As of 01/17/2025
Indus: 43,488 +334.70 +0.8%
Trans: 16,431 -169.75 -1.0%
Utils: 1,013 +1.53 +0.2%
Nasdaq: 19,630 +291.91 +1.5%
S&P 500: 5,997 +59.32 +1.0%
|
YTD
+2.2%
+3.4%
+3.0%
+1.7%
+2.0%
|
44,700 or 41,600 by 02/01/2025
17,200 or 15,700 by 02/01/2025
1,050 or 950 by 02/01/2025
20,500 or 18,670 by 02/01/2025
6,100 or 5,700 by 02/01/2025
|
As of 01/17/2025
Indus: 43,488 +334.70 +0.8%
Trans: 16,431 -169.75 -1.0%
Utils: 1,013 +1.53 +0.2%
Nasdaq: 19,630 +291.91 +1.5%
S&P 500: 5,997 +59.32 +1.0%
|
YTD
+2.2%
+3.4%
+3.0%
+1.7%
+2.0%
| |
44,700 or 41,600 by 02/01/2025
17,200 or 15,700 by 02/01/2025
1,050 or 950 by 02/01/2025
20,500 or 18,670 by 02/01/2025
6,100 or 5,700 by 02/01/2025
| ||
Updated with new performance information on 11/13/24.
Open-Close Reversal, Downtrend
|
Characteristic | Discussion |
1 or 2 bars | The pattern is composed of one bar but it references the close of the prior bar. |
Downtrend | Look for the pattern in a short-term down trend. |
Open | The open must be within 25% of the intraday low. |
Close | The close must be within 25% of the intraday high, but also be below the prior day's close. |
Trading Tactic | Explanation |
Reversal | The pattern is supposed to act as a reversal of the down trend, and it does, but only 51% of the time in a bull market. |
Buy | Once price closes above the top of the pattern or below the bottom of it, buy/short at the open the next day, respectively. |
Measure rule | The open-close reversal fulfills the measure rule 82% of the time (bull market, up breakout). That is, measure the height of the pattern and add it to the high price to get an upward target or subtract it from the intraday low to get a downward price target. |
For the following statistics, I used 1,149 stocks, starting from January 1990 to March 2013, but few stocks covered the entire range. All stocks had a minimum price of $5. There were two bear markets in the 2000s (as determined by the S&P 500 index), from 3/24/2000 to 10/10/2002 and 10/12/2007 to 3/6/2009. Everything outside of those dates represents a bull market.
For each open-close reversal, I found when the trend started and when it ended. To find the trend peak or valley, I found the lowest valley and highest peak within plus or minus 10 days (21 days total) each, before the open-close reversal and the same peak/valley test after the open-close reversal. The closest valley or peak before the open-close reversal is where the trend began. The closest peak or valley after the open-close reversal is where the trend ended. I compared the peak or valley to the average of the high and low price of the open-close reversal pattern (2nd day).
The 10-bar peak or valley number tends to find major turning points on the daily charts.
I measured performance from the day after the breakout (opening price) to the nearest trend peak or trend valley.
To determine the inbound price trend (I was looking for a down trend), I used linear regression on the average of the high-low prices in the five days before the pattern. That caught the short-term trend.
Market/Breakout direction | 5% Failure | Average Rise/Drop |
Bull market, up breakout | 42% | 7% |
Bull market, down breakout | 51% | -6% |
Bear market, up breakout | 33% | 10% |
Bear market, down breakout | 27% | -12% |
Table 1 lists failure rates, sorted by market condition and breakout direction along with the average rise or decline.
A failure occurs when the stock fails to move in the direction of the breakout more than 5%.
The failure rates may appear high, but that's typical for short-term patterns like the open-close reversal. The highest failures occur in a bull market: 42% to 51% fail to see price move at least 5%.
Market/Breakout direction | Success |
Bull market, up breakout | 82% |
Bull market, down breakout | 80% |
Bear market, up breakout | 75% |
Bear market, down breakout | 81% |
Table 2 shows how often the measure rule works. Use the measure rule to estimate of how far price is likely to rise or drop.
To do this, measure from the high to the low in the pattern to get the height. Add the height to the high or subtract it from the low to get the target.
Market/Breakout direction | Bull/Up | Bull/Down | Bear/Up | Bear/down |
Net profit/loss | $90.31 | $(47.93) | $(35.80) | $57.44 |
Wins | 58% | 45% | 49% | 53% |
Winning trades | 1,547 | 621 | 300 | 181 |
Average gain of winners | $702.46 | $754.00 | $728.42 | $768.96 |
Losses | 42% | 55% | 51% | 47% |
Losing trades | 1,131 | 765 | 311 | 160 |
Average loss | ($746.99) | ($698.91) | ($772.99) | ($747.47) |
Average hold time (calendar days) | 30 | 28 | 16 | 14 |
Table 3 shows the performance based on 5,061 trades using $10 commissions per trade ($20 round trip), starting with $10,000 per trade. No other adjustments were made for interest, fees, slippage and so on.
Here's the setup.
For example, in a bull market after an upward breakout, the net gain was $90.31 for all trades. The method won 58% of the time and there were 1,547 winning trades. The average gain of winning trades was $702.46.
Forty-two percent, or 1,131 trades were losers. They lost an average of $746.99.
The average hold time was 30 calendar days.
Notice how the gains and losses were pegged near 7%, which is how the test was setup.
The figure shows a open-close reversal pattern in 3M (MMM) on the daily scale, at A.
Price drops into the open-close reversal. The open is near the intraday low at A. The close is near the day's high but it remains below the prior day's close.
The next day, the stock closes above the top of A, staging an upward breakout. Buy at the open, at B.
When price climbs 7% above the buy price, sell. That happens at C.
A stop placed 7% below the buy price would stop out the trade in case of a reversal.
I show a OCRD pattern in the figure, in the red box. In these tests, I assumed the OCRD was a 2-bar pattern.
Entry for the upward breakout (the only direction tested) uses a buy stop placed a penny above the top of the chart pattern (above the higher of the two bars). A stop loss order placed a penny below the bottom of the lowest bar helps limit losses.
The target exit (sell point) is found by computing the height of the OCRD, multiplying by two, and adding it to the top of the OCRD. In this example, the trade is stopped out for a loss.
For a more detailed explanation of the method I used to test the pattern, see the link.
As explained in the example above, I used a target exit placed twice as high as the height of the OCRD added to the price of the top of the OCRD. I placed a stop loss a penny below the bottom of the pattern.
Tables 4 and 5 show results for bull markets with upward breakouts and an inbound downward price trend. I used 497 stocks in the test.
Metric | OCRD in Downtrends | Downtrend Benchmark |
Trades | 1,309 | 5,373 |
Average profit/loss per trade | $80.90 | $68.70 |
Win/loss ratio | 44% | 42% |
Average hold time (days) | 18 | 15 |
Winning trades | 570 | 2,262 |
Average gain of winners (days) | 8% | 7% |
Average hold time of winners | 23 | 20 |
Losing trades | 739 | 3,111 |
Average loss | -4% | -4% |
Average hold time of losers (days) | 16 | 13 |
Table 4. The OCRD pattern is profitable ($80.90 versus $68.70) compared to the benchmark. The win-loss ratio also shows improvement.
The OCRD is highlighted by the red box in the chart. The entry is a buy stop a penny above the top of the 2-bar pattern and a stop loss order is placed a penny below the bottom of the pattern.
In this example, the ETF rises far enough to hit the target exit for a profitable trade.
This is the same test as the prior one except I used 94 exchange traded funds (ETFs) instead of common stocks.
Metric | OCRD in Downtrends | Downtrend Benchmark |
Trades | 886 | 5,631 |
Average profit/loss per trade | $67.27 | $51.31 |
Win/loss ratio | 47% | 45% |
Average hold time (days) | 16 | 13 |
Winning trades | 420 | 2,548 |
Average gain of winners (days) | 5% | 5% |
Average hold time of winners | 22 | 19 |
Losing trades | 466 | 3,083 |
Average loss | -3% | -3% |
Average hold time of losers (days) | 16 | 13 |
Table 5. The OCRD is a stronger performer than the benchmark ($67.27 to $51.31). We also see an improvement with the win/loss ratio when trading ETFs.
I could not find enough trades of the pattern in cryptocurrencies.
-- Thomas Bulkowski
These are two-bar price patterns.
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