Ordered fear plays a strong role in market chaos
When the current financial crisis hit, the failure of traditional economic doctrines to provide any sort of early warning shocked not only financial experts worldwide, but also governments and the general public, and we all began to question the effectiveness and validity of those doctrines. "….analyzed the volatility time series of 10 different stock markets from seven countries over a period of about 50 years and, rather than following traditional economic analyses, they analyzed time variations in the volatility -- or the "volatility of volatility," a.k.a. "fear volatility." In all markets studied, analysis revealed the existence of hidden temporal order in the volatility and very high correlations between the volatility and the magnitude of price variations. This marks the first time hidden temporal order has been found in these market "human factors." "To a non-economist, economic theories seem decoupled from human reality. The fundamental assumption is that investments are made rationally. But investors can behave irrationally -- driven largely by greed and fear, and other human factors," explains Ben-Jacob. "It's also odd that many mathematical analyses, such as the design of investment portfolios, assume no memory. It's assumed that stock prices behave with no apparent temporal order. Yet investors, including professional traders, take into account past behavior and are particularly influenced by the variation in prices or the volatility associated with the fear index." The existence of such volatility order, or "ordered fear," implies that proper portfolio design should take into consideration the "volatility of volatility," according to the team. For example, the common approach to reducing risk is to select stocks with negative or low correlations in their sequence of returns. The new findings suggest that selection criteria should incorporate the correlations in the stocks' volatility dynamics. "We're working on incorporating human factors into market analysis," Ben-Jacob says, "by constructing a new parameter to replace the traditional systemic risk parameter." "