasury bonds. To test this hypothesis, we simulated a multi-factor portfolio, equally risk weighted to Value, Momentum, Quality, and Low Volatility equity strategies and targeting 1 portfolio volatility. The chart below shows the rolling 12-month returns for this portfolio compared to long duration Treasury bonds (roughly the same volatility). We can see that the multi-factor returns and Treasuries have a similar return pattern going back 25 years Multi-factor strategies perform in-line with Treasuries Exclude this anomaly (dot.com bust outperformance) in comparison Multi-factor Long-term Treasuries Source: Ken French Data Library, Greenline Partners analysis. 8

9 This chart only goes back to 1993 in order to highlight the Dot.com period where most of the multi-factor outperformance was delivered. But the high correlation to Treasury bonds was true going back to the 1970 s as well. If we exclude from the comparison, the return and risk statistics for the multi-factor strategy are almost identical to that of Treasury bonds, while being highly correlated as shown in the table below. The examples of simplicity beating complexity abound (excl ) Multi-factor strategy (simulation) Long maturity Treasury Bonds Excess Return 4.6% 4.7% Volatility 9.5% 8.9% Sharpe Ratio Source: Ken French Data Library, Bloomberg, Greenline Partners analysis. Remember, diversification has declining benefits with the addition of each additional return stream. As few as 3-5 lowly correlated return streams maximize the risk-adjusted returns for a portfolio. We would therefore not expect factor strategies to materially improve risk-adjusted returns in an already diversified portfolio since they are not fundamentally diversifying to the primary asset classes like bonds and commodities. Also note the frequent 20+% drawdowns for the multi-factor portfolio. Given the amount of leverage used (approximately 7:1 in our simulation), these periods could have led to blow up and irrecoverable loss. We have found some existing products that exhibit this high correlation to buying and holding asset classes. As the assets going into these leveraged multi-factor strategies increases, we think the risk of blow ups also increases. Conclusions The key to factor investing is identifying sources of lasting positive risk-adjusted return, with low correlation to traditional asset classes. Most factors are discovered through data mining and will not pass these tests. Even the most sound ones, like Value and Momentum, we think offer only small opportunity for improvement in an already diversified portfolio. We showed that the most popular equity factors of Value, Momentum, Quality and Low Volatility, delivered risk-adjusted returns only similar to that of asset classes, not better. And importantly, these returns were delivered at similar times as diversifying asset classes such as bonds and commodities like gold. For example, investors who have been positioning their portfolios for rising interest rates, may be unknowingly adding a bond-like exposure by overweighting some of these factor exposures. Investors would avoid most losses by keeping only two facts about markets in mind: 1) Markets are zero-sum. For every winner there is a loser. That means not everyone can win. Investing in easily copied strategies, adopted by the masses, cannot provide easy outperformance by a wide margin. 2) Making money consistently is the holy grail but one that has never been discovered. Any time such a feat is promised, investors should run the other way. Having a sound framework for diversification and staying disciplined with investing in quality assets at an appropriate valuation are about the best one can do to improve consistency. Knowing what you own is critical to investing success. The abstraction of factors makes them more difficult to understand and see their role in the context of a total portfolio. Scenario analysis is a powerful tool in assessing any investment, whether an individual security or asset class. From our view, most factor exposures should be of little benefit to an already diversified portfolio of stocks, bonds, and inflationprotecting assets. In our goal of separating signal from noise, most factor talk sounds like pure noise. 9

10 Excess Return over Cash Excess Return over Cash Appendix: Background on economic environments driven by Growth and Inflation Economic environments are defined by changes in growth and inflation conditions. These are the primary risk factors that drive asset classes. And shifts or surprises in what markets are discounting for these factors define the economic environments. That is, when inflation is surprising up we call it a Rising Inflation environment. Today, when inflation is priced in to be around 2% over the next decade, and were it to come in at 3% instead, while not high by historical standards, it would be high relative to what asset classes had discounted and therefore would be a Rising Inflation environment as assets would reprice (stocks down, commodities up) to reflect this. The same goes for Growth, where a scenario of economic growth coming in below what markets have priced in would be considered one of Falling Growth. The core asset classes of equities, interest rates (Treasury bonds), and commodities have clear and logical biases to perform well in some environments and poorly in other environments. The charts below summarize the environments in which assets tend to perform well or poorly. A positive bar means the asset tends to outperform in that environment. For example, commodities tend to do well when inflation is rising above what markets were discounting. Similarly, bonds tend to perform poorly in that same environment, as we see in the right-hand chart. 2 15% 1 Growth Environments Equities Rates Commodities 3 2 Inflation Environments 5% 1-5% -1-15% Rising Growth Falling Growth -3 Rising Inflation Falling Inflation Equities is the S&P 500. Rates is the Barclays US Treasury Bond Index. Commodities is the S&P/GSCI until Dec 1990 and the Bloomberg Commodity Index thereafter. Periods of Rising and Falling Growth and Inflation are defined using Greenline Partners current understanding of markets and macroeconomics. Source: Bloomberg, Federal Reserve, Robert Schiller data, Greenline Partners analysis. Data from Jan 1970-Oct Environmental bias analysis is a replacement for using unstable measures such as correlation to assess whether two assets or strategies are diversifying to each other. The environments in which an asset performs well or poorly is a more fundamental way to understand the relationship between assets. What we see with asset classes is logical. We expect equities to outperform bonds when growth is rising and vice versa, as shown in the chart on the left. We expect commodities to outperform stocks and bonds when inflation is rising and vice versa, as shown in the chart on the above right. We want to apply the same scenario analysis to better understand the linkage between equity factor strategies, which we go into next. Scenario analysis and looking at the environmental bias of an asset or strategy are fundamental ways to understand the correlation between assets. Statistical correlations are unstable and do not explain the relationships between assets. These environmental biases explain the linkage between assets and the macroeconomics that drives them. 10

11 DISCLOSURES: The information contained herein is the property of Greenline Partners, LLC and is circulated for information and educational purposes only. There is no consideration given for the specific investment needs, objectives or tolerances of any of the recipients. Additionally, Greenline's actual investment positions may, and often will, vary from its conclusions discussed herein based upon any number of factors, such as client investment restrictions, portfolio rebalancing and transaction costs, among others. Reasonable people may disagree about a variety of factors discussed in this document, including, but not limited to, key macroeconomic factors, the types of investments expected to perform well during periods in which certain key economic factors are dominant, risk factors and various assumptions used. Recipients should consult their own advisors, including tax advisors, before making any investment decision. This report is not an offer to sell or the solicitation of an offer to buy the securities or instruments mentioned. No part of this document or its subject matter may be reproduced, disseminated, or disclosed without the prior written approval of Greenline Partners, LLC. HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS: Projected or hypothetical performance is intended to show only an expected range of possible investment outcomes based on historical average returns and standard deviation of each investment type contained in the investment plan recommended by Greenline Partners, but does not take into consideration the effect of taxes, changing risk profiles, or future investment decisions. Projected and hypothetical performance does not represent actual accounts or actual trades and may not reflect the effect of material economic and market factors. The actual transaction costs in Client accounts may be different. Actual investors with Greenline Partners may experience different results from any hypothetical results shown. There is a potential for loss, as well as gain, which is not reflected in the hypothetical information portrayed. The hypothetical performance results shown do not represent the results of actual trading using client assets but were achieved by means of the retroactive application of a model designed with the benefit of hindsight. Investors should carefully review the additional information presented by Greenline Partners as part of any hypothetical comparison. Unless otherwise indicated, results shown are gross of fees, include the reinvestment of interest, gains and losses, and do not take into account the reduction of any management fees, costs, commissions, or other expenses that may be associated with the implementation of a portfolio. The individuals involved in the preparation of this document receive compensation based on a variety of factors, including individual and firm performance. Additional information about Greenline Partners, LLC, including fees charged, is located in Greenline s Form ADV, which is accessible at Greenline s CRD Number is Past performance is not a guarantee of future results. FORWARD LOOKING STATEMENTS AND OPINION: Certain statements contained in this presentation may be forward-looking statements that, by their nature, involve a number of risks, uncertainties and assumptions that could cause actual results or events to differ materially, potentially in an adverse manner, from those expressed or implied herein. Forward-looking statements contained in this presentation that reference past trends or activities should not be taken as a representation that such trends or activities will necessarily continue in the future. Greenline Partners undertakes no obligation to update or revise any forward looking statements, whether as a result of new information, future events or otherwise. Opinions offered herein constitute the judgment of Greenline Partners, as of the date of this presentation, and are subject to change. You should not place undue reliance on forward-looking statements or opinions, as each is based on assumptions, all of which are difficult to predict and many of which are beyond the control of Greenline Partners. Greenline Partners believes that the information provided herein is reliable; however, it does not warrant its accuracy or completeness. The information contained in this document is current as of the date shown. Greenline Partners has no obligation to provide the recipient of this document with updated information or analysis contained herein. Additional information regarding the analysis shown is available upon request, except where the proprietary nature precludes such dissemination. Information presented herein (including market data and statistical information) has been obtained from various sources which Greenline Partners, LLC considers to be reliable including but not limited to the Federal Reserve, International Monetary Fund, National Bureau of Economic Research, Organization for Economic Co-operation and Development, United Nations, US Department of Commerce, World Bureau of Metal Statistics as well as information companies such as BBA Libor Limited, Bloomberg Finance, L.P., Global Financial Data, Inc., Hedge Fund Research Inc., Markit Economics Limited, Moody's Analytics, Inc., MSCI, Standard and Poor's, and Thomson Reuters. However, Greenline Partners, LLC makes no representation as to, and accepts no responsibility or liability whatsoever for, the accuracy or completeness of such information. Greenline Partners, LLC has no obligation to provide recipients hereof with updates or changes to such data. All projections, valuations and statistical analyses are provided to assist the recipient in the evaluation of the matters described herein. They may be based on subjective assessments and assumptions and may use one among alternative methodologies that produce different results and, to the extent that they are based on historical information, they should not be relied upon as an accurate prediction of future performance. This material is not intended to represent a comprehensive overview of any law, rule or regulation and does not constitute investment, legal, or tax advice. You should exercise discretion before relying on the statements and information contained herein because such statements and information do not take into consideration the particular circumstances or needs of any specific client. Accordingly, Greenline Partners, LLC makes no representation or warranty as to the accuracy of the information contained herein and shall have no liability, howsoever arising to the maximum extent permitted by law, for any loss or damage, direct or indirect, arising from the use of this information by you or any third party relying on this presentation. 11