"It is possible to develop and employ quantitative equity models which possess the ability to produce superior rates of return. We build confidence in our Models through a process of continual backtesting and refinements."
While performance is the end we seek, it does not stop us from asking "why" a particular approach works. It is by asking this question that we develop a deeper understanding of how markets work, leading to more discriminating models and better performance.
This philosophy drives the proprietary investment approach discussed in this website. We believe the stock selections that emerge from our process are appropriate for consideration by the entire spectrum of professional managers.
We have demonstrated the ability to provide consistently attractive rates of return in both up and down market environments, and at acceptable risk/reward levels.
PROCESS
"The stock selection process has been thoroughly tested in the crucible of professional money manager review. For over 24 years, more than 150 of the finest minds in the investment arena have utilized our research to aid them in making crucial investment decisions."
Our research relies on pricing inefficiencies unmasked by 4 proprietary models:
MARKET PROFILE (detail)
It has become widely accepted in the past decade that over 95% of an investor's performance is due to style choices. The most common of style models produce a profile matrix made up of Value, Growth, Small Companies, and Large Companies. Our Style Model not only goes beyond this simplistic view by applying a broader spectrum of variables, but assigns forward probabilities to the nature of style. Market Profile Theorems has been a pioneer in developing Models that anticipate style and style changes.
INSIDER (detail)
Corporate management comprises the layer of knowledge most in tune with the corporate outlook. A thoughtful, comprehensive review of their buying and selling activity can provide the investor a ground floor entry into a better investment choice. The 7-factor Market Profile Theorems Insider Model has gained widespread respect over many years on Wall Street for its ability to separate wheat from chaff at the Individual Company, Industry and Sector levels.
EARNINGS (detail)
The Market Profile Theorems Earnings Model has shown a powerful ability to provide excess returns. Its 6 factor approach combines long- and short-term facets of earnings surprise and expectations yielding results that have matched or exceeded other earnings models available over the past 16 years.
TECHNICAL (detail)
Academic research has long suggested that the most consistent discriminator provided by analysis of Price and Volume is that of Relative Strength. The Technical Model provides the input that keeps the investor in stocks that are doing well and allows one to avoid those that have lost sponsorship.
SUMMARY (detail)
Combines all models to provide relative rankings for some 5300 publicly held US companies. Companies which: Possess style characteristics in-tune with the current market biases; Exhibit Insider Buying; Consistently exceed analysts expectations; and Outperform other stocks on a price basis, have a strong probability of continuing to do well. It is this profile that we seek.
Model Detail
In 1986, we began looking at the behavior of stock characteristics, such as PE ratio's, Price to Book, and Dividend Yield, relative to price performance. A research paper written in 1984 by Theodore M. Theodore then working at Morgan Stanley, Inc inspired this endeavor. He suggested that it might be valuable to analyze trends in the market pricing mechanism relating to common, corporate financial ratios.
Soon after we began our research, we realized that not only did there appear to be differing sensitivities among these characteristics or "factors", but also a trending mechanism and strong expression of the concept of "regression to the mean" appeared as dominant features. Studies on the relative performance of companies ranked by Market Capitalization are an example of this phenomenon. For example, extremely positive and negative correlation's of the stock characteristic with relative price performance are consistently followed by "regression to the mean," and beyond.
In building our knowledge database over the years, we developed "average" values for each of these characteristics which we currently use to find the degree to which the current months score for a factor is over/under valued. In the current Market Profile Model, a total of 10 "factors", of the 30 we track, are scored to create a ranking for each stock. Finally, these results are adjusted to reflect the current market bias.
We have also developed rules for evaluating the broad market bias for VALUE and EARNINGS DRIVEN/PRICE MOMENTUM markets using the cumulative, relative scores for each of the factors. Under the current rules, the broad market scores for these factors range from + 10 in a pure EARNINGS DRIVEN/PRICE MOMENTUM market, to a - 10, reflecting a pure VALUE market. Very simply, if the current adjusted score is typical of the first type of market, it is given a score of + 1; if it is typical of the second, VALUE type market, it receives a -1. The scores for all ten factors are then totaled. Secondary information is thrown off which helps us identify other markets such as Cyclical, Transitional, Moderate Earnings\Value etc. The probability that a market style will persist for the coming period is derived from a model that incorporates: Trending, Cyclical and Seasonal elements of style.
Volatility, while moderated by a 10-factor approach, is extreme in this Model. Interpretation is therefore supplemented (for the broad market only), by the degree of overall variation of the 10 factors from their historical means. In sum, the factor approach has been a valuable addition to the overall MPT, Inc. Summary Model. It kept us in position to take advantage of the EARNINGS GROWTH/PRICE MOMENTUM market for the 36 months prior to February of 2000, and which began a consistent turn to VALUE through the spring of 2006. Not only did it suggest that we were moving into a VALUE mode in the broad market sense, but it selected more stocks and industries that had VALUE characteristics. More recently the model reflected the GROWTH bias of 2006 - 2007.
There is no doubt that more can be learned from the "factor" approach to stock selection. We intend to continue to be at the forefront of research in this area, and add to our client's performance and understanding of the markets as a result.
"Insiders Buying And Selling Of Their Own Company Shares."
The basic assumption underlying Insider research is that individuals who are running Corporate America have a special understanding of their company fortunes. As a society, we have decided that while allowing these persons to buy and sell publicly held stock creates the potential for abuse, it is a healthy expression of the entrepreneurial spirit to encourage them to participate in the fruits of their labor. Investors take it as a healthy sign that the people who are running the company, own stock in it. Society is not totally naive however, and has placed constraints on this "inside trading." For example, an Insider must now declare open market transaction(s) within 40 hours of the event. A second rule prohibits the insider from selling stock purchased in the open market within 6 months of the date of purchase, and profit from the trade. The guiding principle is that Insiders are prohibited from trading on "inside information." The protection afforded the investing public is theoretically greater for insider buying than selling. The "6 month rule," and reporting deadlines on purchases, limits the edge that the Insider has on other investors. Rules regarding insider selling based on inside information in front of bad news are less protective, as only the reporting requirement protects the investing public. The authors believe that most persons would agree that, on average, people who work for a company understand the prospects for that organization better than most other investors.
Development of the Insider Model was begun 36 years ago, and used at Market Profile Theorems for the last 24, was based this last point. Support for or against that concept was sought in academia. From this source certain clues emerged: The position of the insider within the firm, the number of shares transacted, the type of transaction (sell or buy), original purchases versus subsequent ones, and the number of transactions were all factors that should be considered in an Insider Model. In addition, both academic studies and the authors' research suggested that the amount of time from the transaction date had an impact on performance, and that the impact of the passage of time varied for sells and buys. More recent research indicates that performance can be improved by including sales as a % of holdings.
Insider activity data and its interpretation have clearly changed over the past 35 years in which the authors have been involved. For example, the quality of the data has improved dramatically. One of the problems inherent in analyzing insider activity is that the data relies on so many inputs before it gets to the modeling level. The Insider must report the transaction in a timely manner. He or she must know how to fill out the SEC reporting forms properly (before you react to that improbability, consider the estimated 20% error rate in filling out the IRS form 1040EZ). A government worker must then transpose the form to computer, etc.
A second problem, inherent in the early work, was that of the insider filer not taking the task seriously. Recently, reports seem to be filed in a much more timely manner with fewer, older transaction dates seen in the data. This trend has accelerated and seems to coincide with some of the changes in reporting requirements instituted early in 1992. This increases confidence in the data on which the models are based.
Not only is the data may be in better condition, it is the author's sense that insider modeling has lost none of its luster. That is, knowledge of insider transactions, as reported, produces better or equivalent performance advantage to the investor today as it did 25 years ago. MPT has moved beyond more simplistic Insider models and combinations with it: 1) Developing more sophisticated "black box models"; 2) Developing a more discriminating sense of what is important in insider activity for individual stocks; 3) Gaining additional value from insider models by combining them with other models such as the MPT, Inc. Earnings Expectational and Technical Models -- yielding performance better than the model used alone, 4) Analyzing derivative insider activity at Industry or Sector levels and; adding value by comparing current to standardized insider model scores.
The Insider activity Model adds value in excess of its stand-alone performance to the overall Summary, Earnings and Technical Models. In addition, as many clients will attest, our ability to subjectively analyze gross inordinate insider activity correctly, has been invaluable in controlling risk, leading to better risk-adjusted returns.
"Consensus Earnings Estimates By Stock Market Analysts."
The group of individuals second closest to the fortunes of publicly held companies are the analysts who work for brokerage firms, banks, money management firms or private research boutiques. These analysts provide research to clients (both institutional and retail), to their investment banking arms, and to each other. Studies on the information content of earnings estimates, both immediate and long term, have found residual value in acting on certain configurations of their estimates. The residual value, (excess over or under performance), has been generated by two classes of data provided by analysts: 1) The degree to which the estimates are different from the reported number; and 2) The direction of analyst estimates.
Three researchers, Latne, Rundelman, and Jones, at the University Of North Carolina and Duke did much of the pioneering work on estimates as a guide to future performance. While others concentrated on simple earnings surprise (the percent difference in the mean analyst earnings estimate and the actual earnings at the time of the reported earnings), these individuals put forth the more sophisticated concept of Standardized Unexpected Earnings (S.U.E.). S.U.E. compares the mean earnings estimate over a period of time before the estimate, to the actual earnings reported, and then standardizing it statistically (dividing the result by the standard deviation of estimates). The results of this approach astounded the investment community and gave legitimacy to several firms providing mean analyst estimates to the investment public. The most prominent of those names today are Zacks Investment Research, I/B/E/S, and First Call. In sum, research suggested that, the degree of difference between the estimate and the actual earnings number is roughly proportional to the relative price move in the stock. While this result is not unexpected, what was surprising was that relative price performance persisted in the same direction (but with lessening impact) for many months after the disparity was revealed. Accordingly, an investor could take long term advantage of an earnings announcement. There are many corollaries to this concept, all serving to lessen the strength of the strict form of the efficient market hypothesis (EMH). For example, residual value has been found in the direction of mean analyst estimates, and in simple, quarterly earnings surprise.
The authors have some insights as to why this phenomenon works. Important factors include the psychological phenomenon of Cognitive Dissonance and the Political Nature of the analysts' decision making process. Cognitive Dissonance refers to the refusal of an individual or group with an established opinion to accept another point-of-view, in spite of new irrefutable evidence suggesting quite another conclusion. The stronger their original opinion, the more resistant they are to changing it. Further, whether in science, politics, or the investment world, the more highly regarded the person providing the opinion, the greater the Cognitive Dissonance of the majority accepting the opinion. In the investment community, not only are analysts unwilling or slow to change, but investors who rely on high profile analysts are as well. We believe this phenomenon creates prolonged inefficiency in the pricing mechanism of the stock market. The Political Nature of the analysts' environment works to create inefficiencies generated by earnings surprise. (We won't include the impact of what we believe is a mythical wall between investment banking and stock recommendations.) Very few investors have the psychological make-up to admit they are totally wrong. This applies to analysts as well, except that to do so might add the ignominy of putting their credibility and therefore, jobs on the line. Analysts will gradually cut back or increase estimates over a period of time following strong disparity between estimates and actual earnings. This tends to prolong disappointment/optimism which creates longer-term pressure on prices in the corresponding direction. Evaluation of trends in the direction of estimates provides evidence that this type of activity is occurring and can also be used to anticipate reversals in trends (when the trend slows or reverses), etc. The decisions the analyst community is making are very human. In expressing their humanity and reflecting their political environment, they create investment performance opportunities that can be acted upon. This model has provided excellent results over the past 24 years.
"Beyond Tea Leaves"
The explosion in the variety of technical analytic techniques over the past 24 years has been truly astounding. This has been driven in large part by the development and distribution of computer and communications technology which has allowed for virtually instantaneous transmission of transactions taking place anywhere in the world to trading rooms, offices, and homes. Further, once received, individuals now have the power to process the information in an infinite array of algorithmic combinations, and have access to communications channels through which to act (trade) on their conclusions. It is a commonly expressed sense amongst senior money managers that pricing processes which, 35 years ago took weeks to wash through the marketplace, now take hours. In this environment it is easy for managers' to feel overwhelmed. We have constructed our Technical Model simply and with a longer term, "portfolio managers time horizon," in mind.
Most technical models fall into 2 categories; pattern recognition, and analysis of price and volume. We suppose one could argue they are one in the same, and indeed with the application of computers to "pattern recognition" the boundary has become blurred. Three models come to mind in the area of "pattern recognition" -- Edwards & Magee's, Elliot & Prechter's, and the Market Profile proposed by MARKET PROFILES (Chicago), and used on the CBOT by many traders. Examples of Price and Volume approaches would include Price Trending Models, Overbought/Oversold Models, Stochastics, Parabolics, Regression Models, Moving Averages, Envelopes, DMI, ADX, Bollinger Bands, MACD, RSI, On-Balance Volume, Divergences, Chaos Theory, etc.
The fact that there are so many approaches suggests that either no one approach works or that they work only some of the time.It is clear that each model works some of the time. It therefore remains to find the model that is the most consistent. Market Profile Theorems has chosen the approach that relative trends in price behavior posses the most consistent, risk adjusted, technical performance. While not spectacular, trend following models, used in the right market (non-consolidating types), offer a good deal of consistency. Given the general long-term tendency of the equity markets to "trend higher" the odds would favor this type of approach in the long run. We have combined this concept with a Technical Model for individual stock selection that evaluates relative price strength over 4 week, 12 week, and 24 week time periods. In addition, we evaluate volume over the 2 most recent 4-week periods. The ideal stock from our perspective has positive relative strength for all three periods on increasing average volume.
While this Model has not been the most spectacular of the individual MPT, Inc. approaches, it has lent stability to the Summary Model and improved the performance of both it and other models combined with it. The Technical/Insider combination has proved especially powerful and as a result we present each month those companies which score best using this combination of Models.
"The Whole Is Greater Than The Sum Of It's Parts"
A manager of investments is ultimately judged by his/her ability to win above average returns for their clients. It is no different in the management of equities in particular. According to a survey done for Pensions & Investments by Richard Carton (Aug. 3, 1992), plan sponsors score performance highest at 8.6 on a 10 point scale. Quality of Personnel & Firm Reputation score 7.8 and 7.5 respectively, while fees were valued at 6.6 out of 10 in importance in the selection of a manager -- turnover was not evaluated.
It is against the unrelenting expectation of superior performance that the investment management community has labored over the past 24 years. The Rock of Sisyphus has become larger, and the hill steeper during this period. Rotation of group/sector performance has been unruly, margins slimmer across the entire investment community, and investors increasingly jaded by the extraordinary gains, exceeding 800%, experienced from 1982 to 1997 (DJIA 750 to 7000). Over the last 24-year period, the Market Profile Theorems Summary Model has been available to the investment community, providing calm, relative performance gains in the eye of the swirling investment hurricane.
The reasons for this exceptional and steady performance are related to the concepts that drive the Summary Model. They are:
- There is an informational hierarchy in the marketplace for stocks that cannot possibly, in a practical sense, be known, understood, and acted upon at the same time by the investment public. (Insider and Earnings Expectational Models).
- Human beings, and the psychology that drives them, is a major factor in setting prices. For example, investors tend to ignore initial and surprising bad news, and in fact are paralyzed by it. (Earnings Expectational Model).
- It is important to understand the factors that are driving stocks as they relate to those components by which we measure fundamentals such as PE's, Earnings Growth, & Dividend Yield, Etc. (Market Profile Model, Technical Model).
- Markets' trend in the long run. (Technical Model, Market Profile Model).
- Markets revert to the mean. (Market Profile Model, Insider Model).
- Relative strength is important. (All Models).
While the Market Profile Theorems approach has proved valuable over the past 24 years of actual implementation and 30-Years of theoretical testing, we realize we may have only captured a healthy slice of performance time. We have selected models that contain information content that transcends performance time slices. In other words, those that do well in most market environments.