Price momentum

This is a small article.  From Dorsey Wright research.  Requiring additional research on my part.  I will try to do that and add more to this post.  For my benefit.

More Supporting Data For Momentum

The WSJ reports the performance of Sam Eisenstadt’s, former head of research at Value Line, stock-ranking system from 1965-2012.

Though the system is proprietary, its two primary factors are known as “price momentum” and “earnings momentum.” A stock is ranked higher to the extent its performance over the trailing year has been good and its earnings growth has accelerated. Despite the name “Value Line,” the stocks it favors fall closer to the “growth” end of the spectrum.

The system has been phenomenally successful over the past five decades. From 1965 through 2012, according to data on Value Line’s website, Group 1 stocks on average have gained an annualized 12.9%, before dividends. That’s nearly seven percentage points per year better than the S&P 500′s 6.1% annualized return over the same period, and more than 22 percentage points ahead of the minus 9.8% return for Group 5.

Once again, the data confirms the effectiveness of price momentum.

Diced into smaller pieces, from Mark Hulbert:

The system has been phenomenally successful over the past five decades. From 1965 through 2012, according to data on Value Line’s website, Group 1 stocks on average have gained an annualized 12.9%, versus minus-9.8% for Group 5 — an average spread of more than 22 percentage points a year.

In recent years, however, the Value Line system has struggled. The advantage enjoyed by Group 1 over Group 5 has narrowed considerably. Over the past decade, it has been just 11 percentage points a year, on annualized basis; in the 1970s, for example, it was three times greater.

Yet its recent performance is still impressive, according to David Aronson, a former finance professor at Baruch College and currently president of Hood River Research, a quantitative-analysis firm in New York. “Indeed, quants on Wall Street often celebrate when they discover a stock-selection system that can identify a performance differential of just a few percentage points between different groups of stocks,” he says.

Eisenstadt says that, given the initial success of his system, it was inevitable there would be at least some narrowing of Group 1’s advantage over Group 5. “A successful strategy typically weakens as more and more investors start following it,” he says.

I think these are actually quoting the same article originally in WSJ.

Interesting interview from April 2012, talks a little more about analysis of stock market data in general:

Special Meet of QWAFAFEW, New York
April 16, 2012

Question: Please describe the circumstances that lead to the development of the Value Line Timeliness Ranking System. What needs were perceived to need addressing? When it started, did you have any idea how long it would take to complete?

Answer: No, it was an open-ended research project for us. The purpose was to produce an improved system. We noticed that interrelationships between highly related variables frequently caused factors to drop out of regressions. An example of this was IBM, a consistently up-trending stock, where the lagged price became the most important factor.

Question: The academic literature references relative earnings and price ranks, EPS growth, price momentum, and earnings surprise as being factors in the model. It has also been noted that Value Line was the first known system to use earnings surprise as a factor. How did this factor become a part of the system?

Answer:  A physics professor from Brooklyn Polytech, Professor Fabricant had detected that whenever an analyst’s earnings projection (next 12 months) was raised, the relative price action of the stock subsequently improved. The question became: “How could we take advantage of this action in the Ranking System?” We believed that by examining the reason for the revision, we might improve the System. We found that, more often than not, the revision took place after an earnings release.  Thus, by evaluating the earnings release, we could get a jump on the analyst revision itself. Hence the birth of the earnings surprise factor. It was tested, found significant, and introduced into the system prior to anyone else’s use of this factor (to the best of our knowledge).

Question: The first famous article about the Value Line ranking system as an “anomaly” to the Efficient Market Theory being trumpeted by academics was called “Yes, Virginia, There Is Hope; Tests Of The Timeliness Ranking System” by Dr Fischer Black. Could you tell us how the article came about; what assistance you provided in helping him perform his tests, and any other things you think we might find interesting?

Answer: Dr. Black was invited by Arnold Bernhard to test our ranking system using any procedures and tests that he could think of. The result was “Yes Virginia, There Is Hope;”. Value Line provided the computer power and Fischer was paid for his efforts. Several professors at the University of Chicago claimed that Dr. Black was “paid and quartered by Value Line”, thus suggesting that his results were biased towards a favorable outcome for Value Line. Subsequent results of the ranking system for many years would appear to have validated Fischer Black’s conclusions. Indeed, Value Line’s ranking system results might have resulted in some modifications in the Capital Asset Pricing and Efficient Market discussion!

Question: Why do you enjoy tinkering with data so much?

Answer: I was always looking for numerical solutions to stock price forecasting. Discovery of statistical solutions and significance, particularly in stock price forecasting provided a thrill – even if only a momentary one, at times. It shed a bit of light on the darkness that enveloped the subject. I think the thrill would have been there, even if the subject under investigation were other than stock prices.

Question: What other ranking systems and models have you been involved in testing and attempting to develop over the years?

Answer: I’ve developed a technical ranking system. Most technicians do not use statistical methods to construct and test their systems. This is one field that requires such testing since much of their beliefs are not justified by mathematical verification. The technical system provides a small amount of explanatory power with mixed results, particularly in recent years. Relative strength is the primary tool, but applied using multiple regression techniques. Also, in the early years, a model was constructed in order to assign quality grades to companies based upon growth and price stability.



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