As of 04/30/2025
Indus: 40,669 +141.74 +0.3%
Trans: 13,640 +63.98 +0.5%
Utils: 1,033 -3.63 -0.4%
Nasdaq: 17,446 -14.98 -0.1%
S&P 500: 5,569 +8.23 +0.1%
|
YTD
-4.4%
-14.2%
+5.1%
-9.7%
-5.3%
|
 41,700 or 38,000 by 05/15/202514,400 or 13,000 by 05/15/20251,075 or 1,000 by 05/15/202518,300 or 16,500 by 05/15/20255,700 or 5,300 by 05/15/2025 |
As of 04/30/2025
Indus: 40,669 +141.74 +0.3%
Trans: 13,640 +63.98 +0.5%
Utils: 1,033 -3.63 -0.4%
Nasdaq: 17,446 -14.98 -0.1%
S&P 500: 5,569 +8.23 +0.1%
|
YTD
-4.4%
-14.2%
+5.1%
-9.7%
-5.3%
| |
|
41,700 or 38,000 by 05/15/202514,400 or 13,000 by 05/15/20251,075 or 1,000 by 05/15/202518,300 or 16,500 by 05/15/20255,700 or 5,300 by 05/15/2025 | ||
Fixed errors with hold time 3/3/25.
One-Day Reversal, Top
|
| Characteristic | Discussion |
| 3 bars | The pattern is composed of one bar, but for identification, I use three bars, one day before to one day after the one-day reversal. |
| Top | Look for the pattern in a short-term up trend. In other words, wait for a downward breakout (a close below the bottom of the pattern). |
| Open and close | The open and close on the one-day reversal must be within 25% of the intraday low. |
| Surrounding days | The high price of the two adjacent bars must be below the mid point of the one-day reversal. This should make the one-day reversal bar stand alone, like a tree atop a peak. |
| Tall | The one-day reversal should be at least as tall as the one-month average height of other price bars. |
| Volume | High volume should be present on the one-day reversal. However, I excluded this requirement since the pattern is rare enough without it. |
| Trading Tactic | Explanation |
| Reversal | The pattern is supposed to act as a reversal of the up trend. Only trade those that reverse the short-term up trend (breakout downward). |
| Buy | Once price closes below the bottom of the pattern, sell short at the open the next day. |
| Measure rule | The one-day reversal fulfills the measure rule 67% of the time (bull market). That is, measure the height of the pattern and subtract it from the low price to get the downward target. |
For the following statistics, I used 1,160 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 one-day 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 one-day reversal and the same peak/valley test after the one-day reversal. The closest valley or peak before the one-day reversal is where the trend began. The closest peak or valley after the one-day reversal is where the trend ended. I compared the peak or valley to the average of the highest high and lowest low price of the one-day reversal pattern.
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 pattern ended 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 the pattern. That caught the short-term trend.
| Market | 5% Failure | Average Drop |
| Bull | 48% | 6% |
| Bear | 31% | 10% |
Table 1 lists the failure rates, sorted by market condition along with the average drop. Since the one-day reversal is supposed to act as a reversal of the upward trend, I assumed a downward breakout.
A failure occurs when the stock fails to drop more than 5%.
The failure rates may appear high, but that's typical for short-term patterns like the one-day reversal. The highest failures occur in a bull market: 48% fail to see price drop at least 5%. The average drop is just 6%. Since a bear market sucks prices lower, it makes sense that this pattern works better in a bear market.
| Market | Success |
| Bull | 67% |
| Bear | 67% |
Table 2 shows how often the measure rule works. Use the measure rule to estimate of how far price is likely to drop.
To do this, measure from the highest high to the lowest low in the pattern to get the height. Subtract the height from the lowest low in the pattern to get the target.
Price reaches the measure rule target 67% of the time, regardless of the breakout direction.
| Market | Bull | Bear |
| Net profit/loss | $(97.80) | $8.80 |
| Wins | 42% | 51% |
| Winning trades | 1,477 | 299 |
| Average gain of winners | $748.19 | $749.70 |
| Losses | 58% | 49% |
| Losing trades | 2,043 | 293 |
| Average loss | ($709.41) | ($747.26) |
| Average hold time (calendar days) | 28 | 15 |
Table 3 shows the performance based on 4,790 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.
The results are sorted by bull or bear market. The trades used the same setup as listed in One-Day Reversal, Top, Performance Statistics.
Here's the setup.
For example, in a bull market, the net loss was $97.80 for all trades. The method won 42% of the time and there were 1,477 winning trades. The average gain of winning trades was $748.19.
Fifty-eight percent, or 2,043 trades were losers. They lost an average of $709.41.
The average hold time was 28 calendar days.
Notice how the gains and losses were pegged near 7%, which is how the test was setup.
The figure shows two one-day reversal patterns in Alaska Air (ALK) on the daily scale, at A and C.
Price rises leading to the one-day reversal. Price opens near the low for the day and also closes near the low for the day, with a tall trading range, as required by the pattern.
The next day, price breaks out downward when it closes below the bottom of A and C.
The stock is shorted at the open of bars B and D.
A stop placed 7% below the buy price would exit the trade if needed. It triggers for both A and C at E.
The following tests are different from the ones above.
Even though the one-day reversal top is a bearish pattern, the following tests assume it's bullish. I wait for price to rise above the top of the ODR before buying.
In the discussion that follows, I use twice the height of the ODRT (the middle price bar of the 3-bar pattern) as a price target to sell, and a stop loss order placed a penny below the day to limit adverse moves.
I show an example trade in Advanced Energy stock. Yes, it's unusual to trade a topping pattern this way (by buying when price exceeds the top of the one-day reversal).
I highlighted the ODR pattern on the chart. Entry occurs as shown with a buy-stop placed a penny above the top of the middle price bar in the ODR. Because we wait one day after the middle price bar to be sure the ODR identifies as a valid pattern (meaning the spike is well above the two adjacent bars), entry is delayed by (at least) one day.
The target is twice the height of the ODR day added to the top of the ODR (not shown).
A stop loss order is placed a penny below the bottom of the ODR. Not shown, but the stock rises far enough to reach the target and close out the trade for a profit.
Testing for the ODR is different than for other small patterns. Why? The one-day reversal is a one day pattern but I also use the two adjacent days to make sure the ODR sticks out. However, the buy and sell points still trigger on the middle day (the ODR itself) even though entry is delayed by a day (at least). The delayed-benchmark follows this scheme by delaying entry until the day after the 3-bar pattern completes (then price is compared to the ODR day and a breakout buy consummated if necessary).
I used a target exit placed twice as high as the height of the ODRT day (the middle price bar of the three). I placed a stop loss a penny below the bottom of the ODR day. For additional methodology details, see the link.
Tables 4 and 5 show results for bull markets with an upward breakout and an upward inbound price trend. I used 497 stocks in the test. I show the 1-day delay entry scheme for the benchmark, but also the non-delayed entry for the benchmark. For the non-delay column, I placed a buy stop a penny above the top of the pattern for entry, and a stop loss order a penny below the price bar for a stop exit. The target exit remains as twice the height of the price bar. There is no artificial delay of a day before entry.
| Metric | ODRT in Uptrend | 1-Bar Delay Benchmark | No Delay Benchmark |
| Trades | 234 | 5,821 | 5,682 |
| Average profit/loss per trade | $39.23 | $29.08 | $32.55 |
| Win/loss ratio | 39% | 51% | 43% |
| Average hold time (days) | 16 | 8 | 8 |
| Winning trades | 92 | 2,967 | 2,430 |
| Average gain of winners | 7% | 4% | 5% |
| Average hold time of winners (days) | 22 | 8 | 9 |
| Losing trades | 142 | 2,854 | 3,252 |
| Average loss | -4% | -3% | -3% |
| Average hold time of losers (days) | 13 | 8 | 7 |
The results for the ODRT columns show that it outperforms the benchmark (delayed column) in an apples-to-apples comparison, with a profit per trade of $39.23 versus the benchmark's $29.08.
When there is no delay on entry, (the "No delay benchmark column) the profit per trade increases to $32.55, which is closer to the $39.23 for the ODR trades.
I show a sample trade in US Broker-dealers index fund (IAI).
The ODRT is the tall price spike shown. I placed a stop-loss order a penny below the pattern's low to protect against a big loss, and a buy stop a penny above the high to enter the trade quickly. Entry occurs when the ETF rising above the top of the ODR.
The height of the pattern is the highest high minus the lowest low based only on the middle price bar (the ODR day). Multiply that by two and add it to the top of the ODR day. When price reaches the target, sell.
As the chart shows, the ETF reached the target and sold for a profit.
This is the same test as the prior one except I used 94 exchange traded funds (ETFs) instead of common stocks.
| Metric | ODRT in Uptrend | 1-Bar Delay Benchmark | No Delay Benchmark |
| Trades | 32 | 6,385 | 6,095 |
| Average profit/loss per trade | $29.87 | $31.17 | $38.39 |
| Win/loss ratio | 44% | 59% | 51% |
| Average hold time (days) | 14 | 6 | 6 |
| Winning trades | 14 | 3,756 | 3,120 |
| Average gain of winners | 4% | 2% | 3% |
| Average hold time of winners (days) | 17 | 6 | 7 |
| Losing trades | 18 | 2,629 | 2,975 |
| Average loss | -3% | -2% | -2% |
| Average hold time of losers (days) | 13 | 6 | 6 |
Because of few trades, the results should not be relied upon. If we ignore that advice, the ODR in ETFs underperform the benchmark in terms of net profit.
The ODR pattern with an upward breakout is rare in the crypto world. I found only 5 trades, too few to discuss.
-- Thomas Bulkowski
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