Description
SIMPLYSTATED
April 2015
Calling the Turns:
Why Market Timing Is So Hard
by Philip Lawton, Ph.D., CFA
The stock market is cyclical, and any investor who
market may have mispriced it. Similarly, by comparing
could call the turns—buying when prices are lowest
the market’s current cap-weighted price/earnings to
and selling when they are highest—would make a
the long-term average, analysts can judge whether,
fortune. But only a fortuneteller would say, “The peak
and by how much, the market as a whole is misvalued.
will arrive next Tuesday morning,” and like the rest of
us, she’d be guessing (and almost certainly guessing
But DCF analysis, P/E multiples, and other theoretically
wrong). The facts are clear—most actively managed
sound valuation measures cannot tell us how much
equity mutual funds underperform the market.
Even more misvalued the market will get nor can they worse, most individual investors underperform the explain the wild swings we’ve experienced in the two funds they invest in: their money-weighted returns— equity market cycles in the last 15 years.4 As Figure 1 the rates of return they actually earn—are illustrates, the stock market seems to go too far in preponderantly lower than the time-weighted returns both directions—up and down—and the amplitude of that the funds report (Hsu and Viswanathan, 2015). these movements cannot be satisfactorily explained 1 within the cool analytical framework of the standard Investment managers’ underperformance relative to model. their benchmark generally results from unfortunate decisions in one or more of three areas: market timing, Empirical research has established that sooner or later sector weighting or factor exposures, and stock stock prices revert toward their long-term averages. selection.2 The practical reality is that timing is There is also strong evidence that the value premium integral to all aspects of investment decision making. is mean reverting (Hsu, 2014). If the market rises or Allocating funds across sectors, setting factor falls to an extreme level despite a natural tendency to exposure targets, and identifying attractively priced self-correct, then countervailing forces must be at stocks all have an element of market timing. Mutual work. fund investors’ underperformance relative to the active funds they hold is simply the result of their own One hypothesis is that many market participants view inopportune purchases and redemptions. mental effort as an avoidable transaction cost. Disinclined to gather and analyze solid information If it’s all in the timing, why is it so hard to get the timing about the stocks that interest them, they are carried right? along by the crowd, trading on momentum and noise. The Market in Theory In addition to this kind of indolence or inertia, Daniel The standard model of investment management Kahneman (2011) and others have described a number equips portfolio managers and traders reasonably well of cognitive biases and patterns of emotionally to determine if an individual stock is fairly valued. charged behavior that affect individuals’ choices under Most investment professionals use discounted cash uncertainty—the selling and buying of securities being flow (DCF) analysis to estimate a stock’s inherent an excellent example of such an activity.
They include worth, and so to judge whether it is mispriced. With overconfidence and the illusion of control,5 mental a handle on a stock’s true value, an investment accounts, availability cascades, loss aversion, professional can also observe the extent to which the overreacting to news, and herding, among others. 3 © Research Affiliates, LLC . April 2015 SIMPLYSTATED Figure 1. S&P 500 Index Monthly Price Levels (January 2000–March 2015) 2100 S&P 500 Index Closing Price 1800 1500 1200 900 600 S&P 500 Closing Price Average Source: Research Affiliates using data from FactSet. The field of neuroeconomics has also contributed much “Predominantly,” Smith (2009, p. 157) writes, “both to our understanding of the autonomous brain, the old economists and psychologists are reluctant to allow lizard brain, which leaps to conclusions while our that naïve and unsophisticated agents can achieve conscious minds are still deliberating. The process of socially optimal ends without a comprehensive reasoning, it appears, is often rationalizing choices we understanding of the whole, as well as their individual may not know we’ve already made (Zweig, 2007).
The parts, implemented by deliberate action.” But in Smith’s insights into decision making that we’ve gained from account, personal exchanges gave rise to impersonal behavioral finance and neuroeconomics go a long way markets which serve to facilitate the specialization that toward explaining investors’ actions and reactions when creates wealth. Smith demonstrates that in a diverse the outcome is in doubt. set of circumstances, such as the airlines’ response to Beyond Behavioral Finance Given the behavioral view of investors’ practical decision-making processes, two promising ways of thinking about how markets really work are Vernon Smith’s concept of ecological rationality and Andrew Lo’s adaptive markets hypothesis. trust games, the interaction of individuals with partial Smith, the experimental economist who shared the 2002 Nobel Prize in Economic Science with Kahneman, distinguishes between constructivist and ecological rationality. The former involves the intentional use of reason to analyze the given and to advocate a course of action.
(The standard model of investment management is a sterling product of constructivist rationality.) Ecological rationality, in contrast, emerges in institutions, such as markets, through human interaction rather than by human design. © Research Affiliates, LLC deregulation, FCC spectrum auctions, and a variety of knowledge leads in due time to near-equilibrium solutions. Lo (2004, 2005) invokes pertinent findings of behavioral finance and neuroeconomics in his effort to develop a more realistic framework than the standard model. He also introduces key concepts from evolutionary psychology—competition, adaptation, and natural selection—and reintroduces the classic notion of bounded or approximate rationality proposed by Herbert Simon. Simon’s idea crucially takes into account “the simplifications the choosing organism may deliberately introduce into its model of the situation in order to bring the model within the range of its computing capacity” (Simon, 1955, p.
100). For example, attempting to maximize the expected payoff from an . April 2015 SIMPLYSTATED action is a computationally intensive exercise. One of the simplifications Simon describes is “satisficing,” more modestly requiring only that the benefit exceed some threshold. Thanks to Kahneman, Smith, Lo, and many others, our understanding of the ways investors think and markets function is richer and more sensible than it was when the best minds of the time constructed the standard investment model. But these theoretical advances still don’t solve the active investor’s conundrum: when to buy and sell in strongly trending markets. Blue Sky Solutions So, where will the solution come from? Let’s think blue sky. Among the unfettered solutions that come to mind, one approach might be modeling the actions and reactions of distinct groups (Lo’s “species”) whose members generally employ specifiable decision rules, but are subject to social influences and cognitive biases. Alternately, the industry might train its immense technological firepower on the markets themselves in a search for deep structures or path-dependent vectors that signal a change in direction: technical analysis with Cray supercomputers. In either case, the analytical techniques that ultimately crack the code of market timing may originate in fields far removed from finance and economics—information theory, for example, or the study of complex networks. Recall that “Brownian Motion in the Stock Market,” an article written by the physicist M.F.M. Osborne (1959) and published in a nonfinancial journal, contributed to Endnotes 1. According to the SPIVA Scorecard compiled by S&P Dow Jones Indices, for periods ended December 31, 2014, 76.25% of actively managed U.S.
large-cap equity funds underperformed the S&P 500 for 3 years, 88.65% for 5 years, and 82.07% for 10 years. 2. For an approach to performance attribution analysis that isolates the impact of tactical asset allocation in factor investing (i.e., timing the cyclicality of risk premiums), see Hsu, Kalesnik, and Myers (2010) and Hsu and Shakernia (2013). 3. Cornell and Hsu (2015) hold that the investment professionals to whom end investors delegate decisionmaking authority use DCF analysis so prevalently that their discount models are likely both to drive prices and to determine the cross-section of expected returns. © Research Affiliates, LLC the random walk theory of prices (Bernstein 2005, p. 103, and Fox, 2009, pp. 64–67). And Back to Earth The stock market’s turning points, as well as the valuation peaks and troughs of individual stocks, increasingly appear to be driven more by mass psychology than by sober professional judgment based on disciplined valuation techniques. In fact, the active investor’s conundrum is such a challenge that many investors have chosen passive investing—simply removing timing decisions from their purview.
But there is strong evidence that the popularity of passive investing tied to prominent cap-weighted indices is actually associated with higher return correlations among stocks and, therefore, higher systematic equity market risk (Sullivan and Xiong, 2012). At this juncture, we must acknowledge that financial theory does not provide clear and timely trading signals. Calling the turns is hard because we don’t have a mechanics of mean reversion. Our best theories— including behavioral finance, neuroeconomics, experimental economics, and evolutionary psychology— do not enable us to foresee the sudden exogenous shock that will trigger a reversal, or to sense when a gradual change in investors’ attitudes will reach the tipping point. Not even the most skilled and experienced asset allocators can pinpoint in advance the onset of a reversal.
Most of us are well advised not to attempt market timing. The soundest plan is to choose a strategy that suits our investment objectives and risk tolerance— potentially including a disciplined smart beta strategy that systematically rebalances over time—and to stick with that choice for the long term. 4. 5. 6. Nor does the standard model account for the sheer volume of non-algorithmic stock market trades. The novelist Italo Svevo satirized the illusion of control when he described a fictional character’s apparently successful effort to regulate the stock exchange on behalf of a late friend’s family: “I don’t know anyone who has ever been able to tolerate similar exertion for fifty hours. Every shift in price I recorded, brooded over, and then (why not say it?) mentally urged shares forward, or held them back, as best suited me, or rather my poor friend.
Even my nights were sleepless.” (Svevo 2003, p. 388.) Lo (2004) gives examples of “species” in the economy, including pension funds, retail investors, market makers, and hedge fund managers. . April 2015 SIMPLYSTATED References Bernstein, Peter L. 2005. Capital Ideas: The Improbable Origins of Modern Wall Street. Hoboken, NJ: John Wiley & Sons. Lo, Andrew.
2004. “The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective.” Journal of Portfolio Management, vol. 30, no.
5 (30th Anniversary):15–29. Cornell, Bradford, and Jason Hsu. 2015. “The Self-Fulfilling Prophecy of Popular Asset Pricing Models,” Journal of Investment Management (forthcoming). ———.
2005. “Reconciling Efficient Markets with Behavioral Finance: The Adaptive Markets Hypothesis.” Journal of Investment Consulting, vol. 7, no.
2:21–44. Fox, Justin. 2009. The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street.
New York: HarperCollins. Osborne, M.F.M. 1959. “Brownian Motion in the Stock Market.” Operations Research, vol.
7, no. 2 (March/ April):145–173. Hsu, Jason. 2014.
“Value Investing: Smart Beta versus Style Indexes,” Journal of Index Investing, vol. 5, no. 1 (Summer):127-135. Simon, Herbert.
1955. “A Behavioral Model of Rational Choice.” Quarterly Journal of Economics, vol. 69, no.
1 (February):99–118. Hsu, Jason C., Vitali Kalesnik, and Brett W. Myers. 2010. “Performance Attribution: Measuring Dynamic Asset Allocation Skill.” Financial Analysts Journal, vol.
66, no. 6 (November/December):17–26. Smith, Vernon L. 2009.
Rationality in Economics: Constructivist and Ecological Forms. Cambridge: Cambridge University Press. Hsu, Jason C., and Omid Shakernia. 2013.
“A Framework for Examining Asset Allocation Alpha.” Journal of Index Investing, vol. 3, no. 4 (Spring):64–72. Hsu, Jason, and Vivek Viswanathan.
2015. “Woe Betide the Value Investor.” Research Affiliates (February). Kahneman, Daniel. 2011.
Thinking, Fast and Slow. New York: Farrar, Strauss, and Giroux. Sullivan, Rodney N., and James X. Xiong.
2012. “How Index Trading Increases Market Vulnerability.” Financial Analysts Journal, vol. 68, no.
2 (March/April):70–84. Svevo, Italo. 2003. Zeno’s Conscience.
Translated by William Weaver. New York: Vintage Books. Zweig, Jason. 2007.
Your Money and Your Brain: How the New Science of Neuroeconomics Can Help Make You Rich. New York: Simon & Schuster. ABOUT THE AUTHOR Philip Lawton is responsible for content marketing. Earlier in his career he was head of the Certificate In Investment Performance Measurement (CIPM®) program at CFA Institute; a vice president at State Street Investment Analytics, where he managed client service for the Independent Consultants Cooperative; a vice president at Citibank, where he was responsible for providing performance measurement reports to U.S.
master trust and custody clients; a second vice president and fixed income portfolio manager at The Travelers; and director of cash flow forecasting and liquidity management at Aetna Life & Casualty. Philip earned his bachelor’s, licentiate, and Ph.D. in philosophy in the French-speaking section of the Catholic University of Louvain, Belgium, and an MBA degree at Northeastern University. The material contained in this document is for information purposes only. This material is not intended as an offer or solicitation for the purchase or sale of any security or financial instrument, nor is it investment advice on any subject matter.
Research Affiliates, LLC and its related entities do not warrant the accuracy of the information provided herein, either expressed or implied, for any particular purpose. By accepting this document you agree to keep its contents confidential. No disclosure may be made to third parties regarding any information contained in this document without the prior permission of Research Affiliates, LLC. The trademarks Fundamental Index™, RAFI™, Research Affiliates Equity™ and the Research Affiliates™ trademark and corporate name and all related logos are the exclusive intellectual property of Research Affiliates, LLC and in some cases are registered trademarks in the U.S.
and other countries. Various features of the Fundamental Index™ methodology, including an accounting data-based non-capitalization data processing system and method for creating and weighting an index of securities, are protected by various patents, and patent-pending intellectual property of Research Affiliates, LLC. (See all applicable US Patents, Patent Publications, Patent Pending intellectual property and protected trademarks located at http:/ /www.researchaffiliates.com/Pages/legal.aspx#d, which are fully incorporated herein.) Any use of these trademarks, logos, patented or patent pending methodologies without the prior written permission of Research Affiliates, LLC, is expressly prohibited. Research Affiliates, LLC, reserves the right to take any and all necessary action to preserve all of its rights, title, and interest in and to these marks, patents or pending patents. The views and opinions expressed are those of the authors and not necessarily those of Research Affiliates, LLC.
The opinions are subject to change without notice. © Research Affiliates, LLC 620 Newport Center Drive, Suite 900 Newport Beach, California 92660 www.researchaffiliates.com .
Even more misvalued the market will get nor can they worse, most individual investors underperform the explain the wild swings we’ve experienced in the two funds they invest in: their money-weighted returns— equity market cycles in the last 15 years.4 As Figure 1 the rates of return they actually earn—are illustrates, the stock market seems to go too far in preponderantly lower than the time-weighted returns both directions—up and down—and the amplitude of that the funds report (Hsu and Viswanathan, 2015). these movements cannot be satisfactorily explained 1 within the cool analytical framework of the standard Investment managers’ underperformance relative to model. their benchmark generally results from unfortunate decisions in one or more of three areas: market timing, Empirical research has established that sooner or later sector weighting or factor exposures, and stock stock prices revert toward their long-term averages. selection.2 The practical reality is that timing is There is also strong evidence that the value premium integral to all aspects of investment decision making. is mean reverting (Hsu, 2014). If the market rises or Allocating funds across sectors, setting factor falls to an extreme level despite a natural tendency to exposure targets, and identifying attractively priced self-correct, then countervailing forces must be at stocks all have an element of market timing. Mutual work. fund investors’ underperformance relative to the active funds they hold is simply the result of their own One hypothesis is that many market participants view inopportune purchases and redemptions. mental effort as an avoidable transaction cost. Disinclined to gather and analyze solid information If it’s all in the timing, why is it so hard to get the timing about the stocks that interest them, they are carried right? along by the crowd, trading on momentum and noise. The Market in Theory In addition to this kind of indolence or inertia, Daniel The standard model of investment management Kahneman (2011) and others have described a number equips portfolio managers and traders reasonably well of cognitive biases and patterns of emotionally to determine if an individual stock is fairly valued. charged behavior that affect individuals’ choices under Most investment professionals use discounted cash uncertainty—the selling and buying of securities being flow (DCF) analysis to estimate a stock’s inherent an excellent example of such an activity.
They include worth, and so to judge whether it is mispriced. With overconfidence and the illusion of control,5 mental a handle on a stock’s true value, an investment accounts, availability cascades, loss aversion, professional can also observe the extent to which the overreacting to news, and herding, among others. 3 © Research Affiliates, LLC . April 2015 SIMPLYSTATED Figure 1. S&P 500 Index Monthly Price Levels (January 2000–March 2015) 2100 S&P 500 Index Closing Price 1800 1500 1200 900 600 S&P 500 Closing Price Average Source: Research Affiliates using data from FactSet. The field of neuroeconomics has also contributed much “Predominantly,” Smith (2009, p. 157) writes, “both to our understanding of the autonomous brain, the old economists and psychologists are reluctant to allow lizard brain, which leaps to conclusions while our that naïve and unsophisticated agents can achieve conscious minds are still deliberating. The process of socially optimal ends without a comprehensive reasoning, it appears, is often rationalizing choices we understanding of the whole, as well as their individual may not know we’ve already made (Zweig, 2007).
The parts, implemented by deliberate action.” But in Smith’s insights into decision making that we’ve gained from account, personal exchanges gave rise to impersonal behavioral finance and neuroeconomics go a long way markets which serve to facilitate the specialization that toward explaining investors’ actions and reactions when creates wealth. Smith demonstrates that in a diverse the outcome is in doubt. set of circumstances, such as the airlines’ response to Beyond Behavioral Finance Given the behavioral view of investors’ practical decision-making processes, two promising ways of thinking about how markets really work are Vernon Smith’s concept of ecological rationality and Andrew Lo’s adaptive markets hypothesis. trust games, the interaction of individuals with partial Smith, the experimental economist who shared the 2002 Nobel Prize in Economic Science with Kahneman, distinguishes between constructivist and ecological rationality. The former involves the intentional use of reason to analyze the given and to advocate a course of action.
(The standard model of investment management is a sterling product of constructivist rationality.) Ecological rationality, in contrast, emerges in institutions, such as markets, through human interaction rather than by human design. © Research Affiliates, LLC deregulation, FCC spectrum auctions, and a variety of knowledge leads in due time to near-equilibrium solutions. Lo (2004, 2005) invokes pertinent findings of behavioral finance and neuroeconomics in his effort to develop a more realistic framework than the standard model. He also introduces key concepts from evolutionary psychology—competition, adaptation, and natural selection—and reintroduces the classic notion of bounded or approximate rationality proposed by Herbert Simon. Simon’s idea crucially takes into account “the simplifications the choosing organism may deliberately introduce into its model of the situation in order to bring the model within the range of its computing capacity” (Simon, 1955, p.
100). For example, attempting to maximize the expected payoff from an . April 2015 SIMPLYSTATED action is a computationally intensive exercise. One of the simplifications Simon describes is “satisficing,” more modestly requiring only that the benefit exceed some threshold. Thanks to Kahneman, Smith, Lo, and many others, our understanding of the ways investors think and markets function is richer and more sensible than it was when the best minds of the time constructed the standard investment model. But these theoretical advances still don’t solve the active investor’s conundrum: when to buy and sell in strongly trending markets. Blue Sky Solutions So, where will the solution come from? Let’s think blue sky. Among the unfettered solutions that come to mind, one approach might be modeling the actions and reactions of distinct groups (Lo’s “species”) whose members generally employ specifiable decision rules, but are subject to social influences and cognitive biases. Alternately, the industry might train its immense technological firepower on the markets themselves in a search for deep structures or path-dependent vectors that signal a change in direction: technical analysis with Cray supercomputers. In either case, the analytical techniques that ultimately crack the code of market timing may originate in fields far removed from finance and economics—information theory, for example, or the study of complex networks. Recall that “Brownian Motion in the Stock Market,” an article written by the physicist M.F.M. Osborne (1959) and published in a nonfinancial journal, contributed to Endnotes 1. According to the SPIVA Scorecard compiled by S&P Dow Jones Indices, for periods ended December 31, 2014, 76.25% of actively managed U.S.
large-cap equity funds underperformed the S&P 500 for 3 years, 88.65% for 5 years, and 82.07% for 10 years. 2. For an approach to performance attribution analysis that isolates the impact of tactical asset allocation in factor investing (i.e., timing the cyclicality of risk premiums), see Hsu, Kalesnik, and Myers (2010) and Hsu and Shakernia (2013). 3. Cornell and Hsu (2015) hold that the investment professionals to whom end investors delegate decisionmaking authority use DCF analysis so prevalently that their discount models are likely both to drive prices and to determine the cross-section of expected returns. © Research Affiliates, LLC the random walk theory of prices (Bernstein 2005, p. 103, and Fox, 2009, pp. 64–67). And Back to Earth The stock market’s turning points, as well as the valuation peaks and troughs of individual stocks, increasingly appear to be driven more by mass psychology than by sober professional judgment based on disciplined valuation techniques. In fact, the active investor’s conundrum is such a challenge that many investors have chosen passive investing—simply removing timing decisions from their purview.
But there is strong evidence that the popularity of passive investing tied to prominent cap-weighted indices is actually associated with higher return correlations among stocks and, therefore, higher systematic equity market risk (Sullivan and Xiong, 2012). At this juncture, we must acknowledge that financial theory does not provide clear and timely trading signals. Calling the turns is hard because we don’t have a mechanics of mean reversion. Our best theories— including behavioral finance, neuroeconomics, experimental economics, and evolutionary psychology— do not enable us to foresee the sudden exogenous shock that will trigger a reversal, or to sense when a gradual change in investors’ attitudes will reach the tipping point. Not even the most skilled and experienced asset allocators can pinpoint in advance the onset of a reversal.
Most of us are well advised not to attempt market timing. The soundest plan is to choose a strategy that suits our investment objectives and risk tolerance— potentially including a disciplined smart beta strategy that systematically rebalances over time—and to stick with that choice for the long term. 4. 5. 6. Nor does the standard model account for the sheer volume of non-algorithmic stock market trades. The novelist Italo Svevo satirized the illusion of control when he described a fictional character’s apparently successful effort to regulate the stock exchange on behalf of a late friend’s family: “I don’t know anyone who has ever been able to tolerate similar exertion for fifty hours. Every shift in price I recorded, brooded over, and then (why not say it?) mentally urged shares forward, or held them back, as best suited me, or rather my poor friend.
Even my nights were sleepless.” (Svevo 2003, p. 388.) Lo (2004) gives examples of “species” in the economy, including pension funds, retail investors, market makers, and hedge fund managers. . April 2015 SIMPLYSTATED References Bernstein, Peter L. 2005. Capital Ideas: The Improbable Origins of Modern Wall Street. Hoboken, NJ: John Wiley & Sons. Lo, Andrew.
2004. “The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective.” Journal of Portfolio Management, vol. 30, no.
5 (30th Anniversary):15–29. Cornell, Bradford, and Jason Hsu. 2015. “The Self-Fulfilling Prophecy of Popular Asset Pricing Models,” Journal of Investment Management (forthcoming). ———.
2005. “Reconciling Efficient Markets with Behavioral Finance: The Adaptive Markets Hypothesis.” Journal of Investment Consulting, vol. 7, no.
2:21–44. Fox, Justin. 2009. The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street.
New York: HarperCollins. Osborne, M.F.M. 1959. “Brownian Motion in the Stock Market.” Operations Research, vol.
7, no. 2 (March/ April):145–173. Hsu, Jason. 2014.
“Value Investing: Smart Beta versus Style Indexes,” Journal of Index Investing, vol. 5, no. 1 (Summer):127-135. Simon, Herbert.
1955. “A Behavioral Model of Rational Choice.” Quarterly Journal of Economics, vol. 69, no.
1 (February):99–118. Hsu, Jason C., Vitali Kalesnik, and Brett W. Myers. 2010. “Performance Attribution: Measuring Dynamic Asset Allocation Skill.” Financial Analysts Journal, vol.
66, no. 6 (November/December):17–26. Smith, Vernon L. 2009.
Rationality in Economics: Constructivist and Ecological Forms. Cambridge: Cambridge University Press. Hsu, Jason C., and Omid Shakernia. 2013.
“A Framework for Examining Asset Allocation Alpha.” Journal of Index Investing, vol. 3, no. 4 (Spring):64–72. Hsu, Jason, and Vivek Viswanathan.
2015. “Woe Betide the Value Investor.” Research Affiliates (February). Kahneman, Daniel. 2011.
Thinking, Fast and Slow. New York: Farrar, Strauss, and Giroux. Sullivan, Rodney N., and James X. Xiong.
2012. “How Index Trading Increases Market Vulnerability.” Financial Analysts Journal, vol. 68, no.
2 (March/April):70–84. Svevo, Italo. 2003. Zeno’s Conscience.
Translated by William Weaver. New York: Vintage Books. Zweig, Jason. 2007.
Your Money and Your Brain: How the New Science of Neuroeconomics Can Help Make You Rich. New York: Simon & Schuster. ABOUT THE AUTHOR Philip Lawton is responsible for content marketing. Earlier in his career he was head of the Certificate In Investment Performance Measurement (CIPM®) program at CFA Institute; a vice president at State Street Investment Analytics, where he managed client service for the Independent Consultants Cooperative; a vice president at Citibank, where he was responsible for providing performance measurement reports to U.S.
master trust and custody clients; a second vice president and fixed income portfolio manager at The Travelers; and director of cash flow forecasting and liquidity management at Aetna Life & Casualty. Philip earned his bachelor’s, licentiate, and Ph.D. in philosophy in the French-speaking section of the Catholic University of Louvain, Belgium, and an MBA degree at Northeastern University. The material contained in this document is for information purposes only. This material is not intended as an offer or solicitation for the purchase or sale of any security or financial instrument, nor is it investment advice on any subject matter.
Research Affiliates, LLC and its related entities do not warrant the accuracy of the information provided herein, either expressed or implied, for any particular purpose. By accepting this document you agree to keep its contents confidential. No disclosure may be made to third parties regarding any information contained in this document without the prior permission of Research Affiliates, LLC. The trademarks Fundamental Index™, RAFI™, Research Affiliates Equity™ and the Research Affiliates™ trademark and corporate name and all related logos are the exclusive intellectual property of Research Affiliates, LLC and in some cases are registered trademarks in the U.S.
and other countries. Various features of the Fundamental Index™ methodology, including an accounting data-based non-capitalization data processing system and method for creating and weighting an index of securities, are protected by various patents, and patent-pending intellectual property of Research Affiliates, LLC. (See all applicable US Patents, Patent Publications, Patent Pending intellectual property and protected trademarks located at http:/ /www.researchaffiliates.com/Pages/legal.aspx#d, which are fully incorporated herein.) Any use of these trademarks, logos, patented or patent pending methodologies without the prior written permission of Research Affiliates, LLC, is expressly prohibited. Research Affiliates, LLC, reserves the right to take any and all necessary action to preserve all of its rights, title, and interest in and to these marks, patents or pending patents. The views and opinions expressed are those of the authors and not necessarily those of Research Affiliates, LLC.
The opinions are subject to change without notice. © Research Affiliates, LLC 620 Newport Center Drive, Suite 900 Newport Beach, California 92660 www.researchaffiliates.com .
