This page includes sophisticated financial research and educational information that is intended only for investment professionals and other knowledgeable institutional investors who are capable of evaluating investment risks and making their own investment decisions. It should not be interpreted as investment advice or as a recommendation of any particular security, strategy or investment product.
Factors are one of the building blocks of a systematic approach. They define the characteristics of attractive and unattractive stocks and provide a consistent, rules-based implementation of an investment philosophy. How does it work? In a long-only portfolio, a systematic factor strategy will overweight stocks that rank highly on a certain factor and underweight stocks that rank poorly on that factor. Using factors allows us to explain exactly why the portfolio is positioned the way it is and what the drivers of return are—every time.
Value investing is one of the best-known and most-studied approaches to outperforming the broader market over the long term. Equity valuations can be quantified by the ratio of a fundamental anchor—like book value, earnings or cash flows—over price. There are many ways to measure the valuation of a stock—we find that using a combination of measures yields the most robust results.
Sources: AQR and Kenneth R. French Data Library. Portfolios from Kenneth R. French Data Library formed based on book-to-market; quintiles are equal-weighted; returns are excess of cash. Returns sourced from “Portfolios Formed on Book-to-Market.” See Kenneth R. French Data Library for further details. These are not the returns of an actual portfolio AQR manages and are for illustrative purposes only. Past performance is not a guarantee of future performance.
Simply put, momentum is the idea that assets that have recently outperformed will tend to do better than assets that have recently underperformed. This tendency has been documented in at least as many asset classes as value and over even longer histories. A simple yet common measure of momentum is the last 12-months price return of an asset. Importantly, the returns of the momentum premium have tended to be negatively correlated to those of the value premium—which means they may offer investors great diversification benefits.
Source: AQR and Kenneth R. French Data Library. Portfolios from Kenneth R. French Data Library formed based on 12-month momentum, skipping most recent month; quintiles are equal-weighted; returns are excess of cash. Returns sourced from “10 Portfolios Formed on Momentum.” See Kenneth R. French Data Library for further details. These are not the returns of an actual portfolio AQR manages and are for illustrative purposes only. Past performance is not a guarantee of future performance.
Defensive stocks tend to be low-risk, stable or safe. As with most factors, there is more than one way to characterize a defensive company—from purely fundamental measures such as profitability and general quality to statistical measures such as low beta and low volatility. We find that both may help identify attractive stocks. For example, a defensive portfolio is likely to go long or overweight stocks that rank high on earnings quality and profitability and rank low on beta and volatility.
Source: AQR and CRSP/Compustat data. Portfolios formed based on gross profits-to-assets using all stocks in the CRSP universe; quintiles are equal-weighted; returns are excess of cash. These are not the returns of an actual portfolio AQR manages and are for illustrative purposes only. Past performance is not a guarantee of future performance.
Combining Factors into a Multi-Factor Portfolio
The combination of multiple factors has been shown to be more effective than any one individually. But how you combine them matters.
For example, how would you build a portfolio that seeks to capture both value and momentum premia? The easiest approach would be to separately buy the stocks that look most attractive from a value perspective and also buy the stocks that look most attractive from a momentum perspective. This is essentially constructing an aggregate portfolio by mixing stand-alone-style portfolios.
We believe there’s a better way. Theoretically and empirically, we find that buying stocks that look attractive from both value and momentum perspectives is more effective than considering each factor separately. In other words, applying investment themes in an integrated manner may be better than mixing individual styles in an “a la carte” manner.
Factor Diversification Versus Timing
Factors may offer long-term sources of returns, but that doesn’t mean they make money at the time. Can investors do better—can factors be successfully timed?
Factors (like many other sources of return) can become cheap or expensive compared to their histories. It might seem intuitive to test the efficacy of factor timing by overweighting a factor when it’s cheap and underweighting when it’s expensive.
Theoretically and empirically, we find it’s not so easy. Factor timing, especially contrarian factor timing, is far from an efficient way to make returns. Why? First, there is only a weak predictive relationship between how cheap a factor might seem and its future returns. Second, we find the returns from contrarian factor timing are meaningfully correlated to the returns from the value factor itself. What that means for factor investors is there’s only limited benefit (if any at all) for portfolios that already have a value tilt or an allocation to the value factor.
Instead, we find that strategically diversifying across multiple factors to be more effective, not just in U.S. stocks, but in other geographies and asset classes too. Diversification across multiple factors doesn’t rule out timing entirely, but it raises the bar more than most investors might realize.
Factor timing is likely even harder than market timing.
September 23, 2014
Momentum is the phenomenon that securities that have performed well relative to peers (winners) on average continue to outperform, and securities that have performed relatively poorly (losers) tend to continue to underperform.Read more
November 5, 2015
Value investing has been a part of the investment lexicon for at least the better part of a century, yet confusion about it remains.Read more
July 1, 2012
This paper analyzes the intuition behind defensive equity. We then analyze the empirical evidence, construction and performance of defensive equity portfolios, and discuss the possible explanations for its historical outperformance.Read more
March 1, 2013
Combining successful investing styles to magnify their effects represents a new paradigm in active equity-portfolio management. Core Equities integrates value, momentum and profitability styles to offer a more persistent, systematic approach.Read more
June 30, 2016
We contrast two common approaches to long-only style investing: the “portfolio mix” and the “integrated portfolio.” Our results suggest that long-only factor or smart beta investors should consider integrating styles in portfolio construction.Read more
June 1, 2016
Often the first question after an initial discussion of factors is “Okay, what’s the current outlook?” And the common answer, “The same as usual,” is often unsatisfying.Read more
March 7, 2017
The increasing popularity of factor investing has led to valuation concerns among some contrarian-minded investors and fears of imminent mean-reversion and underperformance.Read more
In this quick video primer, we cover the basics of how a disciplined, repeatable approach can potentially harvest returns from stock markets.Read more
From white papers to data sets, we’ve compiled our most relevant advanced thinking on systematic equities.Read more
This information is for informational purposes only and not intended to, and does not relate specifically to any investment strategy or product that AQR offers. It is being provided merely to provide a framework to assist in the implementation of an investor’s own analysis and an investor’s own view on the topic discussed herein.
Past performance is not a guarantee of future results. Diversification does not eliminate the risk of experiencing investment loss. Broad-based securities indices are unmanaged and are not subject to fees and expenses typically associated with managed accounts or investment funds. Investments cannot be made directly in an index.
HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS, SOME OF WHICH, BUT NOT ALL, ARE DESCRIBED HEREIN. NO REPRESENTATION IS BEING MADE THAT ANY FUND OR ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN HEREIN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS SUBSEQUENTLY REALIZED BY ANY PARTICULAR TRADING PROGRAM. ONE OF THE LIMITATIONS OF HYPOTHETICAL PERFORMANCE RESULTS IS THAT THEY ARE GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. IN ADDITION, HYPOTHETICAL TRADING DOES NOT INVOLVE FINANCIAL RISK, AND NO HYPOTHETICAL TRADING RECORD CAN COMPLETELY ACCOUNT FOR THE IMPACT OF FINANCIAL RISK IN ACTUAL TRADING. FOR EXAMPLE, THE ABILITY TO WITHSTAND LOSSES OR TO ADHERE TO A PARTICULAR TRADING PROGRAM IN SPITE OF TRADING LOSSES ARE MATERIAL POINTS THAT CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS IN GENERAL OR TO THE IMPLEMENTATION OF ANY SPECIFIC TRADING PROGRAM WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF HYPOTHETICAL PERFORMANCE RESULTS, ALL OF WHICH CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS. The hypothetical performance results contained herein represent the application of the quantitative models as currently in effect on the date first written above and there can be no assurance that the models will remain the same in the future or that an application of the current models in the future will produce similar results because the relevant market and economic conditions that prevailed during the hypothetical performance period will not necessarily recur. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results, all of which can adversely affect actual trading results. Discounting factors may be applied to reduce suspected anomalies. This backtest’s return, for this period, may vary depending on the date it is run.