By now most informed investors are at the very least aware of the rationale behind index investing. It’s a simple argument really. Thanks to millions of buyers and sellers the market does a good job of translating information into prices. Indexers stay on the bench because they know the perils of playing the “find the next best stock” game.

The evidence for buying and holding the index vs. attempting to beat it is long and well founded. There’s nothing new to this argument and maybe that’s the point. It’s been made for over 40 years. Vanguard founder John Bogle is perhaps the most vocal and consistent messenger. In fact, I might argue that he’s saved investors more money than any single financial persona in history due to the size and scope of the company he built. Here’s the problem. Few index investors understand that the same academics responsible for its groundbreaking research, see it as the maiden version of factor based investing.

In the scientific community Eugene Fama is revered as the father of modern day finance. He won the Nobel prize in 2013, but he’s still probably not what you would consider a household name. His seminal work on market efficiency laid the foundation for the main argument that index investors make daily “It’s hard to beat the market…So just own it.

When compared to other scientific areas of study, it’s fair to say that modern day financial science is a newer discipline, coming of age when we first began tracking securities prices with the help of computers. The discovery that stock prices tend to follow a random walk theory, moving independent of trends, may have been one of the first transcendent ideas to come from this research. Now, over 50 years later we know much more about empirical factors that help to explain where investment returns come from.

In 1992 Fama, along with colleague Kenneth French went on to publish one of the most widely sourced academic papers in all of finance. The “Fama-French Three Factor Model” documented the historical evidence behind the tendencies for stocks to outperform bonds, small companies to outperform large companies and value companies to outperform growth companies. Since then, academia has continuously searched to identify ways to improve upon what we already know about the movement of prices. Momentum and other factors that have rigorous academic backing embody these efforts.
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In 2017 “objectivity” is the common buzzword that gets thrown around all too lightly. Choosing to build a market cap weighted index portfolio doesn’t strike me as an objective approach to portfolio management given the decades of research compiled since the efficient markets hypothesis.
 
Evidence and research aside, that doesn’t mean all strategies are created equal. The financial industry hasn’t done investors a lot of favors with the marketing of factor based investing and maybe that’s the reason it’s so grossly misunderstood. Smart beta, active indexing, and fundamental indexing are just a few of the invented alias’s. Any fund or strategy claiming the backing of empirical research should be carefully vetted for how the factor/factors are being targeted, fees and also how its inclusion interacts with the rest of the portfolio.      
 
It’s not bad or wrong to simply own the market, but I would argue that if you believe in index investing, you should believe in factor based investing if for no other reason than the initial architects of such research do. It represents the best empirical understanding we have of what drives investment performance. 

Should stock investors worry about changes in interest rates?
Research shows that, like stock prices, changes in interest rates and bond prices are largely unpredictable.[1] It follows that an investment strategy based upon attempting to exploit these sorts of changes isn’t likely to be a fruitful endeavor. Despite the unpredictable nature of interest rate changes, investors may still be curious about what might happen to stocks if interest rates go up.

Unlike bond prices, which tend to go down when yields go up, stock prices might rise or fall with changes in interest rates. For stocks, it can go either way because a stock’s price depends on both future cash flows to investors and the discount rate they apply to those expected cash flows. When interest rates rise, the discount rate may increase, which in turn could cause the price of the stock to fall. However, it is also possible that when interest rates change, expectations about future cash flows expected from holding a stock also change. So, if theory doesn’t tell us what the overall effect should be, the next question is what does the data say?

Recent Research
Recent research performed by Dimensional Fund Advisors helps provide insight into this question.[2] The research examines the correlation between monthly US stock returns and changes in interest rates.[3] Exhibit 1 shows that while there is a lot of noise in stock returns and no clear pattern, not much of that variation appears to be related to changes in the effective federal funds rate.[4]
 
Exhibit 1.     Monthly US Stock Returns against Monthly Changes in Effective Federal Funds Rate,
August 1954–December 2016

For decades we’ve known about the existence of factors that help to explain expected investment return. “Factor based investing” isn’t a new concept, but it is new to many investors. For one reason or another the terminology, which is widely recognized in financial academia, struggled to find mainstream adoption. Now, for the first time things are beginning to change. Unlike the relentless stream of jargon invented by the financial industry, factor based investing describes an investment approach that’s grounded in science, as opposed to many others which are created to support Wall Street sales pitches.

The easiest way to understand factor based investing is to first think about investment management in a very basic sense of either passive or active. The two styles occupy separate ends of a decision spectrum which represents not only the level of activity, but also the type of activity. Factor based investing really sits at the intersection of passive and active management, but in order to truly understand it, we must further define the opposite ends of the spectrum.

Pure Passive Index Investing
A pure passive approach applies the most simplistic form of expected return predictability. The goal is to closely track the market index in order to replicate its performance while mitigating as many fees as possible throughout the process. Basically, buy it and hold it forever with virtually no activity or human intervention.
 
The predominant passive indexing approach used today hasn’t evolved much over the last 40 years. Market cap weighting or cap weighted indexing assigns a company’s exposure in the index by its overall size in the marketplace. The number of outstanding shares times the share price gives us a company’s market cap, which is then used to determine what % of exposure it gets in the index. Therefore, the largest companies have a bigger impact on index performance than the smallest. For example: The S&P 500 index represents that largest 500 companies in the United States. Apple is just one company yet; it accounts for nearly 4% of the index.   
 
Conventional Active Investing
​Historically, we think about active investing in the context of predicting stock or asset class behavior based upon a number of fundamental or technical indicators. This type of forecasting places a high level of subjectivity in the hands of managers who are charged with making decisions that add value (or alpha as it’s known in the industry), above and beyond what the investor could have received had they invested in the passive index. The managers goal is to outperform. Doing so over long periods of time usually results in a fair amount of stardom and large fund inflows coming from return chasing investors.

Passive index style investing has seen a significant popularity growth in recent years largely due to the evidence suggesting a failure of speculative active managers. Yet, it’s inaccurate to portray inactivity as a sound investment strategy based on this fact alone. Our understanding of capital markets and the factors that explain investment return has evolved significantly since the advent of index investing over 40 years ago. Every time a decision is made to adjust a portfolio in some way, even if the decision is to simply rebalance, the investor makes an active decision to move away from the pure passive end of the management spectrum.

Factor Based Investing
​Factor based investing seeks to answer the question: What are the INTELLIGENT active and passive decisions that can be made to improve the risk/return profile of a portfolio?
 
This is where financial science comes in. Factor based investors believe in making decisions based on the evidence reflected in large amounts of historical data. The conventional active investor believes in the possession of a superior skill or intellect which can be used to outsmart the market by seeing things others have missed. The issue with a conventional active approach is that at some stage in the decision making process, the outcome must be interpreted as a reasonable guess, hunch, or gut feeling. In contrast, a factor based approach is always able to reference the historical data and only the data as evidence of rational, thereby removing much of the subjective human element from the decision making process.

Factor based investing positively pulls from both active and passive sides of the spectrum. Like passive, it strongly agrees with the idea that attempting to time the market is routinely impossible. Unlike a pure passive indexing, factor based investing recognizes the evolution in our understanding of capital markets and factors that help to explain investment returns. Thus, it actively structures investments in the optimal way to compensate investors for taking risks that are historically worth taking.

The supporting evidence
Factors such as the following help to explain the reward investors receive for the amount of exposure they maintain to the MARKET as a whole, VALUE companies, SMALL companies and HIGH PROFITABILITY companies. The data going as far back as the 1920’s is reveals these effects which exist not only in domestic markets as listed below, but also across geography and asset classes around the globe. As time elapses over different 1,5,10 and 15 year periods, we begin to see the undeniable effect.

Historical Performance of Factors over Rolling Periods

These examples make a strong case for structuring portfolios in a manner to target some specific factors. However, one point that’s often left out of the discussion is the importance of diversification. If the research is interpreted to suggest that due to the historical likelihood of value stocks outperforming growth and small to outperform large, a portfolio should therefore ONLY own small and value companies, it has been sorely misinterpreted. The diversification benefits of owning a large number of companies which fall across the growth, value and size spectrum, in addition to fixed income is of critical importance to most investors in order to reduce overall portfolio volatility.
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Research Pioneers
In its purest form factor based investing holds true to objective ongoing research that turns a blind eye to the name or even reputation of any single company. Pioneers of this movement such as Nobel Laureates Harry Markowitz, William Sharpe, Eugene Fama and Kenneth French are unlikely household names to the average investor, but they’re undoubtedly giants of modern finance. They, along with forward thinking industry titans like Vanguard’s Jack Bogle and Dimensional Fund Advisor’s David Booth have helped make the practical application of empirical research possible. 

The current level of activity and new product development has never been higher. Perhaps the most important thing to understand about factor based investing is that today’s research stands on the shoulders of yesterday. “Eureka” moments are few and far between with most new developments coming in the form incremental improvements to well-founded ideas. I would issue a word of caution, and even a healthy level of skepticism of the financial industry which regularly rushes products to market, citing new research, without fully understanding its validity. Remember, Nobel Prizes don’t grow on trees.

Factor based investing isn’t purely active and it isn’t purely passive but a marriage of intelligent research backed ideas from both disciplines. It’s about taking what financial science has given us, evaluating the strongest ideas and filtering through thousands of solutions to find the best translation of those ideas.

It used to be a strategy reserved only for the wealthy sophisticated few. Today, I can proudly say that with the help of firms like WealthShape investors from all walks of life have access to evidence based investment solutions that are built on reason, not speculation.

Since the 1950s, there have been numerous breakthroughs in the field of financial economics that have benefited both society and investors.

One early example, resulting from research in the 1950s, is the insight that diversification can increase an investor’s wealth. Another example, resulting from research in the 1960s, is that market prices contain up-to-the-minute, relevant information about an investment’s expected return and risk. This means that market prices provide our best estimate of a security’s value. Seeking to outguess market prices and identify over- and undervalued securities is not a reliable way to improve returns.

This long history of innovation in research continues into the present day. As academics and market participants seek to better understand security markets, insights from their research can enable investors to better pursue their investment goals. In this article, we will focus on a series of recent breakthroughs into the relation between a firm’s profitability and its stock returns. As we will see, an important insight Dimensional drew from this research is how profitability and market prices can be used to increase the expected returns of a stock portfolio without having to attempt to outguess market prices.

DIFFERENCES IN EXPECTED RETURNS
The price of a stock depends on a number of variables. For example, one variable is what a company owns minus what it owes (also called book value of equity). Expected profits, and the discount rate investors apply to these profits, are others. This discount rate is the expected return investors demand for holding the stock. The impact of market participants trading stocks is that market prices quickly find an equilibrium point where the expected return of a stock is commensurate with what investors demand.

Decades of theoretical and empirical research have shown that not all stocks have the same expected return. Stated simply, investors demand higher returns to hold some stocks and lower returns to hold others. Given this information, is there a systematic way to identify those differences?

OBSERVING THE UNOBSERVABLE: CURRENT AND FUTURE PROFITABILITY
Market prices and expected future profits contain information about expected returns. While we can readily observe market prices as stocks are traded (think about a ticker tape scrolling across a television screen), we cannot observe market expectations for future profits or future profitability, which is profits divided by book value. So how can we use an unobserved variable to tell us about expected returns?

A paper by Professors Eugene Fama and Kenneth French published in 2006[1] tackles this problem. Fama and French have authored more than 160 papers. They both rank within the top 10 most-cited fellows of the American Finance Association[2] and in 2013, Fama received a Nobel Prize in Economics Science for his work on securities markets.

Fama and French explored which financial data that is observable today contain information about expected future profitability. They found that a firm’s current profitability contains information about its profitability many years hence. What insights did Dimensional glean from this? Current profitability contains information about aggregate investor’s expectations of future profitability.

MEASURING PROFITABILITY
The next academic breakthrough on profitability research was done by Professor Robert Novy-Marx, a world-renowned expert on empirical asset pricing. Building on the work of Fama and French, he explored the relation of different measures of current profitability to stock returns.

Profits equal revenues minus expenses. One particularly important insight Dimensional took from Novy-Marx’s work is that not all current revenues and expenses have information about future profits. For example, firms sometimes call a revenue or expense “extraordinary” when they do not expect it to recur in the future. If those revenues or expenses are not expected to recur, should investors expect them to contain information about future profitability? Probably not.

This is what Novy-Marx found when conducting his research. In a paper published in 2013,[3] he used US data since the 1960s and a measure of current profitability that excluded some non-recurring costs so that it could be a better estimate for expected future profitability. In doing so, he was able to document a strong relation between current profitability and future stock returns. That is, firms with higher profitability tended to have higher returns than those with low profitability. This is referred to as a profitability premium.

Around the same time, the Research team at Dimensional was also conducting research into profitability. They extended the work of Fama and French and found that in developed and emerging markets globally, current profitability has information about future profitability and that firms with higher profitability have had higher returns than those with low profitability. They also found that this observation held true when using different ways of measuring current profitability. These robustness checks are important to show that the profitability premiums observed in the original studies were not just due to chance.

Their research indicated that when using current profitability to increase the expected returns of a real-world strategy, it is important to have a thoughtful measure of profitability that provides a complete picture of a firm’s expenses while excluding revenues and expenses that may be unusual and therefore not expected to persist in the future.

THE CUTTING EDGE: NEW RESEARCH
Many papers documenting profitability premiums globally have been written since 2013. An exciting forthcoming paper[4] by Professor Sunil Wahal provides powerful out-of-sample US evidence of profitability premiums. Wahal is an expert in market microstructure (how stocks trade) and empirical asset pricing.

Fama, French, and Novy-Marx’s research on profitability used US data from 1963 on. Why? Because when they conducted their research, reliable machine-readable accounting statement data required to compute profitability for US stocks was only available from 1963 on. Hand-collecting and cleaning accounting statement data and then transcribing it in a reliable fashion is no easy task and presents many a challenge for any researcher.

Wahal rose to those challenges. He gathered a team of research assistants to hand-collect accounting statement data from Moody’s Manuals from 1940 to 1963. By applying his (and his team’s) expertise in accounting, combined with a great deal of meticulous data checking, Wahal was able to produce reliable profitability data for all US stocks from 1940 to 1963. Using this data to measure the return differences between stocks with high vs. low profitability, Wahal found similar differences in returns to what had been found in the post-1963 period.

This research provides compelling evidence of the profitability premium pre-1963 and is a powerful out-of-sample test that strengthens the results found in earlier work.

THE SIZE OF THE PROFITABILITY PREMIUM
So how large has the profitability premium been historically? Large enough that investors who want to increase expected returns in a systematic way should take note. Exhibit 1 shows empirical evidence of the profitability premium in the US and globally. In the US, between 1964 and 2016, the Dimensional US High Profitability Index and the Dimensional US Low Profitability Index had annualized compound returns of 12.55% and 8.23%, respectively. The difference between these figures, 4.32%, is a measure of the realized profitability premium in the US over the corresponding time period. The non-US developed market realized profitability premium was 4.51% between 1990 and 2016. In emerging markets, the realized profitability premium was 5.21% between 1996 and 2016.

Most professions have a measuring stick to quantify a reputation or skill set. Medical degrees, law degrees and teaching certificates represent recognizable benchmarks for their professions. Our proud service men and women use a chain of command that instantly indicates their level of responsibility. So why is it so difficult to determine whether or not a financial advisor is worth their salt?
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The term “Financial Advisor” may very well be one of the most misrepresented professional titles. Reason being: Almost anyone can call themselves one. Don’t get me wrong, the financial services industry puts numerous exams and stipulations in place to license and track advisors, but just like any standardized test a passing score isn’t necessarily a great barometer for quality. According to WalletHub there are over 250 thousand advisors across the country. Thankfully, there are ways to help you to determine the background, experience and type of advisors out there.

Professional designations such as the CFP® (Certified Financial Planner), CFA (Chartered Financial Analyst®) and the already recognizable CPA, (Certified Public Accountant) give consumers a basic understanding of the training someone has endured. In any vetting process, educational background combined with a professional designation is one of the first things to look for. It’s not to say the absence of one is bad. I know many advisors who do a good job for their clients and don’t have letters after their name, which brings me to my next point.

Experience. Type can often be more valuable than tenure. While it’s comforting to see lots of years in the industry, that experience may not add up to a whole lot of knowledge. Here’s a shocker: Some financial services organizations allocate more resources to sales training than education.

A good way to decipher experience from fluff is to interview. Just like any job interview, pointed open-ended questions help to uncover details. What types of clients have you worked with? What is your investment philosophy and why? Situational questions such as, “tell me about the message you were sending to your clients back in 2008 and 2009 during the financial downturn,” provide a window into what the experience and expectations could look like.

Background. Finance is one of the most regulated industries on the planet largely because it involves money management. A background check is a great way to examine an advisor’s experience, licensing and whether or not any complaints have been filed against them. FINRA (Financial Industry Regulatory Authority) provides a great reference tool.
Hint: It will also help you to recognize the different types in the next topic.
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There’s a difference between suitability and fiduciary. Similar to the Hippocratic oath to do no harm that a licensed physician takes, a fiduciary is bound by law to act in your best interest. Believe it or not, this isn’t a requirement for most financial advisors. Reason being; if they sell commissionable products, the only obligation is to make sure that the product is suitable for the investor. The phraseology here is interesting. If you were to ask an investor which they would prefer: something that was in their best interest or something that was merely suitable for them, you would likely receive resounding support for the former.
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Consider the idea of a doctor being solely compensated based upon the treatments or medicines they recommended. The conflict of interest would instantly be apparent. Entering into an engagement with an advisor, whose compensation was based upon the commission from a product sale, isn’t a heck of a lot different from this scenario. The incentives often work in the opposite direction of what's in your best interest, even if they're trying to do the right thing.

As fiduciaries, Fee-Only Registered Investment Advisors receive zero commissions because the only product they have to sell is their expertise, something that is quantifiable and transparent, as opposed to sales commissions which are often wrapped into the complexities of a financial products expenses.

It’s important to point out the dilemma that Fee-Based Advisors face. Namely, when is it appropriate to sell products to a client based on a standard or suitability, and when is it appropriate to provide advice as a fiduciary acting in their best interest? Many see this as a contradiction. Why wouldn’t someone want to act in my best interest all the time? It’s the critical question that should be asked of every financial professional.

Hopefully this sheds some light on a confusing topic. A word of advice would be to know what type of advisor you are speaking with before you even interact with them. Due diligence up front is key because in a business populated by a litany of salespeople, judgment can sometimes get cloudy after a face to face meeting.

Financial professionals are always being mischaracterized partly due to an industry that intentionally blurs the lines. Most true Fee-Only Financial Advisors loathe being inadvertently called Brokers, and Brokers often do little to clarify that they aren’t actually acting in a fiduciary capacity. I’m not sure if we’ll ever get away from blanket terminology, but I am sure that individual investors are better served when they’re empowered with the knowledge to make informed choices.  

March 9th marked the 8-year anniversary of the current bull market. It’s not the longest on record (1987-2000), nor is it the shortest. From the 1990’s up until today the S&P 500 has gone from a long bull market to a momentary bear, back to a 5-year bull, leading up to the most recent bear market of ‘08 and finally arriving at today’s bull market. That’s five changes in total, spanning the course of over 26 years. The unpredictable nature of capital markets isn’t news to long term investors, making the significance of the 8-year anniversary essentially a moot point.

Although republicans hold majorities in the house and senate, healthcare reform came and went prior to having a vote. It is yet to be seen when the topic will be revisited as tax reform appears more likely to be the next priority. If anything is predictable in Washington, it’s party gridlock. Until further details unfold, maintaining the status quo is still the best option as opposed to speculating on what may or may not happen.​

As people change jobs, one constant stays the same: the importance of rolling over your 401k properly into an IRA. Today’s workers may need to execute a rollover anywhere from 5 to 10 times in their working life, and there are many pitfalls to the process. This webinar will look at the primary reasons to properly manage a rollover and the increasing investment options. Rollovers should not only be seen as an opportunity to preserve hard-earned retirement money, but also as a chance to reduce fees and consolidate and diversify one’s portfolio.

We're now 8 years removed from the market bottoms of 2009. March 9th has come to represent an anniversary of sorts - the day markets started moving in the right direction following a year’s worth of upheaval. As in previous years, this occasion will undoubtedly be marked by the usual onslaught of articles pontificating about how much steam this bull market has left in it. Yet, that repetitive angle, while tempting, seems to miss a critical point. 

In former editions of what feels like an annual March 8th bull market commentary I typically reference the length of this latest bull market and its place in history. I’ve always found a historical perspective more valuable than the fear mongering click bait produced by financial journalists desperately searching for retweets. Predictably, you'll get the "Is This Bull on its Last Leg?” or "Bear Market Ahead?" headlines designed to be more provocative than substantive, but I don’t begrudge anybody from making a living. After all, I myself had a momentary stint as a journalist a long time ago. I understand how hard it is to write new and engaging material on dry topics where the only time the masses pay attention is when the news isn't so welcoming. However, as a CERTIFIED FINANCIAL PLANNER™ professional my intuition tells me that there’s a more relevant angle to this story. Asking how much longer the current run can last is logical, but is it the right question? Perhaps the more applicable question should be:
 
On the anniversary of this current bull market, should any long term investor care?
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Admittedly, it’s a loaded question because the premise applies only to long-term investors, a point to which I would argue “any monies invested in the stocks should presumably be for the long-term”, further defined as a period not less than at least five years. Still, a time frame of five, ten or even twenty years might not be the most accurate representation. For many of us an investment lifetime begins in our 20’s and can last long into retirement.
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These realizations suggest that looking at things through the lens of bull vs. bear markets really doesn’t make all that much sense providing you agree that over time markets reward long-term, disciplined investors. The impact of missing even just a few of the good days is well chronicled, and thereby suggests that time is the ally of the long-term investor and market timing the adversary.

Bulls, bears and some perspective
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The usual definition of a bear market is when the stock’s decline by 20% from their peaks over a 2 month period. From the 1990’s till today the S&P 500 has gone from a long bull market to a momentary bear, back to a 5-year bull, leading up to the most recent bear market of 08 and finally arriving at our current 8-year bull market. That’s 5 changes in total, spanning the course of over 26 years. Long-term investors should accept the historical fact that markets fluctuate. None of us has to feel good about the prospect of any looming bear market. We need only to accept them as part and parcel to a greater end. 

In a motor vehicle, the suspension system keeps the tires in contact with the road and provides a smooth ride for passengers by o setting the forces of gravity, propulsion, and inertia.

You can drive a car with a broken suspension system, but it will be an extremely uncomfortable ride and the vehicle will be much harder to control, particularly in di cult conditions. row in the risk of a breakdown or running off the road altogether and there’s a real chance you may not reach your destination.

In the world of investment, a similarly bumpy and unpredictable ride can await those with concentrated and undiversified portfolios or those who constantly tinker with their allocation based on a short-term rough patch in the markets.

Of course, everyone feels in control when the surface is straight and smooth, but it’s harder to stay on the road during sudden turns and ups and downs in the market. And keep in mind the x for your portfolio breaking down is unlikely to be as simple as calling a tow truck.

For that reason, the smart thing to do is to diversify, spreading your portfolio across different securities, sectors, and countries. That also means identifying the right mix of investments (e.g., stocks, bonds, real estate) that aligns with your risk tolerance, which helps keep you on track toward your goals.

Using this approach, your returns from year to year may not match the top performing portfolio, but neither are they likely to match the worst. More importantly, this is a ride you are likelier to stick with.

Just as drivers of suspension less cars change their route to avoid potholes, people with concentrated portfolios may resort to market timing and constant trading as they try to anticipate the top-performing countries, asset classes, and securities.

Here’s an example to show how tough this is. Among developed markets, Denmark was number one in US dollar terms in 2015 with a return of more than 23%. But a big bet on that country the following year would have backfired, as Denmark slid to bottom of the table with a loss of nearly 16%.1

It’s true that the US stock market (by far the world’s biggest) has been a strong performer in recent years, holding the number three position among developed markets in 2011 and 2013, first in 2014, and sixth in 2016. But a decade before, in 2004 and 2006, it was the second worst-performing developed market in the world.1

Predicting which part of a market will do best over a given period is also tough. For example, while there is ample evidence to support why we should expect positive premiums from small cap, low relative price, and high profitability stocks, these premiums are not laid out evenly or predictably across the map. US small cap stocks were among the top performers in 2016 with a return of more than 21%. A year before, their results looked relatively disappointing with a loss of more than 4%. International small cap stocks had their turn in the sun in 2015, topping the performance tables with a return of just below 6%. But the year before that, they were the second worst with a loss of 5%.2

If you’ve ever taken a long road trip, you’ll know that conditions along the way can change quickly and unpredictably, which is why you need a vehicle that’s ready for the worst roads as well as the best. While diversification can never completely eliminate the impact of bumps along your particular investment road, it does help reduce the potential outsized impact that any individual investment can have on your journey.

With sufficient diversification, the jarring effects of performance extremes level out. at, in turn, helps you stay in your chosen lane and on the road to your investment destination.
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Happy motoring and happy investing. 

Checking the weather? Looking at a map of the world to plan your next vacation? Guess what - you’re using a model. While models can be useful for gaining insights that can help us make good decisions, they are simplifications of reality.

One example of a model is a weather forecast. Using data on current and past weather conditions, a meteorologist makes a number of assumptions and attempts to approximate what the weather will be in the future. This model may help you decide if you should bring an umbrella when you leave the house in the morning. However, as anyone who has been caught without an umbrella in an unexpected rain shower knows, reality often behaves differently than a model predicts it will.

In investment management, models are used by investors to gain insights that can help inform investment decisions. Financial researchers are frequently looking for new models to help answer questions like “What drives returns?” These models are often touted as being complex and sophisticated and incite debates about who has a “better” model. Investors who are evaluating investment strategies can benefit from understanding that the reality of markets, just like the weather, cannot be fully explained by any model. Hence, investors should be wary of any approach that requires a high degree of trust in a model alone.

THE MODEL, THE USER, AND THE APPLICATION
Just like with the weather forecasts, investment models rely on different inputs. Instead of things like barometric pressure or wind conditions, investment models may look at variables like the expected return or volatility of different securities. For example, using these sorts of inputs, one type of investment model may recommend an “optimal” mix of securities based on how these characteristics are expected to interact with one another over time. Users should be cautious though. The saying “garbage in, garbage out” applies to models and their inputs. In other words, a model’s output can only be as good as its input. Poor assumptions can lead to poor recommendations. However, even with sound underlying assumptions, a user who places too much faith in inherently imprecise inputs can still be exposed to extreme outcomes.

Nobel laureate Robert Merton offered some useful insights on this topic in an interview with David Booth, Chairman and Co-CEO of Dimensional Fund Advisors. “You’ll often hear people say, during the [financial] crisis or something, ‘There were bad models and good models.’ And someone will say, ‘Is yours a good model?’ That sounds like a good question, a reasonable question. But, actually, it isn’t really well-posed. You need a triplet: a model, the user of the model, and its application. You cannot judge a model in the abstract.” (For a video of the interview, please click the following link: Models Interview.)

We believe bringing financial research to life requires presence of mind on behalf of the user and awareness of a model’s limitations in order to identify when and how it is appropriate to apply that model. No model is a perfect representation of reality. Instead of asking “Is this model true or false?” (to which the answer is always false), it is better to ask, “How does this model help me better understand the world?” and “In what ways can the model be wrong?”

“THE EARTH IS ROUND,” INVESTING, AND THE JUDGMENT GAP
Consider the shape of the earth. One simple model describes the earth as a round sphere. While this is a good approximation, it is not completely accurate. In reality, the earth is an imperfect oblate spheroid—fatter at the equator and more squashed at the poles than a perfect sphere. Additionally, the surface of the planet is varied and changing: There are mountains, rivers, and valleys—it is not perfectly smooth. So how should we judge the model of “the earth is round”? For a parent teaching their child about the solar system or for a manufacturer of globes, assuming the earth is a perfect sphere is likely a fine application of the model. For a geologist studying sea levels or NASA engineers launching an object into space, it is likely a poor model. The difference lies in the user of the model and its application.
 
In investing, one should pay similar attention to the details of user and application when a model informs real-world investment decisions. For example, for investors in public markets, the efficient market hypothesis (EMH) is a useful model stating that asset prices reflect all available information. This model helps inform investors that they can rely on prices and that it is not worth trying to outguess the ones set collectively by millions of market participants. This insight has been confirmed by numerous studies on investment manager performance.[1] In applying this model to real-world investment solutions, however, there are several nuances that a user must understand in order to bridge the gap between theory and practice. Even if prices quickly reflect information, one should not assume that the EMH protects investors from making investment mistakes. Rigorous attention must be paid to trading costs and to avoid trading in situations when there may be asymmetric information or illiquidity that might disadvantage investors. To quote Professor Merton again, successful use of a model is “10% inspiration and 90% perspiration.” In other words, having a good idea is just the beginning. Most of the effort is in implementing the idea and making it work. In the end, there is a difference between blindly following a model and using it judiciously to guide your decisions. By employing sound judgment and thoughtful implementation, we believe it is more likely that outcomes will be consistent with a user’s expectations.

So what is an investor to do with this knowledge? When evaluating investment approaches, understanding a manager’s ability to effectively test and implement ideas garnered from models into real-world applications is an important first step. An investor who hires an investment manager to bridge this gap is placing trust in the judgment of that manager. The transparency offered by some approaches, such as traditional index funds, requires a low level of trust because the model is quite simple and it is easy to evaluate whether or not they have matched the return of the index. The tradeoff with this level of mechanical transparency is that it may sacrifice the potential for higher returns, as it prioritizes matching the index over anything else. For more opaque and complex approaches, like many active or complex quantitative strategies, the requisite level of trust required is much higher. Investors should look to understand how these managers use models and question how to evaluate the effectiveness of their implementation.

By selecting an investment manager that has experience in effectively putting financial research into practice and executing an approach that balances transparency with value-added implementation, investors should increase the probability of having a positive investment experience.

It’s been said that risk and reward is a double edged sword, inseparable and ever present in all aspects of life. We make daily decisions with our health, relationships, time etc. that in some way demonstrate a tradeoff between risk and reward. In essence, these decisions while seemingly trivial at times are mental calculations that attach probabilities depending on the gravity of each situation. So, how do we calculate the inherent relationship between risk and reward in our portfolio’s? I won’t be the first to tell you that financial jargon is dull to most people, but this term’s impact shouldn’t be. It’s called “standard deviation” and few investors have a clue what it means to their portfolio.
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First, higher isn’t always better. Double digit returns feel great. For risk averse investors, double digit standard deviation does not! As a historic volatility measurement, think of standard deviation as a thermometer for risk, or better yet anxiety. The higher it goes, the higher your blood pressure rises during volatile times. Portfolios that report large standard deviation numbers have experienced wide fluctuations in returns, both positively and negatively, around the average return. Those with a lower standard deviation have been able to mitigate volatility, meaning the up and down swings of the returns aren’t as wide.

​How it works in practical application
For this example, we’ll use 2x standard deviation. All that means, is we’ll be multiplying the standard deviation by 2 (known as the 95% confidence interval, which basically says that 95% of the time we can expect the return to lie between these two numbers in any given year). From the beginning of 2007 to the end of 2016 the S&P 500 average annual return was 6.95%. The standard deviation was 15.28%. Simplifying the numbers: 15 times 2 = 30. Now we just add 30 to the 6.95% average return to get 36.95% and subtract 30 from 6.95% to get -23.05%. In summation, with 95% confidence we can expect the S&P 500 return to fall between +36.95% and -23.05% in any given year based on historic volatility over the last ten years.
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Typically, as exposure to assets that tend to fluctuate more (i.e. stocks) increases, so does standard deviation. Therefore, if well diversified, a 100% stock portfolio will likely have higher historic volatility than 80% stocks, 80% higher than 60% stocks and so on. However, it doesn’t stop at the portfolio level. The underlying funds that make up your portfolio also exhibit volatility characteristics based on their makeup, sort of like a portfolio within your portfolio. For instance, you should generally expect an emerging markets fund to have a higher standard deviation than a US large cap growth fund because of the historically high volatility associated with emerging markets as an asset class. Why is that important? All else being equal, two portfolios that appear similar from a general stock to bond ratio will likely have vastly different experiences if one has 20% more exposure to emerging markets than the other.

Returns should always be discussed in context with the level of risk it took to achieve them. When it comes to measuring volatility, the more years of data the better. Standard deviation shouldn’t be measured over a period of less than 3 years with a preference being the inception date of the portfolio or fund. The concept of risk and reward is ever-present in our daily lives. Understanding the true level of risk in our portfolios only serves to reinforce expectations and strengthen the discipline of long term investors

2016 will go down as a year marked by the United Kingdom's vote to leave the European Union and the United States' surprise election of Donald J. Trump as president. From an investment perspective, it was a positive year for virtually every major asset class. US small cap stocks led the way gaining over 20% in 2016, much of which came in the 4th quarter. US large cap stocks also posted double digit returns, coming in at 11.9% for the S&P 500. With fears of China’s economic slowdown subsiding, Emerging Markets advanced over 11%, US bonds were up over 2% and International Developed markets surged in the month of December to a modest annual gain of 1%.

Interest rates were on the move with 10-year Treasury yields falling as low as 1.36% in July; only to reverse course, ending the year at 2.45%. The Fed raised rates last month for the first time in a year, with the likelihood of two or three more hikes expected in 2017.
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It seems like a long time ago, but at this time last year, the news was the tumbling price of oil. Crude touched bottom back in February, sliding all the way to the mid-$20s, the culmination of an uninterrupted 19-month slide. Since then the price of oil has more than doubled.

There’s been much talk about legislative changes to tax policies in 2017. Until further details unfold, it’s best to wait rather than speculate on what may or may not happen. It was in 2008 when then Senator Obama actively campaigned on a sun setting of the Bush era tax cuts, only to extend them throughout his presidency.

2016 reminds us that we all need to operate with a healthy level of skepticism when consuming the news. We witnessed two historic political surprises that a vast majority of media prognosticators never saw coming. The constant siren of absolute certainty spewing from the mouths of pundits makes it more difficult than ever to separate speculation from reality. The good news is; an accurate forecast of the future isn’t a requirement for being successful investors. Like countless other examples throughout history, disciplined investors were rewarded in 2016. Financial markets are complex instruments, but the way they operate is fairly straightforward. They don’t choose which news to disseminate, they react positively or negatively to the collective body of information. ​

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 paper1 by Wei Dai, PhD, explores the challenges of attempting to time the size, value, and profitability premiums.2 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.

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.

Predictions and Portfolios
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.”[1] 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.
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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.
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​Exhibit 1.       Percentage of US Equity Funds That Underperformed a Benchmark

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.       Markets Have Rewarded Discipline
Growth of a dollar—MSCI World Index (net dividends), 1970–2015

​In US dollars. Indices are not available for direct investment. Their performance does not reflect the expenses associated with the management of an actual portfolio. Past performance is no guarantee of future results. MSCI data © MSCI 2016, all rights reserved.

Conclusion
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.

Over time we’ve learned much from financial science and the forces or factors that help to explain where expected returns come from. The momentum factor identifies the tendency for positively/negatively performing assets to continue their positive/negative trajectory for a short amount of time into the future. Essentially the “winners” tend to stay winners and the “losers” tend to stay losers for a period of time. So what does the research suggest and how can investors benefit?

First a bit of background: The momentum effect, first written about in the early 1990’s, leaves efficient market hypothesis (EMH) proponents such as myself with a realism that’s hard to rectify. For EMH advocates price is king. In laymen’s terms: The best judge of any particular assets inherent worth is its current price, thanks to the millions of market participants (buyers and sellers) actively voting with their dollars. Momentum on the other hand contradicts this notion, at least over the short term.

Why does it exist?
The majority of factors that we target in building portfolios commonly have a risk based explanation for their performance, i.e. stocks outperforming bonds, small companies outperforming large companies or value outperforming growth over time. Attempting to explain the momentum factor’s performance through the conventional risk based lens is difficult.

Like these other factors, momentum has been persistent across time, asset classes and geography. However, its performance is best explained from a behavioral perspective. Other theories exist as to why winners stay winners and losers stay losers for a period of time, but the idea that investors tend to either over react or under react to news is a leading hypothesis. This suggests that markets aren’t perfectly efficient, a point to which I would begrudgingly agree. Perfectly being the key word. While over long periods of time, markets usually get it right, in short spurts security prices seem to have a bit of “noise” built into them.

The investment application of momentum
When looking at the addition of any factor to a portfolio, investors should always start out as cynics, requiring large amounts of supporting evidence. First, academia must backup its inclusion with rigorous empirical research. Second, it can’t just look good on paper. Practical application dictates that investors must be able to capture the performance after any additional costs associated with targeting it. For a long time, this was a key issue with incorporating the momentum factor. Due to the frequent changes to the winners and loser’s categories, does the increased trading cost associated with buying and selling surpass the benefit? Furthermore, does its inclusion dilute the all-important diversification of the portfolio?
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Not only must an investment vehicle exist, but the right vehicle has to be selected from a universe of thousands. Adding further complexity, is how it interacts and/or complements the rest of the portfolio. We believe that momentum is most effectively targeted through a low cost, quantitative, rules based methodology. This approach helps to lower cost and improve overall portfolio diversification. Investors commonly associate diversification with the benefits of different sizes and styles of asset classes which don’t always move in the same direction under different market conditions. Well, the same logic can in certain instances be applied to diversifying exposure to factors. Such is the case when momentum is properly paired with value due to their negative correlations with each other.
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In sum, momentum has the ability to offer long term performance and diversification benefits when it is properly implemented. As a firm that specializes in factor based investing we remain dedicated to research and the practical application of it. This translates into ever evolving, globally diversified portfolios which target areas that drive expected return.

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.

THE IMPORTANCE OF PRICE
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.
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THE POWER OF FINANCIAL MARKETS
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.

In US dollars. Global electronic order book (largest 60 exchanges). Source: World Federation of Exchanges. 

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.

Beginning sample includes funds as of the beginning of the 15-year period ending December 31, 2015. Past performance is no guarantee of future results. Source: Dimensional Fund Advisors, “The US Mutual Fund Landscape.” See disclosures for more information.

CONCLUSION
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.

​Someone once told me that people vote with their wallets. If that’s truly the case, then whatever a person’s political persuasion happens to be, it’s likely the one they believe best suits their financial needs. In an election year you’ll find no shortage of opinions on the impact that one party’s candidate will have on your investments. The Clinton camp will cite strong US market performance during Bill’s presidency as evidence to suggest Hillary is capable of delivering similar results. Trump supporters will point to Donald’s real estate success and business acumen to demonstrate his abilities. The question on the minds of investors is: Do I need to worry if my candidate doesn’t win? 

The Markets
Financial markets are complex instruments, but the way they operate is fairly straightforward. They don’t choose which news to disseminate, they react positively or negatively to the collective body of information. Politicians will inevitably take credit when the news is favorable and deflect blame when it doesn’t support their narrative. For this reason, tying a single economic policy to market performance is an inadequate measurement of success. Even if sweeping changes in the tax code or regulatory environment take place, the impact can take years to play out.

During the 2008-09 downturn there was plenty of blame to go around. Financial institutions took most of the heat due to the irresponsible sale of mortgage backed securities worsened by the impact of being highly leveraged. Credit rating agencies didn’t escape responsibility when they failed to appropriately categorize the quality of various financial instruments.
 
Deregulation at the hands of politicians was not overlooked. Many felt this environment was ripened for catastrophe when Bill Clinton signed the 1999 repeal of the Glass-Steagall Act, which was initially designed to limit the abilities of commercial banks and investment firms from crossing over into each other’s business’s. Decades earlier some could point to the relaxing of lending standards through the 1977 Community Reinvestment Act, which was meant to encourage commercial banks to help meet the needs of borrowers with moderate to low incomes.

The simple truth is too many variables exist to attach responsibility to one political party or another because market expansions and recessions are never the result of a single decision. The one major agreement is there is no agreement.
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Silver Lining for Investors No Matter Your Candidate
History has shown that if we look back to 1948, the likelihood of seeing 4 years of negative market returns is far-off. In fact, it’s only happened twice. (Nixon and Bush 43) During both periods the US economy was in a severe recession and as demonstrated above, it would be tough to tie either administration’s specific economic policies to the return of the S&P 500.   

​By and large, presidents have no control over financial markets. If any term comes to mind that’s indicative of a presidents impact it would likely be “victim of circumstance.” The collective history of markets is the most important thing to focus on. Since 1948 the S&P 500 has averaged double digit annualized returns. The vast majority of investors have retirement goals that extend far past 4 or 8 years of a presidential administration that they don’t favor. The good news is, regardless of the applause or blame for economic conditions under any president, they only get to stick around for so long.

​Source: The College Board, “Trends in College Pricing 2015.”

The growth of index investing
The argument for passive investing stems from decades of research into financial markets and the imperfect but solid job they do of incorporating all available information into stock prices. Ironically, what many fail to recognize is that indexes were not initially created for the sole purpose of investing; they were invented to measure the skill of active traders. When it became painfully evident that stock pickers overwhelmingly failed to outperform, products were created to mirror the index.

We’ve learned a lot over the last 60 years about factors that help to explain where investment returns come from. The standard market cap weighted methodology that’s applied to most indexing strategies has been significantly improved upon since it’s inception in the 1970’s, yet so many portfolios haven’t evolved with the research.

Suggesting a market cap weighted basic index portfolio is good enough, flies in the face of enlightenment. Research is meant to build upon itself. While I won’t knock investors who choose such an approach, I will knock those who suggest it’s good enough. For the first half of the 20th century either was a good enough surgical anesthetic and asbestos was a good enough building material.  All sciences strive to uncover evidence that helps to provide further understanding. Financial science strives to learn more about security prices and the forces that drive them.
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Your portfolio should evolve as research as research evolves. The Passive Investing vernacular really is a matter of semantics when you take into consideration the thousands of incremental decisions associated with investment selection, portfolio rebalancing and tax efficient application. WealthShape remains committed to the real life application of over 60 years of investment research. We believe our role is to take what financial science has given us, evaluate the strongest ideas and filter through thousands of solutions to find the best translation of those ideas. The result is broadly diversified portfolios that capture the power of naturally efficient markets and the factors that historically explain investment returns.

When news breaks and markets move, content-starved media often invite talking heads to muse on the repercussions. Knowing the difference between this speculative opinion and actual facts can help investors stay disciplined during purported “crises.”

At the end of June this year, UK citizens voted in a referendum for the nation to withdraw from the European Union. The result, which defied the expectations of many, led to market volatility as participants weighed possible consequences.

Journalists responded by using the results to craft dramatic headlines and stories. The Washington Post said the vote had “escalated the risk of global recession, plunged financial markets into free fall, and tested the strength of safeguards since the last downturn seven years ago.”1

The Financial Times said “Brexit” had the makings of a global crisis. “[This] represents a wider threat to the global economy and the broader international political system,” the paper said. “The consequences will be felt across the world.”2

It is true there have been political repercussions from the Brexit vote. Theresa May replaced David Cameron as Britain’s prime minister and overhauled the cabinet. There are debates in Europe about how the withdrawal will be managed and the possible consequences for other EU members.

But within a few weeks of the UK vote, Britain’s top share index, the FTSE 100, hit 11-month highs. By mid-July, the US S&P 500 and Dow Jones Industrial Average had risen to record highs. Shares in Europe and Asia also strengthened after dipping initially following the vote.
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Yes, the Brexit vote did lead to initial volatility in markets, but this has not been exceptional or out of the ordinary. One widely viewed barometer is the Chicago Board Options Exchange Volatility Index (VIX). Using S&P 500 stock index options, this index measures market expectations of near-term volatility.

You can see by the chart above that while there was a slight rise in volatility around the Brexit result, it was insignificant relative to other major events of recent years, including the collapse of Lehman Brothers, the eurozone crisis of 2011, and the severe volatility in the Chinese domestic equity market in 2015.

None of this is intended to downplay the political and economic difficulties of Britain leaving the European Union, but it does illustrate the dangers of trying to second-guess markets and base an investment strategy on speculation.

Now the focus of speculation has turned to how markets might respond to the US presidential election. CNBC recently reported that surveys from Wall Street investment firms showed “growing concern” over how the race might play out.3

Given the examples above, would you be willing to make investment decisions based on this sort of speculation, particularly when it comes from the same people who pronounced on Brexit? And remember, not only must you correctly forecast the outcome of the vote, you have to correctly guess how the market will react.

What we do know is that markets incorporate news instantaneously and that your best protection against volatility is to diversify both across and within asset classes, while remaining focused on your long-term investment goals.

The danger of investing based on recent events is that the situation can change by the time you act. A “crisis” can morph into something far less dramatic, and you end up responding to news that is already in the price.
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Journalism is often described as writing history on the run. Don’t get caught investing the same way.

​Virtually every investment disclosure includes some variation of the following statement: “past performance is no guarantee of future results.” Very few investors pay any attention to those words, but more should. Not only because they give further information about the data that’s being presented, but also because of the reason these statements are included. Is evaluating past performance the best way to select mutual funds?

​The research offers strong evidence to the contrary. This chart illustrates the lack of persistence in outperformance among US equity mutual funds. The funds are evaluated based on their 10-year track records (2001-2010), and those that beat their respective benchmarks are re-evaluated in the subsequent five-year period (2011-2015). Among the 2,758 equity funds that began the initial 10-year period, only 20% outperformed—and among these 541 winning funds, only 37% continued to beat their benchmarks in the subsequent five-year period.
 
Some US equity fund managers may be better than others, but this evidence shows the extreme difficulties in identifying them in advance using track records alone. Returns contain a lot of noise, and impressive track records often result from good luck. The assumption that past outperformance will continue often proves faulty and leaves many investors disappointed.
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Investment evaluation should embrace a variety of additional metrics including but not limited to the funds strategy: taking into account empirical rationale and economic intuition, cost, style drift and of course overall risk. It’s also critical that any evaluation take into consideration how your overall portfolio is impacted by the addition or subtraction of a fund. 

On June 23rd 52% of Great Britain voted to leave the European Union in a referendum, which subsequently triggered the resignation of European Prime Minister David Cameron. The slim margin of victory is an indication of how divisive UK citizens are on the topic. While there has been much speculation leading up to and since the vote, many of the longer-term implications of the referendum remain unclear, as the process for negotiating what a UK exit may look like is expected to be lengthy.

Initial market reaction to the news was typical of market reaction to uncertainty, with stocks and stock futures falling across the globe and safe haven assets, such as Treasuries and gold, rising on the news. The "leave" vote pushed the British pound to a 30-year low in the immediate aftermath. London and European markets also fell in reaction to the referendum, with the FTSE 100 and FTSE 250 down by about 7 percent each. Here at home, the S&P 500 was not immune to the volatility, dropping by about 3%.

Market forecasters largely got it wrong on the direction they thought this vote would go. In the days leading up to the referendum we saw European market appreciation in anticipation of a UK "stay" outcome. When it became apparent the vote would go in the other direction, the subsequent market reaction was similar to the typical reaction we've seen time and time again. Uncertainty causes stock prices to fall, and quality fixed income prices to rise.
 
Regardless of yesterday’s decision, in the short term we were likely to experience periods of market euphoria or uncertainty. Markets often react sharply. It’s happened many times before and much worse than this. We have nearly 100 years of evidence to support their resiliency. It’s important to keep in mind that the UK only represents about 6% of the world equity market capitalization. In contrast the United States represents about 52%. The entire European Union accounts for around 17% of the world’s economic output.
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Prognosticators will make sweeping statements in an attempt to garner as much attention as possible. We firmly believe that no one has the ability to predict the future when it comes to markets. A solid example is the failure of forecasters to predict this outcome. Markets move with new information. By definition news is unpredictable. When volatility shows up, prices move and not always in the direction you like them to. However, it's precisely that risk which investors have to accept for the expectation of higher long-term growth. 

The coming weeks, months and years are a far better barometer on the underlying issues that led to a Brexit referendum in the first place. The vote in and of itself demonstrates the level of attention to the issues facing Europe. Reacting to its outcome is not the proper course of action because future implications are impossible to predict. If you're portfolio is broadly diversified with exposure to multiple countries, sectors, industries and asset classes, you've already done everything you can to minimize the effects of Brexit and other expected events.