DFA Commentary

Sailing With The Tides

Embarking on a financial plan is like sailing around the world. The voyage won’t always go to plan, and there’ll be rough seas. But the odds of reaching your destination increase greatly if you are prepared, flexible, patient, and well-advised.

A mistake many inexperienced sailors make is not having a plan at all. They embark without a clear sense of their destination. And once they do decide, they often find themselves lost at sea in the wrong boat with inadequate provisions. 

Likewise, in planning an investment journey, you need to decide on your goal. A first step might be to consider whether the goal is realistic and achievable. For instance, while you may long to retire in the south of France, you may not be prepared to sacrifice your needs today to satisfy that distant desire. 

Once you are set on a realistic destination, you need to ensure you have the right portfolio to get you there. Have you planned for multiple contingencies? What degree of “bad weather” can your plan withstand along the way? 

Key to a successful voyage is a good navigator. A trusted advisor is like that, regularly taking coordinates and making adjustments, if necessary. If your circumstances change, the advisor may suggest you re-plot your course.

 As with the weather at sea, markets can be unpredictable. A sudden squall can whip up waves of volatility, tides can shift, and strong currents can threaten to blow you off course. Like a seasoned sailor, an experienced advisor will work with the conditions. 

Once the storm passes, you can pick up speed again. Just as a sturdy vessel will help you withstand most conditions at sea, a well-diversified portfolio can act as a bulwark against the sometimes tempestuous conditions in markets. 

Circumnavigating the globe is not exciting every day. Patience is required with local customs and paperwork as you pull into different ports. Likewise, a lack of attention to costs and taxes is the enemy of many a long-term financial plan. 

Distractions can also send investors, like sailors, off course. In the face of “hot” investment trends, it takes discipline not to veer from your chosen plan. Like the sirens of Greek mythology, media pundits can also be diverting, tempting you to change tack and act on news that is already priced in to markets.

A lack of flexibility is another impediment to a successful investment journey. If it doesn’t look as though you’ll make your destination in time, you may have to extend your voyage, take a different route to get there, or even moderate your goal. 

The important point is that you become comfortable with the idea that uncertainty is inherent to the investment journey, just as it is with any sea voyage. That is why preparation and planning are so critical. While you can’t control every outcome, you can be prepared for the range of possibilities and understand that you have clear choices if things don’t go according to plan.

If you can’t live with the volatility, you can change your plan. If the goal looks unachievable, you can lower your sights. If it doesn’t look as if you’ll arrive on time, you can extend your journey. 

Of course, not everyone’s journey is the same. Neither is everyone’s destination. We take different routes to different places, and we meet a range of challenges and opportunities along the way. 

But for all of us, it’s critical that we are prepared for our journeys in the right vessel, keep our destinations in mind, stick with the plans, and have a trusted navigator to chart our courses and keep us on target. 

Lessons For The Next Crisis

It will soon be the 10-year anniversary of when, in early October 2007, the S&P 500 Index hit what was its highest point before losing more than half its value over the next year and a half during the global financial crisis. Over the coming weeks and months, as other anniversaries of major crisis-related events pass (for example, 10 years since the bank run on Northern Rock or 10 years since the collapse of Lehman Brothers), there will likely be a steady stream of retrospectives on what happened as well as opinions on how the environment today may be similar or different from the period leading up to the crisis. It is difficult to draw useful conclusions based on such observations; financial markets have a habit of behaving unpredictably in the short run. There are, however, important lessons that investors might be well-served to remember: Capital markets have rewarded investors over the long term, and having an investment approach you can stick with—especially during tough times—may better prepare you for the next crisis and its aftermath.


In 2008, the stock market dropped in value by almost half. Being a decade removed from the crisis may make it easier to take the past in stride. The eventual rebound and subsequent years of double-digit gains have also likely helped in this regard. While the events of the crisis were unfolding, however, a future of this sort looked anything but certain. Headlines such as “Worst Crisis Since ’30s, With No End Yet in Sight,”1 “Markets in Disarray as Lending Locks Up,”2 and “For Stocks, Worst Single-Day Drop in Two Decades”3 were common front page news. Reading the news, opening up quarterly statements, or going online to check an account balance were, for many, stomach-churning experiences.

While being an investor today (or during any period, for that matter), is by no means a worry-free experience, the feelings of panic and dread felt by many during the financial crisis were distinctly acute. Many investors reacted emotionally to these developments. In the heat of the moment, some decided it was more than they could stomach, so they sold out of stocks. On the other hand, many who were able to stay the course and stick to their approach recovered from the crisis and benefited from the subsequent rebound in markets.

It is important to remember that this crisis and the subsequent recovery in financial markets was not the first time in history that periods of substantial volatility have occurred. Exhibit 1 helps illustrate this point. The exhibit shows the performance of a balanced investment strategy following several crises, including the bankruptcy of Lehman Brothers in September of 2008, which took place in the middle of the financial crisis. Each event is labeled with the month and year that it occurred or peaked.

Although a globally diversified balanced investment strategy invested at the time of each event would have suffered losses immediately following most of these events, financial markets did recover, as can be seen by the three- and five-year cumulative returns shown in the exhibit. In advance of such periods of discomfort, having a long-term perspective, appropriate diversification, and an asset allocation that aligns with their risk tolerance and goals can help investors remain disciplined enough to ride out the storm. A financial advisor can play a critical role in helping to work through these issues and in counseling investors when things look their darkest.


In the mind of some investors, there is always a “crisis of the day” or potential major event looming that could mean the beginning of the next drop in markets. As we know, predicting future events correctly, or how the market will react to future events, is a difficult exercise. It is important to understand, however, that market volatility is a part of investing. To enjoy the benefit of higher potential returns, investors must be willing to accept increased uncertainty. A key part of a good long-term investment experience is being able to stay with your investment philosophy, even during tough times. A well-thought-out, transparent investment approach can help people be better prepared to face uncertainty and may improve their ability to stick with their plan and ultimately capture the long-term returns of capital markets.

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Quit Monkeying Around!

In the world of investment management there is an oft-discussed idea that blindfolded monkeys throwing darts at pages of stock listings can select portfolios that will do just as well, if not better, than both the market and the average portfolio constructed by professional money managers. If this is true, why might it be the case?


Exhibit 1 shows the components of the Russell 3000 Index (regarded as a good proxy for the US stock market) as of December 31, 2016. Each stock in the index is represented by a box, and the size of each box represents the stock’s market capitalization (share price multiplied by shares outstanding) or “market cap” in the index. For example, Apple (AAPL) is the largest box since it has the largest market cap in the index. The boxes get smaller as you move from the top to the bottom of the exhibit, from larger stocks to smaller stocks. The boxes are also color coded based on their market cap and whether they are value or growth stocks. Value stocks have lower relative prices (as measured by, for instance the price-to-book ratio) and growth stocks tend to have higher relative prices. In the exhibit, blue represents large cap value stocks (LV), green is large cap growth stocks (LG), gray is small cap value stocks (SV), and yellow is small cap growth stocks (SG).

For the purposes of this analogy you can think of Exhibit 1 as a proxy for the overall stock market and therefore similar to a portfolio that, in aggregate, professional money managers hold in their competition with their simian challengers. Because for every investor holding an overweight to a stock (relative to its market cap weighting) there must also be an investor underweight that same stock, this means that, in aggregate, the average dollar invested holds a portfolio that looks like the overall market.

Exhibit 2, on the other hand, represents the dart board the monkeys are using to play their game. Here, the boxes represent the same stocks shown in Exhibit 1, but instead of weighting each company by market cap, the companies are weighted equally. For example, in this case, Apple’s box is the same size as every other company in the index regardless of its market cap. If one were to pin up pages of newspaper stock listings to throw darts at, Exhibit 2 would be much more representative of what the target would look like.

When looking at Exhibits 1 and 2, the significant differences between the two are clear. In Exhibit 1, the surface area is dominated by large value and large growth (blue and green) stocks. In Exhibit 2, however, small cap value stocks dominate (gray). Why does this matter? Research has shown that, historically over time, small company stocks have had excess returns relative to large company stocks. Research has also shown that, historically over time, value (or low relative price) stocks have had excess returns relative to growth (or high relative price) stocks. Because Exhibit 2 has a greater proportion of its surface area dedicated to small cap value stocks, it is more likely that a portfolio of stocks selected at random by throwing darts would end up being tilted towards stocks which research has shown to have had higher returns when compared to the market.


This does not mean, however, that haphazardly selecting stocks by the toss of a dart is an efficient or reliable way to invest. For one thing, it ignores the complexities that arise in competitive markets.

Consider as an example something seemingly as straightforward as a strategy that holds every stock in the Russell 3000 Index at an equal weight (the equivalent of buying the whole dart board in Exhibit 2). In order to maintain an equal weight in all 3,000 securities, an investor would have to rebalance frequently, buying shares of companies that have gone down in price and selling shares that have gone up. This is because as prices change, so will each individual holding’s respective weight in the portfolio. By not considering whether or not these frequent trades add value over and above the costs they generate, investors are opening themselves up to a potentially less than desirable outcome.

Instead, if there are well-known relationships that explain differences in expected returns across stocks, using a systematic and purposeful approach that takes into consideration real-world constraints is more likely to increase your chances for investment success. Considerations for such an approach include things like: understanding the drivers of returns and how to best design a portfolio to capture them, what a sufficient level of diversification is, how to appropriately rebalance, and last but not least, how to manage the costs associated with pursuing such a strategy.


Finally, the importance of having an asset allocation well-suited for your objectives and risk tolerance, as well as being able to remain focused on the long term, cannot be overemphasized. Even well-constructed portfolios pursuing higher expected returns will have periods of disappointing results. A financial advisor can help an investor decide on an appropriate asset allocation, stay the course during periods of disappointing results, and carefully weigh the considerations mentioned above to help investors decide if a given investment strategy is the right one for them.


So what insights can investors glean from this analysis? First, by tilting a portfolio towards sources of higher expected returns, investors can potentially outperform the market without needing to outguess market prices. Second, implementation and patience are paramount. If one is going to pursue higher expected returns, it is important to do so in a cost-effective manner and to stay focused on the long term.

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A Vote For Small Cap Stocks

In the days immediately following the recent US presidential election, US small company stocks experienced higher returns than US large company stocks. This example helps illustrate how the dimensions of expected returns can appear quickly, unpredictably, and with large magnitude.

Average returns for US small company stocks historically have been higher than the average returns for US large company stocks. But those returns include long periods of both strong and weak relative performance.

Investors may attempt to enhance returns by increasing their exposure to small company stocks at what appear to be the most opportune times. Yet this effort to time the size premium can be frustrating because the most rewarding results often occur in an unpredictable manner.

A recent paper by Wei Dai, PhD, explores the challenges of attempting to time the size, value, and profitability premiums. Here we will keep the discussion to a simpler example.

As of October 31, 2016, small company stocks had outpaced large company stocks for the year-to-date by 0.34 percentage points.

To the surprise of many market observers, the broad stock market rose following the US presidential election on November 8, with small company stocks outperforming the market as a whole. In the eight trading days following the US presidential election, the small cap premium, as measured by the return difference between the Russell 2000 and Russell 1000, was 7.8 percentage points. This helped small company stocks pull ahead of large company stocks year-to-date, as of November 30, by approximately 8 percentage points and for a full one-year period by approximately 4 percentage points.

This recent example highlights the importance of staying disciplined. The premiums associated with the size, value, and profitability dimensions of expected returns may show up quickly and with large magnitude. There is no guarantee that the size premium will be positive over any period, but investors put the odds of achieving augmented returns in their favor by maintaining constant exposure to the dimensions of higher expected returns.

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Prediction Season

The close of each calendar year brings with it the holidays as well as a chance to look forward to the year ahead. 

In the coming weeks, investors are likely to be bombarded with predictions about what the future, and specifically the next year, may hold for their portfolios. These outlooks are typically accompanied by recommended investment strategies and actions that are aimed at trying to avoid the next crisis or missing out on the next “great” opportunity. When faced with recommendations of this sort, it would be wise to remember that investors are better served by sticking with a long-term plan rather than changing course in reaction to predictions and short-term calls.


One doesn’t typically see a forecast that says: “Capital markets are expected to continue to function normally,” or “It’s unclear how unknown future events will impact prices.” Predictions about future price movements come in all shapes and sizes, but most of them tempt the investor into playing a game of outguessing the market. Examples of predictions like this might include: “We don’t like energy stocks in 2017,” or “We expect the interest rate environment to remain challenging in the coming year.” Bold predictions may pique interest, but their usefulness in application to an investment plan is less clear. Steve Forbes, the publisher of Forbes Magazine, once remarked, “You make more money selling advice than following it. It’s one of the things we count on in the magazine business—along with the short memory of our readers.” Definitive recommendations attempting to identify value not currently reflected in market prices may provide investors with a sense of confidence about the future, but how accurate do these predictions have to be in order to be useful?

Consider a simple example where an investor hears a prediction that equities are currently priced “too high,” and now is a better time to hold cash. If we say that the prediction has a 50% chance of being accurate (equities underperform cash over some period of time), does that mean the investor has a 50% chance of being better off? What is crucial to remember is that any market-timing decision is actually two decisions. If the investor decides to change their allocation, selling equities in this case, they have decided to get out of the market, but they also must determine when to get back in. If we assign a 50% probability of the investor getting each decision right, that would give them a one-in-four chance of being better off overall. We can increase the chances of the investor being right to 70% for each decision, and the odds of them being better off are still shy of 50%. Still no better than a coin flip. You can apply this same logic to decisions within asset classes, such as whether to currently be invested in stocks only in your home market vs. those abroad. The lesson here is that the only guarantee for investors making market-timing decisions is that they will incur additional transactions costs due to frequent buying and selling.

The track record of professional money managers attempting to profit from mispricing also suggests that making frequent investment changes based on market calls may be more harmful than helpful. Exhibit 1, which shows S&P’s SPIVA Scorecard from midyear 2016, highlights how managers have fared against a comparative S&P benchmark. The results illustrate that the majority of managers have underperformed over both short and longer horizons.

Exhibit 1.png

Rather than relying on forecasts that attempt to outguess market prices, investors can instead rely on the power of the market as an effective information processing machine to help structure their investment portfolios. Financial markets involve the interaction of millions of willing buyers and sellers. The prices they set provide positive expected returns every day. While realized returns may end up being different than expected returns, any such difference is unknown and unpredictable in advance.

Over a long-term horizon, the case for trusting in markets and for discipline in being able to stay invested is clear. Exhibit 2 shows the growth of a US dollar invested in the equity markets from 1970 through 2015 and highlights a sample of several bearish headlines over the same period. Had one reacted negatively to these headlines, they would have potentially missed out on substantial growth over the coming decades.

Exhibit 2.png


As the end of the year approaches, it is natural to reflect on what has gone well this year and what one may want to improve upon next year. Within the context of an investment plan, it is important to remember that investors are likely better served by trusting the plan they have put in place and focusing on what they can control, such as diversifying broadly, minimizing taxes, and reducing costs and turnover. Those who make changes to a long-term investment strategy based on short-term noise and predictions may be disappointed by the outcome. In the end, the only certain prediction about markets is that the future will remain full of uncertainty. History has shown us, however, that through this uncertainty, markets have rewarded long-term investors who are able to stay the course.

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The Power Of Markets

In 1958, economist Leonard Read published an essay entitled “I, Pencil: My Family Tree as Told to Leonard E. Read.”

The essay, narrated from the point of view of a pencil, describes the “complex combination of miracles” necessary to create and bring to market the commonplace writing tool that has been used for generations. The narrator argues that no single individual possesses enough ability or know-how to create a pencil on their own. Rather, the mundane pencil—and the ability to purchase it for a “trifling” sum—is the result of an extraordinary process driven by the knowledge of market participants and the power of market prices.


Upon observing a pencil, it is tempting to think a single individual could easily make one. After all, it is made up of common items such as wood, paint, graphite, metal, and a rubber eraser. By delving deeper into how these seemingly ordinary components are produced, however, we begin to understand the extraordinary backstory of their synthesis. Take the wood as an example: To produce wood requires a saw, to make the saw requires steel, to make steel requires iron. That iron must be mined, smelted, and shaped. A truck, train, or boat is needed to transport the wood from the forest to a factory where numerous machines convert it into lumber. The lumber is then transported to another factory where more machines assemble the pencil. Each of the components mentioned above and each step in the process have similarly complex backstories. All require materials that are sourced from far-flung locations, and countless processes are involved in refining them. While the multitude of inputs and processes necessary to create a pencil is impressive, even more impressive are the coordinated actions required by millions of people around the world to bring everything together. There is the direct involvement of farmers, loggers, miners, factory workers, and the providers of capital. There is also the indirect involvement of millions of others—the makers of rails, railroad cars, ships, and so on. Market prices are the unifying force that enables these millions of people to coordinate their actions efficiently.

Workers with specific knowledge about their costs, constraints, and efforts use market prices to leverage the knowledge of others to decide how to direct their own resources and make a living. Consider the farmer, the logger, and the price of a tree. The farmer will have a deep understanding of the costs, constraints, and efforts required to grow trees. To increase profit, the farmer will seek out the highest price when selling trees to a logger. After purchasing the trees, the logger will convert them to wood and sell that wood to a factory. The logger understands the costs, constraints, and efforts required to do this, so to increase profit, the logger seeks to pay the lowest price possible when buying trees from the farmer. When the farmer and the logger agree to transact, the agreed upon price reflects their combined knowledge of the costs and constraints of both growing and harvesting trees. That knowledge allows them to decide how to efficiently allocate their resources in seeking a profit. Ultimately, it is price that enables this coordination. On a much larger scale, price formation is facilitated by competition between the many farmers that sell trees to loggers and between the many loggers that buy trees from farmers. This market price of trees is observable and can be used by others in the production chain (e.g., the lumber factory mentioned above) to inform how much they can expect to pay for wood and to plan how to allocate their resources accordingly.


There is a corollary that can be drawn between this narrative about the market for goods and the financial markets. Generally, markets do a remarkable job of allocating resources, and financial markets allocate a specific resource: financial capital. Financial markets are also made up of millions of participants, and these participants voluntarily agree to buy and sell securities all over the world based upon their own needs and desires. Each day, millions of trades take place, and the vast collective knowledge of all of these participants is pooled together to set security prices. Exhibit 1 shows the staggering magnitude of participation in the world equity markets on an average day in 2015.

Any individual trying to outguess the market is competing against the extraordinary collective wisdom of all of these buyers and sellers. Viewed through the lens of Read’s allegory, attempting to outguess the market is like trying to create a pencil from scratch rather than going to the store and reaping the fruits of others’ willingly supplied labor. In the end, trying to outguess the market is incredibly difficult and expensive, and over the long run, the result will almost assuredly be inferior when compared to a market-based approach. Professor Kenneth French has been quoted as saying, “The market is smarter than we are and no matter how smart we get, the market will always be smarter than we are.” One doesn’t have to look far for data that supports this. Exhibit 2 shows that only 17% of US equity mutual funds have survived and outperformed their benchmarks over the past 15 years.


The beauty of Leonard Read’s story is that it provides a glimpse of the incredibly complex tapestry of markets and how prices are formed, what types of information they contain, and how they are used. The story makes it clear that no single individual possesses enough ability or know-how to create a pencil on their own but rather that the pencil’s miraculous production is the result of the collective input and effort of countless motivated human beings. In the end, the power of markets benefits all of us. The market allows us to exchange the time we require to earn money for a few milliseconds of each person’s time involved in making a pencil. For an investor, we believe the lesson here is that instead of fighting the market, one should pursue an investment strategy that efficiently and effectively harnesses the extraordinary collective power of market prices. That is, an investment strategy that uses market prices and the information they contain in its design and day-to-day management. In doing so, an investor has access to the rewards that financial markets make available to providers of capital.

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Presidential Elections And The Stock Market

Next month, Americans will head to the polls to elect the next president of the United States. While the outcome is unknown, one thing is for certain: There will be a steady stream of opinions from pundits and prognosticators about how the election will impact the stock market. As we explain below, investors would be well‑served to avoid the temptation to make significant changes to a long‑term investment plan based upon these sorts of predictions.

Short-term trading and presidential election results

Trying to outguess the market is often a losing game. Current market prices offer an up-to-the-minute snapshot of the aggregate expectations of market participants. This includes expectations about the outcome and impact of elections. While unanticipated future events—surprises relative to those expectations—may trigger price changes in the future, the nature of these surprises cannot be known by investors today. As a result, it is difficult, if not impossible, to systematically benefit from trying to identify mispriced securities. This suggests it is unlikely that investors can gain an edge by attempting to predict what will happen to the stock market after a presidential election.

Exhibit 1 shows the frequency of monthly returns (expressed in 1% increments) for the S&P 500 Index from January 1926 to June 2016. Each horizontal dash represents one month, and each vertical bar shows the cumulative number of months for which returns were within a given 1% range (e.g., the tallest bar shows all months where returns were between 1% and 2%). The blue and red horizontal lines represent months during which a presidential election was held. Red corresponds with a resulting win for the Republican Party and blue with a win for the Democratic Party. This graphic illustrates that election month returns were well within the typical range of returns, regardless of which party won the election.

Long-term investing: Bulls & Bears ≠ Donkeys & Elephants

Predictions about presidential elections and the stock market often focus on which party or candidate will be “better for the market” over the long run. Exhibit 2 shows the growth of one dollar invested in the S&P 500 Index over nine decades and 15 presidencies (from Coolidge to Obama). This data does not suggest an obvious pattern of long-term stock market performance based upon which party holds the Oval Office. The key takeaway here is that over the long run, the market has provided substantial returns regardless of who controlled the executive branch.


Equity markets can help investors grow their assets, but investing is a long-term endeavor. Trying to make investment decisions based upon the outcome of presidential elections is unlikely to result in reliable excess returns for investors. At best, any positive outcome based on such a strategy will likely be the result of random luck. At worst, it can lead to costly mistakes. Accordingly, there is a strong case for investors to rely on patience and portfolio structure, rather than trying to outguess the market, in order to pursue investment returns.

Economic Growth & Equity Returns

A relevant question for many investors is whether their view of economic growth should impact how they invest.

Opinions about future economic growth often differ across market participants. For example, in a survey of more than 60 economists conducted by the Wall Street Journal in June 2016, estimates of US GDP growth in 2017 ranged from 0.2% to 3.7%. A relevant question for many investors is whether their view of economic growth should impact how they invest. In this regard, they may be surprised to find that the historical link between annual GDP growth and equity returns has been quite weak.

Exhibit 1 shows annual GDP growth vs. annual returns for developed and emerging markets. These plots indicate that there has not been a strong relation between GDP growth and equity returns in the same year. For example, in developed markets country/year combinations when GDP growth was positive, the spread in returns was substantial: 323 country/year combinations had returns above 10% while 192 country/year combinations had returns below −10%. We see a similar pattern in realized returns for developed markets country/year combinations when GDP growth was negative. Emerging markets show a similar pattern.

Despite this weak relation between GDP growth and stock returns in the historical data, investors often ask whether shorter-term fluctuations in economic cycles impact stock returns in the near term. Stated differently, while on the surface Exhibit 1 presents a weak picture of GDP growth and stock returns in the same year, is there a relationship between the two that is not obvious from this exhibit?

To address this question, we examine 23 developed markets from 1975 to 2014 and 19 emerging markets from 1995 to 2014. Each year, countries are classified as either high or low growth depending on whether their GDP growth was above or below that year’s median GDP growth, defined separately for developed and emerging markets. We then look at stock market returns of high and low growth countries over the following year. The return for each group of countries is the average stock market return of all countries in the group weighted by countries’ market capitalization weights.

Exhibit 2 shows that, historically, differences in GDP growth over the past year contained little information about differences in equity returns this year. In both developed and emerging markets, average annual returns were similar for high and low growth countries. In fact, low growth countries had slightly higher average returns than high growth countries, although this return difference was not reliably different from zero. In other words, there is no evidence that this return difference occurred by anything other than random chance.

Can superior forecasts of short-term future economic growth help improve investment decisions? To address this question, we extend the analysis and assume perfect foresight about GDP growth over the next year. We now study the returns of high and low growth countries over the same year we measure GDP growth. This is not an implementable strategy because investors do not have the advantage of knowing economic growth in advance. They must rely on GDP forecasts, adding additional uncertainty. Exhibit 2 shows that even under the assumption of perfect foresight, using GDP data would not have generated reliable excess returns for investors. In developed markets, low growth countries had higher average annual returns than high growth countries, whereas in emerging markets, high growth countries had higher average annual returns than low growth countries. Neither difference in returns was reliably different from zero. This suggests that markets quickly incorporate expectations about future economic growth, making it difficult for investors to benefit from growth forecasts even with the advantage of perfect foresight. Differences in equity returns across countries seem to be driven more by differences in discount rates than by differences in GDP growth, even under a perfect forecasting scenario.


Many investors look to economic growth as an indicator of future equity returns. However, the relation between economic growth and returns in the historical data has been shown to be weak. This should not come as a surprise given that returns are determined by discount rates and investors’ aggregate expectations of future growth. Surprises relative to those expectations, whether positive or negative, may cause realized returns to differ from expectations. The evidence presented here suggests that differences in GDP growth contain little information about differences in stock returns in the same year and over the subsequent year. This means that it is difficult for investors to earn excess returns by relying on estimates of current or future GDP growth—even estimates that perfectly forecast GDP growth over the next 12 months.


Can Volatility Predict Returns?

When investing in stocks, understanding the volatility of their returns can be an important ingredient to help investors maintain a disciplined approach. People invest their capital hoping to earn a rate of return above that of just holding cash, and there is ample evidence that capital markets have rewarded disciplined investors.  For example, Exhibit 1 illustrates what investing $1 in 1926 into various asset classes would have translated to through the end of 2015. Nevertheless, returns can be negative for days, months, and even years. After such episodes, investors are frequently exposed to stories exclaiming what may cause the next financial crisis.

When volatility spikes, remaining disciplined can be even more challenging as pundits are quick to link volatility to any number of impending “crises” and to predict that short- term returns will be poor. Based on these predications, their advice for investors is o en “sell now” to avoid these poor returns. But as Professor Eugene Fama points out, “The onset of high volatility should be associated with price declines that increase expected returns going forward (to compensate investors for the higher volatility).” That is, volatility often increases after a price decline, which may increase expected returns. So these pundits may be reflecting on what has already occurred, not what will occur.

Do recent stock market volatility levels have statistically reliable information about future stock returns? We can examine historical data to see if there have been statistically reliable differences in average returns or equity premiums between more volatile and less volatile markets, if a strategy that attempts to avoid equities in times of high volatility adds value over a market portfolio, and if there is any relation between current volatility and subsequent returns.

A simple way to see if stock market volatility and returns are related is to look at average returns across different market environments. In Exhibit 2, we take monthly returns for the US equity market (represented by the Fama/French US Total Market Index) and break them up based on the previous month’s standard deviation (computed using daily stock market returns). Average returns in months when the previous month had higher volatility (75th percentile or above) were slightly higher than when the previous month had lower volatility (25th percentile or below). This conforms with the intuition presented by Fama. But, because stock returns have been noisy, these differences in average returns have not been reliably different from zero. In other words, at a glance there does not seem to be an economically meaningful difference in average equity returns based on the volatility of the prior month.

Exhibit 2 demonstrates that average stock market returns appear similar across various levels of market volatility. Is the equity premium (the return over US Treasury bills, or "T-bills") also similar across different levels of volatility? Exhibit 3 shows the average monthly returns for the US equity market and T-bills from January 1927 through April 2016. The full sample is further broken out into average returns for months following a “high volatility” month (75th percentile or above) and the remaining months.

We see that the average monthly equity premium has been higher after high volatility months. Nevertheless, the difference with all other months is not reliably different from zero—meaning we cannot reliably say that the premium is higher or lower after months with high volatility.2 These results suggest it is unlikely we can learn anything about this month’s equity premium based on last month’s volatility.

What if we had a trading strategy that attempted to avoid investing in equities when volatility was high? How would such a strategy perform relative to the market? Exhibit 4 shows returns and standard deviations for the US equity market, T-bills, and a hypothetical trading strategy that bails out of equities and invests in T-bills when the previous month’s volatility was high—a strategy that “flies to safety.” If the previous month’s volatility was high (75th percentile or above), the strategy invests in T-bills. If the previous month’s volatility was not high, the strategy invests in US equities.

Over the period from January 1927 through April 2016, the volatility of the “fly to safety” strategy, as measured by its standard deviation, was lower than the volatility of the US equity market (12.21% vs. 18.66% annualized). This makes sense because the fly to safety strategy is invested in T-bills one quarter of the time, so we would expect it to have a lower volatility. However, this lower volatility came with lower returns, as the fly to safety strategy had an annualized return of 8.22%, compared to 9.75% for US equities. A strategy investing 75% in the market and 25% in T-bills would have performed similarly to the fly to safety strategy, as illustrated in the last column of Exhibit 4.

Consistent with the analysis presented thus far, Exhibit 5 shows the randomness of the relation between recent volatility and future returns. The relation between them looks “flat.” That is, recent volatility does not indicate if future returns will be “high” and does not indicate if future returns will be “low.” This is confirmed through regression analysis, which further indicates there has been no reliable relation between recent volatility and future returns.

What can we take away from this analysis? Put simply, we can expect volatility when investing in stocks. There is considerable academic evidence that an investment strategy attempting to forecast short-term price movements is unlikely to be successful. Forecasting short-term stock market performance based on current volatility is no different. We believe that developing an asset allocation to match up with your desired risk tolerance and investment objectives, and staying disciplined and rebalancing in all market environments, remains an effective way to pursue your long-term investment goals.


GDP Growth and Equity Returns

Does GDP Growth give us any information about short-term market returns?

Market participants continually update their expectations about the future, including expectations about the future state of the economy. e current prices of the stocks
and bonds held by investors therefore contain up-to-date information about expected GDP growth and a multitude of other considerations that inform aggregate market expectations. Accordingly, only new information that is not already incorporated in market prices should impact stock and bond returns.

Quarterly GDP estimates are released with a one-month lag and are frequently revised at a later point in time. Initial quarterly GDP estimates were revised for 54 of the 56 quarters from 2002 to 2015.  Thus, the final estimate for last quarter may end up being higher or lower than 0.5%.

Prices already reflect expected GDP growth prior to the official release of quarterly GDP estimates. e unexpected component (positive or negative) of a GDP growth estimate is quickly incorporated into prices when a new estimate is released. A relevant question for investors is whether a period of low quarterly GDP growth has information about short-term stock returns going forward.

Exhibit 1 shows that, from 1948 to 2016, the average quarterly return for the S&P 500 Index was 3%. When quarterly GDP growth was in the lowest quartile of historical observations, the average S&P 500 return in the subsequent quarter was 3.2%, which is similar to the historical average for all quarters. is data suggests there is little evidence that low quarterly GDP growth is associated with short-term stock returns above or below returns in other periods.

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