As of 09/26/2022
Indus: 29,261 329.60 1.1%
Trans: 11,999 129.90 1.1%
Utils: 953 25.04 2.6%
Nasdaq: 10,803 65.01 0.6%
S&P 500: 3,655 38.19 1.0%

YTD
19.5%
27.2%
2.8%
30.9%
23.3%

32,000 or 29,200 by 10/15/2022
13,800 or 11,800 by 10/15/2022
1,000 or 950 by 10/15/2022
11,975 or 10,700 by 10/15/2022
3,800 or 3,500 by 10/15/2022

As of 09/26/2022
Indus: 29,261 329.60 1.1%
Trans: 11,999 129.90 1.1%
Utils: 953 25.04 2.6%
Nasdaq: 10,803 65.01 0.6%
S&P 500: 3,655 38.19 1.0%

YTD
19.5%
27.2%
2.8%
30.9%
23.3%

32,000 or 29,200 by 10/15/2022
13,800 or 11,800 by 10/15/2022
1,000 or 950 by 10/15/2022
11,975 or 10,700 by 10/15/2022
3,800 or 3,500 by 10/15/2022
 
This article discusses various aspects of volume, such as whether increasing volume can power a stock higher after an upward breakout or how it affects the stock after a downward breakout.
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My book, Encyclopedia of Chart Patterns Second Edition pictured on the left, takes an indepth look at 63 chart and event patterns, including performance statistics.
If you click on the above link and then buy the book (or anything) while at Amazon.com, the referral will help support this site. Thanks.
$ $ $
NOTE: An updated study that is more accurate shows that the increase in performance is meager for upward breakouts after above average breakout volume, but throwbacks, and failures increase substantially. For downward breakouts, those with lower volume outperform. Again, pullbacks and failures increase substantially after an above average breakout.
The following study I believe is flawed because it depends on chart patterns such as broadening tops and bottoms for which the breakout date can be disputed. See the other study for details.
A rising volume trend leading to the breakout from a chart pattern is better than a falling one, but probably not enough that you will see a difference in your trading results. Large breakout day volume suggests a more powerful move after the breakout, for both upward and downward breakouts, but the rate of throwbacks and pullbacks increase.
Here are the detailed findings. The important ones are in bold.
I read in an article that higher volume is good for a stock. No justification was given, no research analysis provided. Was this just a writer's opinion based on something he read somewhere? He was not the first to state it as fact, but if it was true, then it could help my trading, so I decided to take a look.
This is not my first excursion into volume analysis. I discovered volume shapes and explored volume trends, and breakout day volume.
I used several databases of known good chart patterns. That means, I cataloged each chart pattern and measured its performance. I found 15,444 chart patterns on the daily charts in 1,093 stocks. The earliest pattern started in July 2, 1991 (but included at least 3 months of data before the start date) and the data ended on March 16, 2010.
Each chart pattern has a breakout  a buy signal  if you will. Often it's when price exits an area of consolidation. The figure on the right shows a breakout from an ascending triangle chart pattern. When price closes above the top of the pattern, it stages a breakout and confirms a buy signal.
I measured volume preceding the breakout using several time periods.
I show the daily measure as D on the chart, weekly as W, and monthly as M. All of the locations are approximate. All measures stop the day before the breakout. The daily measure uses endofday data, the weekly uses an average for the week, and the monthly measure uses an average for the month. I used an average to smooth out those weeks and months not having the same number of days, caused by holidays or periods in which the markets were closed (9/11 comes to mind).
Using three periods gives two up or down measures. For example, if volume is 400, 700, and 500 shares for the three weeks preceding the breakout, the trend is up for the 400 to 700 share weeks and down when it drops from 700 to 500. When I refer to Up Up, it means the difference between the two oldest weeks followed by the two most recent weeks.
I used the following chart patterns in the test (32 varieties).
For all tests, I measured the rise or fall from the closing price the day before the breakout to the ultimate high or ultimate low. The ultimate high is for upward breakouts, and it is the highest peak before price drops at least 20%. The 20% value is arbitrary, but is commonly used to determine bull or bear markets. It represents a trend change. The ultimate low is the lowest valley before price climbs by at least 20%. The trades using the ultimate high or ultimate low should be considered perfect trades, unlikely to be duplicated on a consistent basis. Nevertheless, they do provide a consistent standard of measure over something like a stop loss exit or moving average crossover. In those situations, you're testing the exit mechanism and not the stock's best performance.
As I mentioned, I looked at average volume for each month preceding the breakout from chart patterns.
Breakout Direction  3=>2 Down  2=>1 Down  3=>2 Down  2=>1 Up  3=>2 Up  2=>1 Up  3=>2 Up  2=>1 Down 
Up Samples  32% 2,090  34% 2,306  32% 1,320  32% 2,942  
Down Samples  20% 1,833  20% 1,679  18% 854  20% 2,371 
The heading 3=>2 means the trend between month 3 compared to month 2 (2 being closer to the breakout than 3) and 2=>1 is the same only it applies to months 2 and 1, respectively. Month 1 ends the day before the breakout.
The results are easy to understand. The best performance (34%) after an upward breakout comes when the average volume drops from months 3 to 2 and rises from months 2 to 1. The worst performance (32%) is everything else. Now look at the percentages. The difference between the best performer, 34%, and the worst, 32%, is tiny.
The number below the percentage is the number of chart patterns found (samples) in the test.
For downward breakouts, a rising volume trend over 3 months means the stock won't drop as far, 18% versus 20% for everything else.
In this test, I consider the results to be a tie. In other words, a 2 percentage point difference doesn't mean much.
Below are the results for the three weeks before the breakout. Week 1 ends the day before the breakout.
Breakout Direction  3=>2 Down  2=>1 Down  3=>2 Down  2=>1 Up  3=>2 Up  2=>1 Up  3=>2 Up  2=>1 Down 
Up Samples  31% 1,775  33% 2,902  34% 1,505  33% 2,498  
Down Samples  20% 1,545  19% 2,191  20% 1,068  20% 1,960 
The best performing is 34% when volume trends upward in the three weeks before the breakout. The worst performance comes when volume trends downward over the three weeks, with a gain of 31%. Here the difference between best and worst is wider: three percentage points.
For downward breakouts, the best performing (largest decline) is a drop of 20% (three categories tie) and the worst is down and up (meaning volume trends downward from week 3 to 2 and upward after that), for an average drop of 19%. The difference between best and worst is just one percentage point.
Below are the daily results. The measures do not use averages (as was used for the weekly and monthly results, above), but the actual volume in the three days before the breakout.
Breakout Direction  3=>2 Down  2=>1 Down  3=>2 Down  2=>1 Up  3=>2 Up  2=>1 Up  3=>2 Up  2=>1 Down 
Up Samples  32% 1,393  32% 2,859  33% 1,898  34% 2,530  
Down Samples  20% 1,159  20% 2,305  19% 1,370  19% 1,930 
The performance difference between best (34%) and worst (32%) is another big yawn. The best performance comes when price trends upward then downward over the three days before an upward breakout. For downward breakouts, the results are mixed. The common elements are a lower volume between days 3 and 2 results in slightly better postbreakout performance. A rising volume over the same period hurts performance. The performance difference between best and worst is just one percentage point for downward breakouts.
Just saying that increasing volume leading to a breakout results in better performance does not tell the full story. For all measures discussed so far, the maximum performance difference is just 3 percentage points  hardly the stuff that movies are made of.
Let's look at volume using a percentage change. That's what I tackle next.
In this test, I used the average weekly volume for the two weeks before an upward breakout and computed the percentage change between those two. The left table shows decreases in volume and the right table shows increases. Failures are a count of how often price rises by less than 10% after the breakout. Sample counts less than 30 may lead to inaccurate results.


For example, using the table on the left, if the average volume decreases between 90% and 100%, the four stocks fitting that category gained an average of 66% with no failures. Another example from lower in the table: 40% to 30%. If volume drops between 30% and 40%, the 663 stocks in that category gained an average of 34% with 19% of them failing to rise at least 10%.
Here's an example from the right table (100% to 125%  notice the change in scale). The 227 samples falling between 100% and 125% of the prior week's volume gained an average of 38% with 11% of them failing to rise at least 10% after the breakout.
The figure on the right shows the stocks's average gain (upward breakouts, black line) or loss (downward breakouts, pink line) as volume changes. For upward breakouts, the chart presents visually the "Gain" columns from the above two tables.
The trend is easiest to see in the black line. As volume changes (horizontal axis) from a decrease of between 90% and 100% to between 10% and 0%, the gain (vertical axis) drops from 66% to 28%.
Put another way, large decreases in volume from two weeks before the breakout to one week before result in large average gains after the breakout. Generally, the larger the volume decrease, the larger the gain.
For increasing volume, which appears as the black line moves from 0% to higher volume, the gain tends to increase as volume increases. The change is not as dramatic as it is for decreasing volume.
The results show that dramatic increases or decreases in volume over the two weeks before the breakout can lead to better postbreakout performance.
This test shows the results when volume changes for downward breakouts. The table on the left shows decreasing volume and the table on the right shows increasing volume.


For example, using the left table, for those stocks showing a decrease in volume of between 90% and 80% during the 2 weeks before the breakout, the average loss was 15% in 23 samples with 30% of them failing to decline at least 10%.
From the right table, when volume increased between 25% and 50% over the prior week (week 1 versus week 2), the 783 samples lost an average of 18% with 28% of them failing to drop at least 10%.
The chart shows the relationship between volume changes in a manner that's easy to understand. It's the same chart as for upward breakouts. The pink line (Losses) is for downward breakouts.
The pink line shows an upward trend in stock losses as the change in volume moves from a large drop (100%) to a smaller one. In other words, the line begins at a 4% loss for those stocks seeing volume drop between 90% and 100%. The middle of the line (0% volume increase) shows a 22% average loss from stocks having almost no volume change from week to week. As the chart shows, the loss holds steady between 15% and 22% over most of its length.
Based on the chart, one can conclude that as volume decreases over the 2 weeks before the breakout, so does the potential loss.
For increasing volume trends from week to week (volume over 0%), the average loss drops, too. That is, the pink line slopes downward. It starts at 20% for volume changes of 0% to 25% and then eases lower to 17% for huge volume changes (300% to 5,000%).
If you exclude samples below 30, then the average loss hovers hear 20%. Dramatically increasing volume tends to lessen the loss, but not to a large degree.
What can we discover about success and failure rates? Failure is just another way of asking about minimum price moves that chart patterns make. If a stock rises just 5% after the breakout, can you make money trading that? Probably not when you factor in slippage, SEC fees, and commissions, added to a perfect trade to capture that 5%. Is the break even point 10%? Let's say that it is. Price has to climb at least 10% after the breakout or I consider it a failure.
On the winning side, how much would you like to make, as a minimum, to consider it a boffo trade? Let's say 25%. If a stock climbs by 25% or more then it's a winner.
Can the volume trend before the breakout decide winners and failures? Let's find out.
Breakout Direction and Duration  3=>2 Down Fail  2=>1 Down Win  3=>2 Down Fail  2=>1 Up Win  3=>2 Up Fail  2=>1 Up Win  3=>2 Up Fail  2=>1 Down Win  
Up: 3 Days  20%  51%  18%  53%  17%  53%  18%  53%  
Up: 3 Weeks  21%  51%  17%  54%  16%  54%  19%  52%  
Up: 3 Months  20%  50%  16%  55%  16%  53%  20%  52%  
Down: 3 Days  28%  29%  28%  29%  28%  30%  30%  29%  
Down: 3 Weeks  30%  29%  29%  29%  26%  30%  28%  29%  
Down: 3 Months  26%  29%  29%  28%  30%  28%  29%  30% 
I separated the above table into upward breakouts (Up:) and downward breakouts (Down:). Within each pair of boxes is a count of failures and winners, expressed as a percentage of those qualifying for the up or down volume trend combination.
For example, using the 3 days before an upward breakout to determine a Down Down volume pattern, I found that 274 out of 1,393 samples (20%) failed to show postbreakout rises of at least 10%. However, over half  51%  showed gains over 25%. Here's another example, using the next pair of boxes. For upward breakouts, 18% failed to climb at least 10% and 53% climbed at least 25% after the breakout when the three days volume trend went from down to up.
For downward breakouts, read the table in a similar way. For example, using the Day row for downward breakouts: 28% failed to drop at least 10% and 29% dropped more than 25%.
What can we conclude from the numbers? For upward breakouts, avoid downward volume trends (Down Down). Those have the most failures regardless of the period measured (days, weeks, or months). The fewest failures have a rising volume trend (Up Up). The difference between the highest failure rate, 21%, and the lowest, 16%, is large enough that it caught my attention. The difference between the two is 31%. If you select chart patterns with a rising volume trend over the 3 weeks before the breakout, on average, you will have 31% fewer losers than if you select stocks on the weekly measure with a falling (Down Down) volume trend. That's a significant finding.
Winners come from a rising volume trend: See Down Up and Up Up. Those two pairs of columns have the higher percentage winners, but it's just a 4 percentage point difference between the best (54%) and the worst (50%).
For downward breakouts, most failures occur when volume trends from up to down, but the numbers are close enough that it does not make much difference (30% versus 28% and 29%). For winners, a rising volume trend (Up Up) works well with two of three measures reporting loss counts averaging 30%. That means 30% of the samples I looked at declined at least 25%.
I compared breakout day volume to its average, then mapped the corresponding rise to the ultimate high or the drop to the ultimate low.
The average volume uses the 5trading days leading to, but not including, the day of breakout. In the case of a holiday or market closure, fewer days were included. Values less than 100% mean the breakout day's volume was less than the week's average. The following table shows the results for upward (left table) and downward (right) breakouts.


Yes, the table is huge and I apologize for that, but the numbers are important. In a moment, I'll show you charts of the results.
Let's take a few examples to make the numbers clear, beginning with the left table. When volume on the day of an upward breakout increased between 650% and 700% (bottom of the left table) over the 5day average, the 40 chart patterns showed gains to the ultimate high averaging 40%. There were 18 throwbacks (Throws) that occurred, representing 45% of possible candidates. Eight percent of the chart patterns had prices that failed to rise at least 10% after the breakout.
Here's another example from the 90% to 100% row. When breakout volume was between 90% and 100% of the 5day average, the stock gained 27% with 55% throwing back and 23% failing to make a 10% rise. Rows from 0% to 100% show breakout volume less than or equal to the 5day average. For all rows after 100%, breakout day volume is higher than the average.
The right table reads the same way. Breakout day volume below 100% is less than the average. Pulls are pullbacks. Results for samples below 30 should be considered unreliable.
What does it all mean? The above figure tells the story. The black line represents upward breakouts. As breakout day volume begins well below average, the gain drops but turns upward at the 20% volume mark (horizontal axis). It rises in an arc, approaching the vertical red line. That line separates below average from above average volume. As breakout day volume increases, so does the percentage gain (left scale).
Downward breakouts use the right scale and those numbers represent losses. When breakout volume hits 50% of the average (pink line), it marks the low point. From there, the average loss increases from about 16% to as high as 26%. The results are similar to upward breakouts: As breakout volume increases, the postbreakout decline also increases.
Above is a chart of failure rates. A failure for this test occurs when the stock fails to rise at least 10% after the breakout before suffering a trend change or dropping below the bottom of the chart pattern (above it for downward breakouts).
I took the numbers in the Failures column from the above tables and graphed them. The black line is for upward breakouts, and it shows that as breakout day volume increases, the number of stocks failing to rise at least 10% after the breakout  drops. The line starts at 25% and finishes at 8%.
The pink line is for downward breakouts. Failures increase as volume increases, but peaks when breakout volume is half the average volume. After that, failures decrease as breakout day volume increases.
Throwbacks occur after upward breakouts and pullbacks after downward ones. Read the associated links for more information.
I counted the number of throwbacks and pullbacks that occurred in all chart patterns in this test and found that throwbacks happened 57.0% of the time and pullbacks occurred 59.7% of the time.
The chart shows the throwback and pullback rates listed in the above tables for which there were at least 30 samples (but downward breakouts include a few low sample counts so that the same number of points appear).
Looking at the black line, more points appear above 57% to the right of the red line than to the left. That means throwbacks occur more often after above average breakout volume than below average. The table shows the count at 7 to 1 for above and below average volume, respectively.
For downward breakouts, the count is 7 to 3 with above average volume leading. The comparison is somewhat unfair since there are more points to the right of the red line than on the left. Nevertheless, the lopsided counts suggest that throwbacks and pullbacks occur more frequently after above average volume breakouts. To flip that around, throwbacks and pullbacks occur less often after a below average volume breakout.
A check of the spreadsheet confirms the findings. Throwbacks that occur after an above average volume breakout total 3,749 compared to just 1,306 throwbacks for below average breakout day volume. Pullback totals show the same trend: 2,803 to 1,308 for above and below average breakout day volume, respectively.
Based on the results from the Success and Failure section, here's how to cut your losses from trading chart patterns by 30%.
Assume that tomorrow is the breakout day. Total the volume over the last 5 trading days (1 week) and compare that to the total of the 5 trading days before that. If the most recent 5 days has a lower volume than the prior 5, then do not buy the stock if it should breakout tomorrow. This is a week to week comparison since the most recent week's volume trend is more important than prior weeks and prior days. It's where you get the most "bang for the buck."
I looked at the percentage change of those with volume trending down into the breakout and found that volume decreased by an average of 20% and a median of 17% over the prior week. Stocks falling into that category had the highest failure rates (21%). Those with volume trending up leading to the breakout saw volume climb by an average of 49% and a median of 24% above the prior week.
If you compute the 5day average for your two week's worth of volume and calculate the percentage change, consider avoiding trading the stock if volume rises less than 49%.
For breakout day volume, higher is better because above average breakout day volume suggests better post breakout performance with fewer failures. To make use of this finding, compare the breakout day's volume to the average of the 5 trading days before the breakout. If breakout day volume is above average, then you're set. This applies to both upward and downward breakouts.
If breakout day volume is above the 5day average, then expect a throwback or pullback. For upward breakouts, throwbacks occur 74% of the time if the breakout happens with above average volume. For downward breakouts, the pullback rate is 68%. Thus, you can wait for a throwback to complete and then jump into a stock when it begins recovering. That lowers your risk of failure in case the stock continues dropping during a throwback.
 Thomas Bulkowski
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