How Volume Provides Clues & What It's Suggesting

Tonight I thought I’d show an example of how volume can affect price action. The last two days the S&P 500 has risen by over 1.5%. Volume has also risen each of the last two days. Ignoring volume I ran a test to see how the S&P performed after back to back 1.5% rises:


Results were choppy and even the better periods generally underperformed a random 1-2 week period.

Next I looked at what happened if the volume rose both days as it has the last 2:


Generally positive results. Nothing eye-popping but “worse than random” has turned to a positive bias.

What if I look at only those times when the market was up 1.5% for two days in a row and there wasn’t a progressively higher volume pattern?


As you’d expect, things have gone from choppy to choppy with a slight downside bias.

What if instead of rising two days in a row, we look at the same price pattern where volume sank two days in a row?


A gently positive bias with rising volume becomes a violently negative bias on decreasing volume. Of course the number of instances here is quite small. To remedy this I lowered the price requirement from 1.5% to 1%. Results below:


Similar story here. Any way you look at it, the moral is this: Pay attention to volume. It matters.

As a bit of a tease I’ll let everyone know that I’m currently conducting a large research project related to volume. I hope to be able to release results some time in August.

A Quick Recovery

After falling hard yesterday the market made up all of those losses and then some today. Historically, these kind of sharp recoveries have been bullish over the next couple of weeks. Below is a study which exemplifies this:



Of the 19 instances, 6 of them dipped below the low of the “big down day” at some point in the following 12 days.

Overall, action seems to have turned more constructive in the last two days.

After The Market Drops Hard Two of Three Days...

The S&P 500 dropped over 1.75% today. This was the 2nd time in 3 days this has happened. Below is a table showing how the market has performed after other such instances:



Things were looking ugly as of Sunday night. With Monday's drop the short-term may be getting a bit overdone.

What The Recent Put/Call Ratios Are Suggesting

With the increased difficulty created by the recent enforcement of short selling rules in certain financial stocks, it would seem that there may be a greater interest in put buying. This is because buying a put would be an alternative way to gain short exposure. What we’ve seen is exactly the opposite. Last Monday the CBOE Total Put/Call Ratio’s 10-day MA dropped below it 200-day MA. It continued to drop further below it all week.

In the past I’ve discussed the need normalize the put/call ratios. I began looking at the 10/200 MA ratio after reading some of Dr. Brett Steenbarger’s research on the subject. Dr. Steenbarger used the Equity P/C Ratio and looked for stretches.

In my case I do not require the 10-day MA to be stretched from the 200-day MA. I simply looked at how the market has performed when the 10-day MA is positioned either above or below the 200-day MA.

From 8/6/1996 through 7/25/2008 the S&P 500 has gained 595.44 points. When the 10-day MA of the Total Put/Call Ratio has been above the 200-day MA the S&P 500 has gained 710.31 points. When the 10-day MA has been below the 200-day MA the S&P 500 has LOST 114.87 points. Based on this I’d consider the recent cross of the 10-day put/call below the 200 day put/call to be a negatvie.

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Putting Thursday's Drop Into Context

After making a new 200-day low last week, the S&P 500 made a nice bounce over the next six days. About half of that six-day bounce was erased Thursday as the market took it on the chin. I conducted a study to see what’s happened following similar circumstances in the past.



Winners and losers were split right about down the middle over the next week to week and a half. Notable is the fact that losers outsized winners by a significant amount from 5 to 10 trading days out. So while the odds are 50/50, risks greatly outwiegh rewards. I ran the test under a few different scenarios. One was using a 2% drop instead of the 1.5% shown above. The results were very similar with fewer instances. I also looked at using a 100-day low instead of 200. In every iteration I ran it appeared there was a downside edge for the first 5-8 days followed by a bounce through day 15 or so and then another pullback through day 20.

Looking at the results of a 2% or greater drop after a bounce from a 200-day low I found that 47% of them went on to make new lows within the next 5 days. In every case where the market managed to hold above its recent lows for the next 5 days, it also held above them for at least 3 more weeks. The next five days may tell a lot about the sustainability of this attempted rally.

Breadth & Helicopters: The Sequel

Yesterday’s post on Breadth and Helicopters received a slew of comments. There were many well thought out and interesting points. I don’t care to get into a lengthy debate and couldn’t possibly address all the issues that were raised, but I thought I would offer a few comments for further clarification on my thinking. I’ll also touch on a few of the issues discussed in the comments section. Anyone who hasn’t read yesterday’s post or some of the comments people made following may want to check that out before continuing.

So the June/July selloff took out two breadth indicators with “perfect” records. In my post I indicated that this didn’t sway me from treating them the same as I had previously.

I should mention that I am neither surprised nor concerned that they both “failed” at the same time. For the most part they both measure the same thing – breadth. One looks at broad market advance/decline breadth while the other looks at how broad extreme selling is in a select list of securities. Still, they’re both looking at breadth. There is no question that it became extremely negative in June. And rather than being accompanied by the sharp bounce that has been customary for the last 25 years, the market continued to slide.

One notable about both of the indicators discussed in yesterday’s post is that their history was somewhat limited. The McClellan data I used only went back to 1986 and the CBI data back to 1995. Under most circumstances, if I get enough instances that the results appear notable, I’m more than comfortable only going back this far.

Daniel mentioned an interesting event – the Crash of ’87. What traders should understand is that prior to that the market did behave differently in many ways. I discussed this in both the 7/7 and 7/13 Weekly Research Letters. From the July 7th Letter:

“I go back to the Crash of ’87 for a few reasons. First, it was the last time that strong negative breadth readings, such as the % below 40ma and the 10-day Advance/Decline EMA led to further selling, and in a big way. Second, it led to changes in the way the market is governed and monitored. Some changes, such as the implementation of trading curbs, are well documented. Others, such as the President’s Working Group, are clouded in mystery. Whatever the reason, breadth extremes as we’ve seen recently have consistently marked buying opportunities over the last 20+ years.”

To see an example of how poor breadth readings formerly failed to spark rallies, you may revisit my June 25th post. There I looked at a 10-period EMA of the advance/decline ratio. Readings such as we were hitting in late June have normally provided traders an edge over the last 20 years. Prior to that, expectations were negative to flat.

An aspect to the recent decline that provided a clue as to how bad things were getting was the persistence of the downtrend. Whereas in the past 20 years oversold was met with buying and violent short-covering rallies, it just wasn’t happening in June and early July. I first discussed this in my July 3rd post, which indicated we were experiencing a selloff unlike anything seen for a very long time. On July 7th I followed it up with another post on persistence.

So why didn’t we bounce sooner? Is it likely to happen again? Are we in a 70’s environment or was the selloff just an anomaly? Will breadth indicators remain useful?

My inclination is that we are not going to revert to a 70’s – type market where selling just begets more selling. For the market to change the way it has behaved for the last 20+ years would take a substantial change in dynamics. Has such a change occurred? Difficult to know, but I don’t think so. No uptick rule? Double-short ETF’s? The ability of retail traders to easily trade baskets of commodities via ETF’s? These are all relatively recent developments and they have changed market dynamics in some way. Enough to cause fairly reliable overbought/oversold breadth indicators to become obsolete? I don’t believe so and like I said yesterday, I’m currently just looking at it as a losing episode.

So why did it happen? I don’t know. One observation I would make is that since the Crash of ’87, the government seems to have taken a greater interest in the equity markets. For instance over the past few years there have been several times when the market appears on the precipice of something awful and the Fed arrives with an announcement that seems to spark a rally. This occurred in March. It occurred in January. It occurred last August. It occurred March of 2007. It occurred in June 2006. Those are a few I can recall off the top of my head. Each time the market turned seemingly because of a rate cut, or a bail out, or an expansion of the use of the discount window, or something.

During the recent selloff the Fed has been caught between a rock and a hard place. Whereas under other circumstances they MAY have stepped in sooner with some announcement that could help spark at least a short-covering rally, this time the anouncement didn’t come. The double-edged sword of inflation and recession was threatening and there wasn’t much they were willing to do. Also, the nature of the selloff was not crash-like. There was little panic. The mood was dour as seen by investment and consumer sentiment surveys, but not outright panic as could be evidenced by the VIX. While not immediately hailed, a temporary enforcement of short selling rules in certain financial stocks MAY have helped the recent bounce.

Perhaps stagflation will become a real problem. Perhaps the Fed will continually find itself handcuffed or the government will decide it will no longer considers the equity markets an important consideration in constructing policy. Perhaps the introduction of double-short ETF’s, commodity and currency ETF’s, no uptick rule and other things are changing the dynamics of the market in such a way that certain indicators, such as some of the breadth measures I use, will no longer be effective. I don’t believe that to be true, though and at this point I’m betting against all of that. I will continue to run studies and construct systems in the same manner I did before the latest meltdown.

Now if it keeps happening,..well…then I’ve got some things to ponder.

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One last note here. There were also some observations about system development in the comments of the last post. I think it would be worthwhile to talk about some of my thoughts there some day, and I’ll try and do that. Just not today. This post is already too long. In fact I doubt anyone is still reading…

Quick Note On Follow Through Day

Investors Business Daily did not declare Tuesday a Follow Through Day. It did qualify under the original 1% rules, though. I conducted most of my studies using the old 1% rules. One primary reason is that moving the requiremnt to a 1.7% move, several large rallies would have been missed. There are a couple of things to note when the market puts in an “Original Follow Through Day” (OFTD) like today. First, based on the 64 OFTD’s I found in my study between 1971 and January of 2008, the expectation over the next week was positive. Second, however the market moved over course of the next week was a predictor of the success or failure of the FTD about 2/3 of the time. You may refer here for more details on these statistics.

Breadth, Perceptions of Risk, and Hawaiian Helicopters

On June 11th the McClellan Oscillator (as measured by TC2000) dropped below -200. That night I published a system related to this oscillator which bought the SPX on a drop below -200 and sold when it moved back above 0. The system was 17 for 17 since 1986. The exit trigger came on 7/17. In this case the system would have lost about 5.6%.

The CBI is another breadth tool I use. On July 1st it reached 10, which I will many times use as a buy signal. Going back to 1995, buying the SPX when it hit 10 and selling on a return to 3 or lower would have resulted in 18 winners out of 18 trades. On Friday the 18th it returned to 3. This would have resulted in a loss of about 1.9%.

So now that the perfect records are ruined, how does this change the risk / reward moving forward?

First a story…

After I got married my wife and I went to Hawaii for our honeymoon. There was a concierge in our hotel that offered all kinds of 1-day packages of things to do – snorkeling, trips to other Islands, etc. One thing we thought looked exciting was a helicopter tour of the island. She told us that the helicopters were all flown by former military pilots and all new and state of the art. The company had been flying for 15 years and never had a crash. We were looking to sign up for something in two days. We told her we’d talk about it and come back the next day to sign up.

After we left we agreed the helicopter sounded the best of the options for that day. We were sight-seeing the next day and figured we’d sign up in the afternoon after we got back. When we got back to the hotel, before going down to the concierge, we flipped on the tv. The news was on and the top story was a helicopter crash that took the lives of 7 people. It was the company we were planning on signing up with and the tour we were planning on taking. It was pretty alarming to say the least.

My thought after seeing the news story was that tomorrow would likely be the absolute best time to take the helicopter tour. One crash every 15 years, and it happened today. No way they crash 2 days in a row. My bride had a different perception of the risk.

We went snorkeling.

In reality the crash had no effect on the risk of flying in the helicopter. Perhaps extra precautions would have been taken following the crash, but for the most part if the chance of crashing was around 1 in 5,000 on Friday, then after the crash on Saturday, the chance was still 1 in 5,000. It wasn’t any more (as my wife perceived) or less (as I perceived) dangerous.

Systems with perfect track records should be viewed in much the same way as the Hawaiian helicopters. The chance of a McClellan Oscillator signal or a CBI signal generating a profitable trade was never 100%. Now that they’ve encountered their first loss, should the risk be viewed differently? Not in my eyes. It should have been viewed at less than 100% before the failure and it should be viewed around the same after. I’ll treat breadth indicators in general and these two in particular in the same way I did before. Should they begin to provide false signals more often than expected, then it may be time to re-evaluate.

Traders should attempt to use any edges they identify to their advantage. They should not view any edge as a guarantee, and they should not be swayed too much by a small sample set. It’s been almost exactly 8 years since the helicopter crash and I don’t believe that company has had a crash since. It’d be nice to see the breadth indicators put in a perfect track record for 8 more years. If they did it still wouldn’t change my approach.

Follow Through Days Quantified

Now that the market has bounced and a potential bottom has been established, CANSLIM and other intermediate-term traders are awaiting a Follow Through Day (FTD). Back in January and February I wrote a series on Follow Through Days and deconstructed them, showing actual statistics based on different assumptions and parameters. If you haven’t seen that series of posts and you trade in the intermediate-term time frame, I’d encourage you to check it out.

Below is a quick summary of my quantification of FTD’s:

1) While I’ve read claims of success rates as high as 80%, using extremely generous assumptions my studies showed success rates of about 55% since 1971.
2) Using the original 1% thrust higher requirement, every rally since 1971 would have been accompanied by a FTD. Increasing the requirement above 1% as IBD has suggested in recent years would have seen several substantial rallies occur without FTD’s
3) In most circumstances the FTD occurs close enough to the bottom for traders to be able to catch a substantial portion of a successful rally.
4) Market action in the days after a FTD has been a decent predictor of whether that FTD is likely to succeed.
5) Leadership may not emerge until some time after the FTD. Traders should not expect it to be present and obvious immediately.
6) FTD’s tend to be more reliable after small declines than large ones.
7) FTD’s after day 10 have had a higher success rate over the last 37 years than FTD’s that occurred between days 4-10. This is contrary to what is typically taught.

For those traders who use Tradestation and would like to conduct their own research, I have now released the Quantifiable Edges Follow Through Day Study on the website. It can be downloaded and tweaked as soon as you order. As with all the studies, the code is open and there are flexible inputs for further research. Here’s an example of how results may vary depending on your inputs:

In the original post which discussed success rates, the assumption I used to label a FTD a failure is that the S&P had to CLOSE below its downtrend low. I did this at the time because I wanted to make the inputs a generous as possible to try and reach the 70%-80% success rate that was claimed. Here’s a graph of the S&P 500 going back to December to see how this would have looked.


If I change the requirement from a CLOSE below the low to an intraday LOW below the low, the results change significantly. Now the success rate drops from 54% down to 45%. Most people might consider this an even more accurate representation. The chart with the adjustment to that input is shown below:

If you trade intermediate-term I’d recommend you learn all you can about this tool. Understand the true quantifiable value of Follow Though Days. Don’t just buy into the hype. Research it yourself. For those with Tradestation, the Quantifiable Edges Follow Through Day Study can be a great place to start.

Solid Gains On Big Volume Provide A Quantifiable Edge

What was most striking about today’s action was the volume. Frequently you see high volume occur on a washout day like Tuesday or even a rebound day like Wednesday. According to my data provider, while Thursday's trading didn’t see the range that the previous two had, it did register the highest NYSE volume since March.

High volume on an up day is typically seen as a sign of institutional accumulation. It is generally thought to be a good thing. I put today’s action to the test:


Very impressive results. Winners swamp losers both when looking at the percentage of wins and the size. Also notice the healthy profit factors in the last column. (Profit factor = Gross Gains / Gross Losses.)

Historically, high volume days under the 200-day moving average where the market is up strongly like today seem to have provided a nice upside edge over the next 1-20 trading sessions.

Get all my weekend testing in this week’s Quantifiable Edges Weekly Research Letter. If you haven’t yet received a sample issue, just send an email with your name and email address to weekly@quantifiableedges.com and you’ll receive the weekend’s entire rundown, including both short and intermediate-term biases.

Will The Bounce Continue?

I received several emails tonight asking my opinion on today’s rally. So below are a few thoughts along with one test.

Recently I showed that large moves off bottoms can provide fuel for a further rally. The real edge didn’t come until the 3% threshold for the S&P 500 was reached. Today’s move of 2.5% may or may not be enough. There isn’t convincing evidence either way based on the above mentioned test.

The Nasdaq did have a 3% day. Below is a table showing other times the Nasdaq rose 3% or more following a 50-day low:

The typical pattern has been a pullback followed by a continuation of the move. Of the 28 trades with a 3-day holding period, 23 of them traded below their entry-day close at some point over the next three days. So if you didn't get long yet, you'll likely have an opportunity in the next three days to pick up some index shares at lower prices if you like.

I’ve shown a few other studies this week which showed a good chance for at least a strong multi-day rally. Currently I expect to see more upside over the next week or so. I’d be surprised if the market just rolled right over to new lows again this time.

New Lows In Rarified Air

The other night I discussed how I measure the % Net New Lows on the NYSE. Today the percent of net new lows spiked even higher. Over 1/3 of all issues hit a new 52-week low today according to my data provider. This is the first time that has happened since 1990. Below are the results of buying this setup and holding for “X” days going back to 1971.

An average gain of 6% over the next 4 days.

But I didn’t show 1970, which wasn’t good. Below are all instances with a 4-day holding period going back to 1970, which is as far as I have the data.

Let’s hope 2008 isn’t like 1970. I’m more than ready for a decent bounce.

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What Happens After Gaps Up Fail

It was another tough day for the bulls. Large gaps up in downtrends tend to provide an edge to the upside. My thought going into the day was that the large gap may cause a short-covering panic that would lead to a nice trend day higher. It didn’t come close as the market dropped right from the first few minutes.

Reversals like this always look ugly, but I thought I’d take a little closer look.

Using the SPY I checked all other times there was a gap up of over 1% and then a close at a 200-day low. Today was the first. So I loosened some parameters.

A choppy beginning but once you get out a few weeks things look very good. An average trade of over 5% in the next 4 weeks is impressive. Of course the number of instances is extremely small. So I lowered the gap requirement to 0.5%:


Nothing mind-blowing but over the next 1-2 weeks it showed a decent upside edge. Of course there has been a multitude of reasons the market should bounce for a while now.

Net New Lows Testing and the Need to Normalize

One measure of breadth that reached an extreme on Friday was the number of NYSE stocks hitting new 52-week lows. Rather than just looking at 52-week lows, I typically like to look at the differential of highs and lows. As with many of the indicators I use, I believe it’s important to normalize the results when looking over long time periods. (Click here for a discussion on normalizing put/call ratios.) For this indicator the need to normalize springs from the fact that the total issues trading on the NYSE is significantly greater now than it was in the 1970’s and early 80's. Therefore I divide the raw result by the number of issues outstanding to get a percent figure. The total result on Friday was a net of 757 or just over 23% of the total issues traded on the NYSE. Here’s an example of two tests that demonstrates how results would vary greatly if you fail to adjust for the total issues trading:


Using 750 as your trigger level would give you 10 trades. Most of which are fairly recent. Now let’s use the percentage instead and see what the results look like:


18 trades instead of 10 and results are not as good as they appeared with the first test. Many more instances are found here when looking back to the 70's and 80's. By using raw numbers instead of normalizing them, you’d be missing out on almost half the pertinent data.

A Discussion on Significance, Math, Staticstics & Common Sense

Back in May I submitted a post which discussed significance testing. The basic idea is that if there appears to be a bullish or bearish bias based on a sample set of data then a significance test can help you determine the probability of the perceived bias being due to chance. This is very helpful when deciding whether to factor the results of a certain study into your decision making.

A high confidence level doesn’t mean the past history of bullish or bearish bias will continue at the same rate. It does mean that what occurred in the past was likely due to more than chance.

As an example, on June 12th I wrote a post on the extreme readings of the McClellan Oscillator as measured by Worden Bros. I showed a system that since 1986 (as far back as Worden keeps the data) would have been profitable 17 out of 17 times. The extreme reading led to a bounce the next day. The bounce soon petered out though without breadth improving to the point where the oscillator (as measured by Worden) returned above 0. At this point that system entry is almost a month old and it appears unlikely that is will close profitably. Does this mean the system doesn’t work? Nope. It probably will work well into the future. There is almost certainly an edge. What is certain is that the edge is not 100%.

When considering the results of a study, though, a lot more should be considered than just win %. The line I normally look at first in the results I publish is typically “Avg Trade”. Even if the indicator is only 50% (or less) accurate, do the times when it was right substantially outweigh those when it was wrong?

Depending on the time period you measure, the long-term upward drift of the market typically averages between 0.03% to 0.05% per day. This would equate to $30-$50 on my “$100,000 per trade" studies. If I find a study that averages $200/per day over a 5-10 day period, then that study is likely suggesting an edge.

It’s important to consider several of the other columns as well. Outliers play a large part in the evaluation process. If the system was wrong 10 times for an average loss of 0.5% and right once for a gain of 20%, looking at the “Average Trade” isn’t going to tell the whole story. The outlier has largely skewed the results. For reasons of space and aesthetics I don’t always show the “Max Gain” or “Max Loss” columns. If I do you can be sure I consider them important.

Profit factor is another interesting stat that I consider. It measures how much you need to endure in losses in order to make a certain amount of gains. The formula is Gross Gains / Gross Losses. In general, a system that makes $1000 from $1,200 in profits and $200 in losses is preferable to a system that makes $1000 from $20,000 in profits and $19,000 in losses. Therefore a higher profit factor is generally more desirable.

I normally give some considerations to the columns I show in the results. Readers who want to get the most from the studies should take the time to look at all of the columns.

Also, there are some studies I do that end up with too few instances to derive meaningful statistics from. This does not mean the study isn’t valuable or can’t teach us something. In fact, many times the lack of instances may in itself be a warning sign. If the market is behaving in a way that it either never or only a small number of times has acted in the past, I find that noteworthy. I want to know when the market is in uncharted territory. For me that may signify some extra caution is warranted.

In other cases, even with too few instances for meaningful statistics, the small number of instances found are noteworthy or compelling in some way. An example of this would be the May 22nd “Net New Highs” study. Three instances. All tops. (And a fourth close call that wasn’t.) Instance #4 has turned out pretty bad as well. The May 22nd study wasn’t one that I quantified and factored into the Aggregator, but that doesn’t mean it did provide useful information to consider when determining my market bias and approach.

As a last point, taking a mathematical approach to the market can help to provide a "quantifable edge". It will never be a perfect edge, though. While the math and the calculations may be perfect, the market isn’t. The market is heavily influenced by emotion. A common sense approach to the numbers is necessary. Otherwise, those times when the market acts in a way that is mathematically 99.999% unlikely, (but realistically more common), then trading accounts could suffer incredible drawdowns and damage. The studies may be my guide…but I’m still driving.

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For those who would like to see how I use the studies as well as some common sense to construct my market bias, send an email to weekly@quantifiableedges.com to receive a sample of the Quantifiable Edges Weekly Research Letter.

Bounce Not Impressive So Far

Last night I discussed the T2116 indicator. I noted that since 1986 there were only four other periods of time where the indicator had risen above the 58.1% level where it stood yesterday. Each instance would have been an opportunistic time to be long.

On Tuesday the market bounced. The S&P 500 managed to rise 1.71%. As far as oversold, short-covering rallies it didn’t seem particularly viscous. Below is a comparison of how it fared against the first day bounce the other 4 times the T2116 rose to 58.1% or above:

Today doesn’t even come close to those. It’s less than half the “worst” ones.

Does it matter?

Back in March, I posted a study that looked at explosions of 3.5% or more following a 100-day low. The results were quite impressive. Tonight I broke down the results by percentage gained on the fist up day. I looked at 3 periods – 5, 10, and 15 days out. Results below:

For every time period, results were substantially better if the move was 3% or better. Below 3% and the results were sketchy. There appears to be a slight upside edge 5 days out, and slight downside edges 10 and 15 days out.

I also looked at today’s volume and breadth statistics and found nothing substantial. The market was certainly oversold enough that it could put in a rally over the next few days and weeks, but today’s start was not impressive.

Another Breadth Indicator Hitting Extremes

One breadth indicator I like to watch is provided by Worden Bros. It measures the % of Stocks that are trading at least 2 standard deviations below their 40-day moving average (T2116). Rather than looking at stocks that are simply in a downtrend like the “% of stocks below the 40-day MA”, it looks for extreme readings. Of all the commercially available breadth indicators out there, this one most closely represents the spirit of the CBI. While the criteria are less stringent, it is still looking for somewhat extreme conditions to measure. Today T2116 hit a new high of 58.1%. The indicator dates back to 1986. I looked back to find all days that had readings higher than today’s. It was a short list: 7/23/02, 9/20 & 9/21/01, 8/31/98, and lastly 10/19/87 (Black Monday) through 10/28/87. That’s it. If you take a look at those dates you’ll find they were very opportune times to buy.

Of course breadth has been suggesting a reversal for a while now…

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5 Weeks Lower - Another Example Of Persistence

Last week I showed how the recent downtrend has shown persistence to a degree rarely seen since the 70’s. Below is another example of the downtrend’s persistence from tonight’s Weekly Research Letter.



This test was run from 1960-present. Only 8 occurrences makes it difficult to draw any solid conclusions. Still, these numbers are terrible. The maximum gain 20 weeks later is only 1.7%! The average loss is over 7% and the average trade lost over 4%. There were only three occurrences since 1988, but none of them were positive. They were 8/24/90, 10/13/00 and 3/2/01. Downside persistence like we’re seeing has historically been bearish.

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The Quantifiable Edges Aggregator

In both the nightly Subscriber Letter and the Weekly Research Letter, I feature a chart in the short-term outlook section of the Quantifiable Edges Aggregator. Below is a write-up on the construction and use of the Aggregator.

In an effort to better illustrate what my studies are suggesting vs. what the market is doing, I developed the Quantifiable Edges Aggregator. To construct the QE Aggregator I first tally what the Quantifiable Edges studies are projecting. To do this I take each active study listed in the Quantifiable Edges Subscriber Letter and plug the gains and losses it projects over the next several days, weeks, or months into a spreadsheet. For each day I add up the projection of all studies and average them. This provides the projection for that day. Since the individual day can be highly variable, I use a 3-day average to determine the projections.

I then compare this with the behavior of the market vs. the studies over the past three days to see whether the market has been outperforming or underperforming expectations. Below is a chart with the indicator included for easier reference:


What’s being shown:

Candlesticks in the top section of the chart are daily bars of the S&P 500.

The bottom section contains the QE Aggregator. There are several lines here to look at:

1) The brown horizontal line is at “0”.

2) The dotted grey line is simply the 3-day moving average return of the S&P 500 in percent terms. If it was up over the last 3 days this will be above the brown line, if it was down it will be below the brown line.

3) The green line is the projected return of the studies for the NEXT 3 days. (The Aggregator.)

4) The thick black line is the difference between the QE Aggregator’s value from 3 days ago and the S&P’s return over the last 3 days (Green line value from 3 days ago – today’s grey line value = black line.) Its value represents whether the market has outperformed or underperformed the Aggregator’s expectations over the last three days. If the black line is above 0 that means the S&P has been underperforming expectations. If the black line is below 0 then the S&P has outperformed expectations over the last three days.

What should we look for to help identify opportunities?
The Aggregator on its own is of some value, but the real opportunities arise under two scenarios:

1) The S&P has underperformed expectations over the last few days and the Aggregator is showing a positive expectation for the next few days. Instances where this occurs are marked with a purple dashed vertical line. You are basically looking for times when both the green line (Aggregator) and the black line are stretched above the “0” line. The higher the stretch the better. These represent long opportunities.

2) The S&P has outperformed expectations over the last few days and the Aggregator is showing a negative expectation for the next few days. Instances where this occurs are marked with a red-dashed vertical line. You are basically looking for times when both the green line and the black line are stretched below the “0” line. The lower the stretch the better. These represent short opportunities.

Several of these “signals” line up with actual long and short trade ideas I put into the Subscriber Letter. These would include the 2/26 short, 3/7 and 3/10 longs, the 3/25 short (which went unfilled in the Letter), and the 3/28 long. By quantifying and visualizing the studies in this way it may make it easier to identify opportunities.

The orange circled areas are the last ones to discuss. The first one near the end of Feb shows a point when then S&P had largely underperformed the Aggregator but the Aggregator was still suggesting lower prices over the next few days. The two circled areas in April represent times when the market had largely outperformed over the past few days but the Aggregator was suggesting a positive bias. In all such cases this generally led to a few days of choppy trading.

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A Selloff Reminiscent of the 60’s and 70’s

Anyone who traded through the bear market of the 2000-2003 knows that it was marked with sharp selloffs and sharper reversals. Moves lower were short and violent and moves back up were much the same. Since early May the market has sold off in a way that has rarely been seen since Reagan entered the White House.

The S&P 500 and Dow have both closed below their 10-day moving averages for 19 days in a row. Unless the S&P rises over 2.7% tomorrow and closes above 1295.57, then it will mark 20 days for that one. I looked back to 1960 to see all other times the S&P closed below its 10-day moving average for at least 20 days in a row. Below is the list.

1/29/62
4/17/62
5/22/62
6/14/65
3/15/66
11/8/67
2/13/68
1/10/69
6/16/69
12/11/69
2/6/70
5/1/70
5/27/71
8/9/71
2/9/73
11/27/73
4/15/74
1/31/77
3/14/80
2/9/84
2/12/03

What we seem to be experiencing is a selloff similar to those that occurred in the 60’s and 70’s, but not since.

The selloff in financials has been more than twice as long. KBE and RKH, two bank ETF’s, have now closed below their 10-day moving averages for 40 days in a row. The last day they closed above it was May 6th. Since that time RKH has lost 29.9% and KBE 33.5%. I am unable to find any other ETF that has ever traded below its 10-day moving average for 40 days. EWW (Mexico) came close when it went 39 days in 1998. While the history for many ETF’s is limited, the persistency of this selloff is quite incredible.

CBI Hits 10 - Some Hypothetical Results

The Capitulative Breadth Indicator (CBI) closed at “10” on Tuesday (July 1st). Historically, this has been a reliable indication that the market is nearing a bounce. Using backtested data from 1995-2005 and live data from 2005 forward, there have been 18 instances when the CBI reached at least 10. Buying the S&P when it hit 10 and selling on a return to 3 or lower would have been profitable all 18 times. Below are some summary statistics ($100,000 per trade):





The max drawdown is important to keep in mind. A CBI of 10 is not magic. It doesn’t guarantee anything. It’s indicating that downside breadth is overdone. This shouldn’t be a revelation. Last week I showed another breadth indicator that was also overdone. It still is. Hopefully the market does what breadth says it’s supposed to do soon.

Gap Reversed

When the market gaps lower, trades at a new recent low and then closes up on the day, most people tend to perceive the action as bullish. A rally could form off such a bar, but I have not found it reliable under such a description.

I thought a visual might be more interesting than a statistics table tonight. Below is a chart of the 2002 summer selloff. All bars with a gap lower, a 20-day low, and a close higher have arrows pointing at them. The 2 large pink arrows represent the 2 times the gap down was greater than 1% as happened today.

Simple Gap Reversals as seen above are not necessarily bullish. On the other hand, simple Gap Reversibles as seen below are quite fetching.

When The CBI Spikes But The VXO Doesn't

The CBI hit 9 today and is reaching elite territory. The VXO is not near an extreme. The VXO (and/or VIX) are getting a lot of discussion lately as traders fret that a market bounce won’t happen until after a VIX spike does. It remains my contention that extreme sentiment measures like the VIX and Put/Call Ratios are “nice to haves”, not “need to haves”.

Tonight I decided to look at CBI readings of 8 or higher broken out by those times the VIX was stretched vs. those times it wasn’t. Rules for entry for the first test are as follows: 1) CBI closes greater than or equal to 8. 2) CBI closes higher than yesterday and 3) The VXO is greater than 10% above its 10-day moving average. If all three are met $100,000 worth of SPX is bought at the close. It is sold when the CBI returns to 3 or less. Results below:

Keeping the first two criteria the same and changing #3 to “VXO is LESS than 10% above its 10-day moving average” would provide the following results:

See the big difference? Neither do I. The results are almost identical.

But today the VXO wasn’t near 10% above its 10ma. In fact it was less than 5% above its 10-day MA. Below are the results when changing requirement #3 to “VXO is less than 5% above its 10-day moving average”.

It appears to me the odds favor a bouce soon with or without a higher VIX.