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Terminology within the investment industry is a barrier to clarity.  The ambiguity of terms causes investors at all levels of sophistication to misinterpret and miscommunicate.

In some cases, this is because a term has multiple meanings, and in other examples, the term’s reference has changed over time.  This is not your standard glossary.  Given the ambiguity of terms, we thought it might be valuable to provide our take on several of these industry terms as a way of revealing more about our own approach to investing.

Absolute and Relative Return

These terms describe different perspectives by which an investor assesses the success of their portfolio. Relative return compares performance against a specified index whereas absolute return is a targeted premium above yields on cash or inflation that is deemed appropriate given the risk and expected time horizon of the portfolio (eg. CPI plus 5%). Absolute return is the ultimate goal for most investors.  Relative return is important based on a crucial assumption, which has been accurate over most medium-term time periods, that equity and fixed income indexes will generate attractive absolute results. The distinction becomes highly relevant because managers whose strategies focus solely on relative return (i.e., define risk as potential deviations from an index) limit their ability to generate acceptable absolute returns when the markets/indexes produce poor absolute results.


It has become common to attempt to define risk with a single concept or even a statistic. The reality is that risk is a multi-faceted term broadly meaning the probability of a negative surprise. These surprises can come in the form of an absolute loss or an opportunity cost – a shortfall relative to other investment options.

Identifying which of these perspectives on risk is the most important is a personal decision based on investor temperament, circumstances and time horizon. And, the specific strategies selected to protect against these individual risks are often mutually exclusive. Quantitative measures of risk, such as price volatility and tracking error (volatility relative to a benchmark) measure historic results. In that risk can be measured in the past but only exists in the future, we regard these metrics more as clues than answers. And as you might expect, we believe any valid assessment of risk must incorporate a sense of price relative to value.


If you accept the notion that, due to the nature of pricing in the capital markets, even your best individual ideas can be wrong, then it is wise to spread your investments. Diversification has been described as one of the few “free lunches” in finance because as you combine investments with different levels of correlation (the tendency for assets to perform differently from one another), there can be a reduction in total portfolio price volatility. Diversification can take many forms – examples include spreading investments over a range of individual stocks, asset classes, countries, investment styles and methods of decision making. Two caveats: over-diversification results in limiting the manager’s ability to translate skill into results (at high fees too), and in bad markets, there is a tendency for correlations to rise and the benefits of diversification are reduced when needed most.

Asset Allocation

Given that asset allocation is generally regarded by investors as the most crucial decision they make in determining their prospective risk and return, it is paradoxical that there is a lack of agreement on what it means. First, there are significant differences in how asset classes are identified as some investors operate with two to four broad categories of investments and others are more granular and specialized in their identification of 10+ different asset classes. Second, asset allocation can refer to a policy allocation which is a long-term target based on the needs and risk tolerances of the investor, but can also be used to describe active changes to allocations based on the current environment and perceived opportunities which are frequently termed tactical asset allocation.

An investor’s relative reliance on policy or tactical allocation is, consciously or sub-consciously, based on a confidence in their or their advisor’s ability to project medium-term prospects for asset classes that vary from long-term expectations.  As a rule of thumb, the more asset classes that are identified and the more the reliance on policy allocation, the more rigid the portfolio structure and strategy.   Tactical allocation is difficult, and timing is rarely perfect at any specific point in time, but it is the only conventional way to protect assets in bad markets.

Balanced Portfolio

A portfolio that combines multiple asset classes with differing risk levels such as stocks, bonds and cash.

Time Diversification

The notion that the longer the time horizon, the greater the probability that actual results will be in line with expectations.  To the extent that this concept is valid, investors with longer time horizons have the capacity to incur greater risk today to achieve higher returns over time.

Fundamental and Technical Analysis

Two very different approaches to investment research and decision-making.  Fundamental research focuses on assessing variables that impact the economics of an investment. These can be macro factors such as GDP growth and changes in interest rates or company specific factors such as product demand, quality of the balance sheet or margin and cash flow trends. Technical analysis studies the historical pattern of a stock’s price and volume to project future prices.  Investors who follow technical disciplines generally have little interest in the fundamental factors of a company’s business.

Momentum Investing

A form of technical analysis that follows the belief that objects in motion tend to stay in motion. Therefore, buy investments that are rising in price.

Market Timing

A similar objective to tactical asset allocation, the goal being to shift between risky and low risk assets in an effort to capture returns during good markets and protect wealth in bad markets. Although distinguishing between these two terms is fuzzy at best, the industry generally refers to market timing as being  shorter term oriented, and thus, more difficult to do effectively.

Quantitative and Fundamental Investing

In its simplest form, quantitative investing is a decision-making process where every concept is expressed as a number. The practice of quantitative investing is tied to technological advancement as the 1970’s brought computers into the industry. Quantitative research has multiple applications; including identifying favorable stock characteristics and screening a universe of companies to quickly identify which companies meet these objectives, combining securities into an optimally diversified portfolio and risk management.  Investment managers use quantitative methods in varying degrees as some use these tools as a part of their approach and others use these methods as an automated decision-making process.

Fundamental investing, as previously defined, focuses on assessing a wide variety of macro and micro variables that impact the economics of a business.  Quantitative and fundamental investing is frequently referred to as apposing approaches. We disagree. Quantitative investing is often simply a formulaic combination of fundamental criteria. Qualitative investing, on the other hand, is where research is less rigidly structured and key variables are more customized to fit the idiosyncrasies of a specific investment.  This is more the “flip-side” of a quantitative approach.

Meritage’s approach to security research is highly quantitative; however our process is not a black box (automated) process.  Rather, we overlay qualitative judgment in making final decisions regarding all aspects of portfolio construction.


If you accept that investing is an exercise in probabilities and that success is based on the odds of being correct in your individual security selections, times the number of independent investment decisions you make (breadth), then the concept of breadth becomes an important variable. A focus on a low breadth decision, such as the choice between stocks and cash, would be more difficult to get right and consistently add value with than a higher breadth activity, such as selecting 50 stocks out of a universe of 6,000.

Top Down and Bottom Up Investing

Top down strategies attempt to identify and allocate assets to “categories” of securities such as sectors, industries, or countries based on economic or thematic projections. Bottom up investing focuses on analysis of and selection of individual companies based on their own merits.  A company’s management, business model, financial conditions and growth prospects are deemed to be more reliable predictors of investment success in bottom up investing than its membership in a favorable category or theme.   Top down investing is a lower breadth activity than bottom up investing as the options are fewer.

Bottom up activities dominate our research efforts at Meritage, however we recognize that there are unique periods when the economy or specific industries are entering important transition points where broad thematic projections take precedence in our decision-making.

Growth and Value Investing

As investors naturally seek to simplify investment complexity, they have attempted to categorize managers by investment style. Growth and value strategies have become the lead examples of style. Growth investing is fairly straight forward and valid. It involves owning companies expected to grow earnings and cash flow at rates above the broad market.  Growth investing has historically focused on companies in technology, healthcare and consumer service sectors.  These companies are generally priced at premium multiples to the market which makes them highly vulnerable to earnings disappointments.  Value investing is less precise as an investment description. Though many in the industry term value investing as owning low expectation companies with cheap stock prices, we believe the concepts of growth and value are not mutually exclusive – rather, stocks across the entire growth spectrum should be assessed based on their relative price to value.

Mean Reversion

The concept that financial variables such as stock prices, corporate profits and market returns, all have an identifiable “equilibrium value,” and that when they go to extremes, high and low, the odds favor a reversal.  Mean reversion disciples (the opposite of momentum investing) would suggest that investing in distressed or low growth stocks is less risky and probably more lucrative than investing in high growth stocks.

Asset Capacity

Most managers agree that generating good performance becomes more difficult as assets under management grow.  The concept is sort of an investment version of the Peter Principle as more assets can dramatically reduce the universe of companies that can be owned, limits flexibility and raises the cost of trading.

Market Cycle

A nebulous time period, generally tied to the business cycle or a combined bull and bear market for stock prices. Managers refer to a market cycle as the length of time required for their investment skill to generate superior performance. This period generally “ball parks” around 3 to 5 years, although recent cycles have been less uniform in their duration.

Portfolio Turnover

The amount of trading in a portfolio (generally on an annual basis) calculated as the lower of the value of purchases or sales divided by the total portfolio value.  Turnover generally is correlated to the manager’s investment time horizon regarding how long they project it to take for their investment thesis to materialize.   High and low turnover strategies are both capable of generating good returns, although high turnover approaches incur higher costs for the strategy to overcome.

Behavioral Finance

The study of how investors make decisions is called behavioral finance (or behavioral economics).  It is the acknowledgement that investors are influenced by environmental and psychological factors in their decision-making and as such, do not always act rationally.  In the quest to understand why this is, research has shown that irrational decisions can be systematic and predictable.   Even more interesting is that the exposure of flawed decision-making does not necessarily lead to a change in behavior.  Overconfidence, for example, is widely accepted as a cognitive bias that can lead to sub-optimal decisions, yet it is more easily recognized in others than it is in ourselves.

The core principles of behavioral finance conflict directly with classical economic theory that holds that markets are efficient.  Behavioral research has helped explain the existence of market anomalies that are implausible in the efficient market world.   Market bubbles and crashes are the best example of real world phenomena that can’t be modeled in an efficient markets framework.

The findings of behavioral finance are consistent with our value-centric beliefs.  We observe that stock prices fluctuate more widely than the true value of underlying companies, largely because of investor overreaction to short-term information.   It is the exploitation of these irrational judgments that createperformance opportunities.

Modern Portfolio Theory (MPT)

A collection of academically derived theories, developed primarily between the mid 60’s and the mid 70’s that have meaningfully impacted the approach to investing and the understanding of risk.  These theories are based around the notion that markets are generally efficient (incorrect) and that overall risk can be reduced by combining different assets with low correlations (correct).  The relationship between risk and return is mathematically determined and the price of a stock is largely a function of the volatility of the stock in relation to the broad market.

In recent years, MPT has been challenged by anomalies in market behavior that seem better explained by the theories of Behavioral Finance (see above).  The investment philosophy of Meritage is built around the recognition that stocks are often mispriced because investors do not always act rationally, something that is not recognized by the MPT model.   Also, the premise that risk is singularly defined by volatility falls short in explaining how investors think about risk and how returns are often loosely

Hedge Funds

A vague term in practice because it refers to a highly disparate assortment of strategies, risk levels, and asset class exposures.  Hedge fund commonalities include the use of a partnership structure, the desired objective of generating positive absolute returns regardless of the market environment, an above-average degree of investment flexibility, and, perhaps the most distinguishing factor, a fee schedule that allows for the manager to participate in a meaningful percentage of the client’s return.

Tracking Error and Information Ratio

Tracking error is a risk measure that focuses on a portfolio’s projected range of performance relative to its targeted benchmark.  The information ratio is a risk adjusted measure that assesses performance based on excess returns relative to volatility of returns around the benchmark.

Standard Deviation and Sharpe Ratio

Standard deviation is a mathematical risk measure focusing on the volatility of absolute returns.  Often used as the primary measure of risk, it does not distinguish between the volatility that investors like (up markets) and the volatility that investors try to avoid (down markets).

The Shape Ratio is a method for risk adjusting the results of a portfolio to assess returns above Treasury Bills relative to the volatility of those returns.

This glossary is a work in process.  We welcome your input to enhance our definitions and the inclusion of new investment terms we should add to the list.