As of 12/20/2024
Indus: 42,840 +498.02 +1.2%
Trans: 15,892 +32.54 +0.2%
Utils: 986 +14.76 +1.5%
Nasdaq: 19,573 +199.83 +1.0%
S&P 500: 5,931 +63.77 +1.1%
|
YTD
+13.7%
0.0%
+11.9%
+30.4%
+24.3%
|
44,200 or 41,750 by 01/01/2025
16,100 or 17,700 by 01/01/2025
1,050 or 975 by 01/01/2025
20,500 or 19,300 by 01/01/2025
6,100 or 5,775 by 01/01/2025
|
As of 12/20/2024
Indus: 42,840 +498.02 +1.2%
Trans: 15,892 +32.54 +0.2%
Utils: 986 +14.76 +1.5%
Nasdaq: 19,573 +199.83 +1.0%
S&P 500: 5,931 +63.77 +1.1%
|
YTD
+13.7%
0.0%
+11.9%
+30.4%
+24.3%
| |
44,200 or 41,750 by 01/01/2025
16,100 or 17,700 by 01/01/2025
1,050 or 975 by 01/01/2025
20,500 or 19,300 by 01/01/2025
6,100 or 5,775 by 01/01/2025
| ||
Updated with new performance information on 11/14/24.
Open-Close Reversal, Uptrend
|
Characteristic | Discussion |
2 bars | The pattern is composed of two bars, including the reference to the close of the first bar. |
Uptrend | Look for the pattern in a short-term up trend. |
Open | The open must be within 25% of the intraday high. |
Close | The close must be within 25% of the intraday low, but also be above the prior day's close. |
Trading Tactic | Explanation |
Reversal | The pattern is supposed to act as a reversal of the up trend, and it does, but only 50% of the time in a bull market. The breakout direction is random, in other words. |
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 84% of the time (bull market, up breakout). That is, measure the height of 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 an up trend), I used linear regression on the average of the high-low prices in the five days before pattern. That caught the short-term trend.
Market/Breakout direction | 5% Failure | Average Rise/Drop |
Bull market, up breakout | 45% | 7% |
Bull market, down breakout | 50% | -6% |
Bear market, up breakout | 37% | 7% |
Bear market, down breakout | 33% | -11% |
Table 1 lists the failure rates, sorted by market condition along with the average rise or drop.
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.
Market/Breakout direction | Success |
Bull market, up breakout | 84% |
Bull market, down breakout | 76% |
Bear market, up breakout | 81% |
Bear market, down breakout | 80% |
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 pattern to get the height. Add the height to the high or subtract it from the low to get the target. Price does best in a bull market after an upward breakout. It reaches the target 84% of the time, on average.
Market/Breakout direction | Bull/Up | Bull/Down | Bear/Up | Bear/down |
Net profit/loss | $118.67 | $(76.87) | $(91.36) | $67.85 |
Wins | 59% | 43% | 45% | 53% |
Winning trades | 1,092 | 1,440 | 135 | 342 |
Average gain of winners | $712.74 | $750.46 | $705.35 | $768.85 |
Losses | 41% | 57% | 55% | 47% |
Losing trades | 750 | 1,882 | 167 | 305 |
Average loss | ($746.29) | ($709.90) | ($735.40) | ($718.19) |
Average hold time (calendar days) | 31 | 28 | 17 | 15 |
Table 3 shows the performance based on 6,167 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, the net gain was $118.67 for all trades. The method won 59% of the time and there were 1,092 winning trades. The average gain of winning trades was $712.74.
Forty-one percent, or 750 trades were losers. They lost an average of $746.29.
The average hold time was 31 calendar days.
Notice how the gains and losses were pegged near 7%, which is how the test was setup.
The figure shows the open-close reversal uptrend at A
Price rises leading to the open-close reversal. Price opens at the high for the day and closes near the intraday low, with the day's close remaining above the prior day's close.
The next day, price breaks out downward when it closes below the bottom of A.
The stock is shorted at the open of bar B.
A stop placed 7% above the entry price closes out the trade for a loss at C. The target price, not shown, would have been 7% below the entry price.
I show a OCRU uptrend pattern in the figure, in the red box.
Entry for the upward breakout (the only direction tested) uses a buy stop placed a penny above the top of the chart pattern. A stop loss order placed a penny below the bottom of the chart pattern helps limit losses.
The target exit (sell point) is found by computing the height of the OCRU, multiplying by two, and adding it to the top of the OCRU. In this example, the stock reaches the target and a sale triggers.
For a more detailed explanation of the method I used to test the pattern, visit the link.
As explained in the example above, I used a target exit placed twice as high as the height of the OCRU pattern added to the price of the top of the pattern. I placed a stop loss a penny below the bottom of the pattern. The uptrend benchmark uses a two-bar random pattern.
Tables 4 and 5 show results for bull markets with upward breakouts and an inbound upward price trend. I used 497 stocks in the test.
Metric | OCRU in Uptrend | Uptrend Benchmark |
Trades | 1,449 | 6,018 |
Average profit/loss per trade | $84.54 | $48.01 |
Win/loss ratio | 42% | 40% |
Average hold time (days) | 20 | 15 |
Winning trades | 608 | 2,402 |
Average gain of winners (days) | 8% | 7% |
Average hold time of winners | 27 | 19 |
Losing trades | 841 | 3,616 |
Average loss | -4% | -4% |
Average hold time of losers (days) | 18 | 13 |
Table 4. The OCRU vastly exceeds the benchmark performance ($84.54 versus $48.01).
The OCRU is highlighted by the red box on the chart. The entry is a buy stop a penny above the top of the OCRU pattern and a stop loss order is placed a penny below the bottom of the pattern.
In this example, the entry triggers as the chart shows but the trade is stopped out for a loss.
This is the same test as the prior one except I used 94 exchange traded funds (ETFs) instead of common stocks.
Metric | OCRU in Uptrend | Uptrend Benchmark |
Trades | 1,076 | 6,675 |
Average profit/loss per trade | $58.42 | $48.84 |
Win/loss ratio | 47% | 45% |
Average hold time (days) | 14 | 13 |
Winning trades | 501 | 2,980 |
Average gain of winners (days) | 5% | 4% |
Average hold time of winners | 21 | 17 |
Losing trades | 575 | 3,695 |
Average loss | -3% | -3% |
Average hold time of losers (days) | 12 | 11 |
Table 5. The results of the OCRU in ETFs is marginally better than the benchmark ($58.42 versus $48.84).
I searched 38 cryptocurrencies using several years of data and did not find any trades.
-- Thomas Bulkowski
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