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 12/01/2024
18,000 or 16,600 by 12/01/2024
1,075 or 1,000 by 12/01/2024
20,000 or 18,400 by 12/01/2024
6,100 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 12/01/2024
18,000 or 16,600 by 12/01/2024
1,075 or 1,000 by 12/01/2024
20,000 or 18,400 by 12/01/2024
6,100 or 5,800 by 12/01/2024
|
|
Bulkowski on Testing Short Patterns
Initial release: 9/3/24.
Small Pattern Testing Methodology
Instead of repeating the testing methodology for every small chart pattern I test, I created this page. Here I outline the rules I followed.
- I placed a minimum price of $5 on stocks only (not on ETFs (exchange traded funds), and crypto currency at the time the pattern formed). If the stock's price was below $5, I ignored the trade because I don't trade
penny stocks (oddly, that's what they are called when price below $5).
- Stocks began with data in 1990 and continued through most of August and into the start of September 2024, but not all stocks covered the entire range. ETFs and crypto currency had less data.
- I used a target (sell price target) that was twice as tall as the chart pattern (from highest high to lowest low). This should give a profit to loss ratio of about two to one. If the
security reached the target, I sold it either at the target price or the opening price if it was higher.
- I used a stop loss placed a penny below the chart pattern's lowest low. If the stock reached the stop value, I exited the target either at the stop price or opening price, whichever was lower.
- Each trade bought $10,000 worth of shares. I allowed fractional shares on ETFs and crypto currency, but not on stocks.
- I assumed no commissions. That's fine for stocks and ETFs but not crypto (which has fees). I ignored commissions, regardless.
- I ignored slippage, SEC fees, and other trading costs.
- I computed the high-low range in each of five days before the start of the pattern and used linear regression on those values to determine if the price trend was up or down.
This method appears to work well to determine the very-short term price trend preceding the start of the chart pattern
- I did not log securities with the following: no breakout or a breakout in both directions on the same day, a zero opening price (very old quotes might have this because of my data),
if it failed to hit the target, failed to get stopped out, or hit both on the same day, if the target was at or below zero or if the target was more than 20% away.
- For the benchmark securities, I chose patterns of the same length (3 bars, 2 bars, 1 bar, etc) and started finding patterns when data started (at any time of the month and year).
Because small patterns are numerous, I often skipped a number of them (such as I picked every fourth one). That tended to use patterns at various times of the month.
The 20% rule I used because it's unrealistic to expect a large gain from a small pattern. For example, with the shark-32 pattern, I found a case where the predicted rise was more than 100%.
The 20% value seemed reasonable as a maximum target.
-- Thomas Bulkowski
See Also
- Small pattern performance.
- Updated daily list of short patterns.
- 3L-R
- Inverted 3L-R
- Closing price reversal, uptrend
- Closing price reversal, downtrend
- Gap2H
- Inverted gap2H
- Hook reversal, uptrend
- Hook reversal, downtrend
- Inside Days
- Key reversal, uptrend
- Key reversal, downtrend
- Open-close reversal, uptrend
- Open-close reversal, downtrend
- Outside Days
- Pivot point reversal, uptrend
- Pivot point reversal, downtrend
- Shark-32 chart pattern.
- Upside weekly reversals
- Downside weekly reversals
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