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S&P 500 Herding Wreaks Havoc On Breadth Indicators at Trader’s Narrative





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At what turned out to be the top in April 2010, I wrote Technical Reasons for More Stock Market Gains. Like many other technical analysts, I was relying on breadth indicators like the cumulative advance decline line and new highs vs. new lows and was caught flat-footed.

Since then, I’ve been wondering why such reliable indicators suddenly betrayed us. One clue may lie in the fact that right now we have a stock market, not a market of stocks. According to a study by Birinyi Associates, the correlation of S&P 500 component stocks is at historic highs:

S&P500 correlation Jul 2010
Source: The Herding Instinct Takes Over (WSJ)

According to Birinyi, the average correlation since 1980 has been 44% - in comparison, it is 81% right now. The previous high was 79% in late 2008 and the all time high is 83% claimed by the infamous 1987 market. There is also another spike in correlation above 60% in 1998 and again in late 2002. So it is self evident that there is a link to volatility. Apparently, when there is fear, traders and investors treat the stock market as a homogeneous entity rather than a composition of varying individual stocks. And looking back at more than 60 years of data, we can see that we are experiencing a very volatile market right now. Of course, you already knew that intuitively.

I’m sure that the growth of basket trading followed by the slicing and dicing of the market into ETFs has also contributed to this pattern. But since there is an ebb and flow to the correlation over time, instead of a steady, unrelenting trend, I think it reflects mood more than an underlying structural change in the market’s functioning. Another reason is that even stable dividend paying stocks like Microsoft (MSFT) get bought and sold with equal frequency as other lesser quality stocks.

The challenge however is that once individual components start to go in lock-step, the many traditional indicators that look at market internals suddenly become much less useful. They can be dangerously quiet when we need them the most.

For example, the historically observed pattern for the new highs and new lows measure has been that it tops out weeks and months ahead of the actual index, giving us a heads up with ample time to prepare. The same is true for the AD line. But in April, they both topped out concomitantly with the S&P 500 index.

For more on this, see this morning’s notes which has a chart of sector correlations.

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10 Responses to “S&P 500 Herding Wreaks Havoc On Breadth Indicators”  

  1. 1 Jim

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    It sounds like overall, periods of high correlation are great times to buy stocks, no?

    As for the indicators topping out at the same time as the index - that’s only true if the index has actually topped, right?

  2. 2 Daniel P

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    Have you witnessed the same uptick in correlation between stocks and other assets classes in this recent pull back? Is the herd bigger than the S&P 500?

  3. 3 PJ

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    I for one have been one of those ETF buyers and if I was doing this you can sure bet that everyone is doing it as well. It is too hard to buy an individual stock nowadays.

    For your next article you should discuss indicators that have not worked and what has worked. This would be a great thing to know.

  4. 4 PAUL MONTGOMERY

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    >For example, the historically observed pattern for the new highs and new lows >measure has been that it tops out weeks and months ahead of the actual index, >giving us a heads up with ample time to prepare. The same is true for the AD line. But >in April, they both topped out concomitantly with the S&P 500 index

    Babak - Mathew has addressed most of this.
    I know I’ve already requested this, but any chance of asking him back?
    I like both his directness & analysis.

  5. 5 Wes

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    As you know, it can be dangerous to look at a few indicators in isolation from the rest. At the end of April the psychology indicators were practically screaming for a correction. Don Hays’ indicators (haysmarketfocus.com) were at a 4 on a 1 to 6 scale, where 1 is most bullish.

    It would have been unwise to ignore this level of greed in a market that had gone a year without a meaningful correction, regardless of A/D or high/low indications.

    The thing that was unforeseen was not the correction per se, but the flash crash and the level of fear it produced.

  6. 6 Wes

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    Additionally, for the record, the correlation for the S&P components was a modest 0.48 at the market peak. This was quite unlikely to be the reason the A/D and high/low indicators didn’t work.

    The high correlation kicked in after the flash crash.

  7. 7 PJ

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    I’ve included the wsj link that shows the a/d, new highs,new lows and volume. Volume is very slow today. So what the media will say is “the market was lower on low volume, which is good”.

    What is the ramification of ETF’s? Will this be good or bad and what will be the outcome?

    The new highs list is skewed by all the non operating companies.

  8. 8 AB

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    On the subject of breadth indicators, I am curious as to why no one mentions the A/D based McClellan Oscillator; it repeatedly does a good job of showing distribution prior to bearish reversals as well as show when bearish extremes occur. The McClellan Oscillator was giving warning signals throughout most of April, so whatever cumulative A/D indicator you were using, it didn’t work.

    Both the McClellan Oscillator and the TRIN should be given more credit for signaling turning points.

    Outside of using breadth indicators, the best way to go is to know when prices have gotten too high and have to reverse, and when prices have gotten too low and have to reverse. If you can figure out these like I’ve getting close to doing, you’ll always make money by entering low risk and reaping high reward, since prices ALWAYS oscillate from oversold to overbought, and vice versa.

  9. 9 Tristan Grayson

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    I’m with Paul — didn’t Matthew Claassen totally call it?

  10. 10 Chris Pappas

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    I find this fascinating. I wonder if it’s fear that drives the correlations, or the large percentage of volumes that are being driven by well capitalized hedge funds, high frequency traders, and other trading institutions all taking similar positions at the same time.

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