What this really means is that amark up materializes in a given sector around clear leaders. These rapidly reach their realistictarget. Yet this leaves a lot ofstranded money that was not in with the leaders, yet the rationale has not beendisproven.
This leads the rationale beenapplied to others in the sector to absorb the pool of willing money. Once that pool is exhausted the situation iscreated whereby a fair number of issues are naturally over priced and internal variabilityhas declined. Thus we gain the mimickingeffect.
Recall the old market adage thateven a turkey can fly in a high wind.
This means that while the leadershave earned their prices a lot of turkeys are now been seriously over priced. Crashes now become more probable and in theend inevitable as the turkeys have drawn of support.
Mimicry among stocks can predict stock market crashes
February 15, 2011 by Lisa Zyga
The co-movement of stocks during six recent years shows the fraction oftrading days during the year (f) in which a certain percentage of stocks (k/N)go up. The chart on the right combines all of the years. Image credit: DionHarmon, et al.
(PhysOrg.com) -- Since early October 2008, when the Dow JonesIndustrial Average began its drop that reached a low point the following March,many questions have been raised - particularly about what caused the crash andif it could have been predicted and somehow prevented. Some possible answersinvolve market volatility, changes in regulations, bank failures, easy credit,or any combination of external influences and internal market dynamics. In anew study, research analysts have found another clue to stock market crashes:high levels of collective stock movements - or market mimicry - tend to precedecrashes, which suggests that measuring the mimicry level of the market couldprovide significant advance warning of an impending stock market crash.
The researchers, Professor Yaneer Bar-Yam and others from the NewEngland Complex Systems Institute (NECSI) have posted their study, “Predictingeconomic market crises using measures of collective panic,” atarXiv.org. Theirresults indicate that it is the internal structure of the market, rather thanexternal news, that is primarily responsible for crashes.
As previous research has shown, investors can often benefit from usinga trend-following strategy - that is, buying or selling a stock based on the recentperformance of other stocks (which is not necessarily based on any fundamentalvalue). Mimicry ishigh when many stocks move up or down together, which provides a potentialpoint of origin of self-induced market-wide panic.
The researchers constructed a model of this mimicry to obtainco-movement data, which is the percentage of stocks that move in the samedirection. When 50% of stocks move in the same direction (and 50% in theopposite direction), then there is no co-movement. But when substantially morethan half of the stocks move in the same direction, this co-movement indicateshigher levels of mimicry.
Using data from the past several years, the researchers plotted thenumber of days in a year that a certain percentage of the market moves up. Forthe year 2000, the curve showed that about 50% of stocks were moving togetheron any given day. But as the decade went on, the curve became flatter andpeaked lower, indicating an increase in co-movement. By 2008, the curve wasnearly flat, with its distribution reaching the critical value of 1. Duringthis time, the likelihood of any percentage of stocks moving up was almost thesame. As the researchers explained, when mimicry gets this high, externalinfluences become very weak compared to the influences among stocks as a whole.
In addition, the researchers found that the Dow Jones’ eight largestdrops (percentage-wise) during the past 26 years occurred during periods inwhich mimicry reached a level that was twice the standard deviation from theprevious year. This signature increase in mimicry occurred before the drops byless than a year, indicating that crashes are preceded by nervousness thatcauses investors to demonstrate increasingly collective behavior. For thisreason, the simple signature pattern could provide advance warning of animpending crash.
“Our results suggest that self-induced panic is a critical component ofboth the current financial crisis and large single day drops over recentyears,” the researchers wrote in their study. “The signature we found, theexistence of a large probability of co-movement of stocks on any given day, isa measure of systemic risk and vulnerability to self-induced panic. Finally, wenote that the ability to distinguish between self-induced panic and the resultof external effects may be widely applicable to collective behaviors.”
In the future, the researchers plan to investigate whether volatilitymight be a better predictor of crashes than mimicry. They note that, whilevolatility often increases at the beginning of a crisis, it is generallyconsidered to be unreliable for predicting crashes.
Researchers at the NECSI also played a role in changing the marketregulations during the 2008 crash. The institute advised the US
More information: Dion Harmon, et al. “Predicting economic marketcrises using measures of collective panic." arXiv:1102.2620v1 [q-fin.ST]
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