As of 11/20/2024
Indus: 43,408 +139.53 +0.3%
Trans: 17,002 -26.31 -0.2%
Utils: 1,055 +1.25 +0.1%
Nasdaq: 18,966 -21.33 -0.1%
S&P 500: 5,917 +0.13 +0.0%
|
YTD
+15.2%
+6.9%
+19.7%
+26.3%
+24.1%
|
 46,000 or 43,000 by 12/01/202418,000 or 16,600 by 12/01/20241,075 or 1,000 by 12/01/202420,000 or 18,400 by 12/01/20246,100 or 5,800 by 12/01/2024 |
As of 11/20/2024
Indus: 43,408 +139.53 +0.3%
Trans: 17,002 -26.31 -0.2%
Utils: 1,055 +1.25 +0.1%
Nasdaq: 18,966 -21.33 -0.1%
S&P 500: 5,917 +0.13 +0.0%
|
YTD
+15.2%
+6.9%
+19.7%
+26.3%
+24.1%
| |
|
46,000 or 43,000 by 12/01/202418,000 or 16,600 by 12/01/20241,075 or 1,000 by 12/01/202420,000 or 18,400 by 12/01/20246,100 or 5,800 by 12/01/2024 | ||
This page explores the price trend over the prior year and determines how likely price will rise or fall over the coming three months and by how much.
By looking at the price trend over the prior 12 months, 3 months, and month, the average rise or decline in the coming three months can be determined, as well as how often the stock actually meets price targets. This page takes a closer look at research that explains how this works.
Ford Equity Research, in their stock reports, mentions a momentum indicator. They write,
"Large price movements over the intermediate and short term tend to reverse themselves. Ford's price momentum measure integrates historical long and short term price changes creating ratings that are highest for stocks with strong twelve month price performance that have a price consolidation in the past quarter and especially the past month."
The results describe three measurement periods, 12 months, quarter (3 months), and month, and then describe the likelihood of an above average rise in price during the next 1 to 3 months. This page begins the effort to duplicate those results and perhaps to develop a trading strategy that incorporates prior price movement into future results.
I created a database of 562 stocks with data starting from April 1, 1996 to July 27, 2008. The actual range of data used for the test was from May 1, 1997 to May 27, 2008 to allow room for a 12 month look back at the start and a 3 month look forward at the end. That will make sense in a moment.
In the test, I measured the close to close percentage price change from the start of the month to the end (close of day 1 to close of the last day in the month), then did the same for the prior quarter (current month plus the prior 2) and year (current month plus prior 11).
I saved the three percentage changes and then did the same calculation each month, for each stock, until the end of data. The dates chosen were used because they almost filled a spreadsheet with samples and it included both bull and bear markets. I define the bear market as the decline in the S&P 500 index from March 2000 to October 2002. Everything outside of those dates represents a bull market. I did not factor in the state of the market (bull or bear), but I wanted to include both.
After collecting the data, I sorted the results according to the price trend over the three time periods and found the highest high and the lowest low posted during the next 3 months. The following section shows what I discovered.
Table 1 shows a partial list of the results (click here for a complete list, as an Excel spreadsheet). Despite having 65,420 samples available, not all combinations yielded enough data to be useful, so I excluded all rows not having at least 300 samples.
| 1 Month | 3 Months | 1 Year | Sample | Avg Rise in | Avg Drop in |
| Look Back | Look Back | Look Back | Count | Next 3 Months | Next 3 Months |
| Down | Down | Down | 10,485 | 24.5% | -17.2% |
| Up | Down | Down | 4,304 | 23.3% | -15.3% |
| Up | Up | Down | 5,106 | 20.4% | -13.0% |
| Up | Up | Up | 20,671 | 20.0% | -14.5% |
| Down | Up | Down | 2,956 | 20.0% | -15.6% |
| Down | Down | Up | 8,345 | 18.4% | -13.6% |
| Down | Up | Up | 8,216 | 17.8% | -12.8% |
| Up | Down | Up | 4,492 | 17.0% | -12.8% |
The table shows the price trend over 1 month, 3 months, and year, either up or down, followed by the number of samples that matched the trend behavior, plus the average rise and decline over the next three months. For example, the first row of numbers shows that if the trend is down during the last year, quarter and month, price tends to rise an average of 24.5% during the next three months and falls an average of 17.2% during the same period. The last row in the table shows that when price over the year and month are up but fell during the quarter, the average rise and decline in the coming three months averaged 17% and 12.8%, respectively.
How is this useful? If you look at the price trend over the past month, 3 months, and year, you can get an idea of the likely direction and magnitude of price change in the coming three months.
| 1 Month | 3 Months | 1 Year | Max Rise in 3 Months Exceeds | Max Drop in 3 Months Exceeds | ||||||||
| Look Back | Look Back | Look Back | 5% | 10% | 15% | 20% | 25% | 5% | 10% | 15% | 20% | 25% |
| Down | Down | Down | 82% | 67% | 53% | 42% | 33% | 77% | 58% | 45% | 34% | 25% |
| Up | Down | Down | 83% | 67% | 53% | 41% | 32% | 73% | 55% | 40% | 29% | 20% |
| Up | Up | Down | 82% | 56% | 46% | 32% | 25% | 73% | 53% | 38% | 26% | 18% |
| Up | Up | Up | 82% | 52% | 39% | 30% | 20% | 70% | 47% | 31% | 20% | 13% |
| Down | Up | Down | 76% | 58% | 43% | 33% | 25% | 75% | 56% | 42% | 29% | 20% |
| Down | Down | Up | 79% | 59% | 42% | 30% | 22% | 72% | 51% | 35% | 24% | 16% |
| Down | Up | Up | 77% | 56% | 40% | 29% | 21% | 70% | 49% | 33% | 21% | 14% |
| Up | Down | Up | 77% | 56% | 40% | 28% | 20% | 69% | 48% | 32% | 22% | 14% |
Table 2 is similar to the prior one, but it shows how many times price peaked or declined in the next 3 months by at least 5%, 10% and so on. For example, when price trended downward for the year, quarter and month, 82% of the stocks meeting those conditions climbed at least 5%, 67% climbed at least 10%, and 53% climbed at least 15%. And so on.
For declines, using the same row, the maximum drop in the coming three months from stocks that were down for the year, quarter, and month, showed that 77% dropped at least 5% in the next 3 months, 58% dropped at least 10%, and (skipping a few) 25% dropped at least 25%.
The results show that the number of stocks exceeding their upward price targets were higher than those dropping below their downward targets. That means it was more profitable to be long than short. Whether this trend will continue for future markets is unknown, but the large sample counts for the entries shown suggests it will.
Let's take an example to see how this information may be useful. Since we are dealing with probabilities, anything can happen, so keep that in mind.
I show a chart of YRC Worldwide on the weekly scale. Let's assume that the vertical green line represents the current day. A year before point D, price started a decline at point A. Three months before D I show that as point B. The 1-month look back begins at C. Notice that all three points, A, B, and C are above D. Thus the price trend is downward leading to D for all three look back periods.
Table 1 says that for price trending downward for all three periods, price rises an average of 24.5% and declines an average of 17.2% in the next 3 months. In this example, price bottomed at E, 15.3% below the close at D and then climbed to a high at F, or 49.1% above the close at D.
The second table shows that a decline of 15.3% happens about 45% of the time, but a rise of 49% is rare (not included in the table). I recalculated the results and found that a 49% rise occurs just 12% of the time.
Using this method is simplicity itself but please remember that you are dealing with probabilities, so anything can happen. Here are the rules.
-- Thomas Bulkowski
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