Herding, information cascades and volatility spillovers in futures markets (original) (raw)

Herd Behavior in Financial Markets

2001

"Men, it has been well said, think in herds; it will be seen that they go mad in herds, while they only recover their senses slowly, and one by one." Charles Mackay

Herd Behavior in Financial Markets: An Experiment with Financial Market Professionals

Journal of the European Economic Association, 2009

We study herd behavior in a laboratory …nancial market with …nancial market professionals. An important novelty of the experimental design is the use of a strategy-like method. This allows us to detect herd behavior directly by observing subjects' decisions for all realizations of their private signal. In the paper, we compare two treatments: one in which the price adjusts to the order ‡ow in such a way that herding should never occur, and one in which the presence of event uncertainty makes herding possible. In the …rst treatment, traders herd seldom, in accordance with both the theory and previous experimental evidence on student subjects. A proportion of traders, however, engage in contrarianism, something not accounted for by the theory. In the second treatment, on the one hand, the proportion of herding decisions increases, but not as much as the theory would suggest; on the other hand, contrarianism disappears altogether. In both

Herding and Contrarian Behaviour in Financial Markets

RePEc: Research Papers in Economics, 2009

Rational herd behavior and informationally efficient security prices have long been considered to be mutually exclusive but for exceptional cases. In this paper we describe the conditions on the underlying information structure that are necessary and sufficient for informational herding and contrarianism. In a standard sequential security trading model, subject to sufficient noise trading, people herd if and only if, loosely, their information is sufficiently dispersed so that they consider extreme outcomes more likely than moderate ones. Likewise, people act as contrarians if and only if their information leads them to concentrate on middle values. Both herding and contrarianism generate more volatile prices, and they lower liquidity. They are also resilient phenomena, although by themselves herding trades are self enforcing whereas contrarian trades are self-defeating. We complete the characterization by providing conditions for the absence of herding and contrarianism.

Herding and Contrarian Behavior in Financial Markets

Social Science Research Network, 2009

Rational herd behavior and informationally efficient security prices have long been considered to be mutually exclusive but for exceptional cases. In this paper we describe the conditions on the underlying information structure that are necessary and sufficient for informational herding and contrarianism. In a standard sequential security trading model, subject to sufficient noise trading, people herd if and only if, loosely, their information is sufficiently dispersed so that they consider extreme outcomes more likely than moderate ones. Likewise, people act as contrarians if and only if their information leads them to concentrate on middle values. Both herding and contrarianism generate more volatile prices, and they lower liquidity. They are also resilient phenomena, although by themselves herding trades are self-enforcing whereas contrarian trades are self-defeating. We complete the characterization by providing conditions for the absence of herding and contrarianism.

Herd Behaviors in Financial Markets

2004

We investigate the herd behavior of returns for the yen-dollar exchange rate in the Japanese financial market. It is obtained that the probability distribution P(R)P(R)P(R) of returns RRR satisfies the power-law behavior P(R)simeqR−betaP(R) \simeq R^{-\beta}P(R)simeqR−beta with the exponents $ \beta=3.11$(the time interval tau=\tau=tau= one minute) and 3.36($\tau=$ one day). The informational cascade regime appears in the herding parameter Hge2.33H\ge 2.33Hge2.33

Herd Behavior in a Laboratory Financial Market

American Economic Review, 2005

We study herd behavior in a laboratory financial market. Subjects receive private information on the fundamental value of an asset and trade it in sequence with a market maker. The market maker updates the asset price according to the history of trades. Theory predicts that agents should never herd. Our experimental results are in line with this prediction. Nevertheless, we observe a phenomenon not accounted for by the theory. In some cases, subjects decide not to use their private information and choose not to trade. In other cases, they ignore their private information to trade against the market (contrarian behavior). (

Estimating a structural model of herd behavior in financial markets

2012

We develop and estimate a structural model of informational herding in …nancial markets. In the model, a sequence of traders exchanges an asset with a market maker. Herd behavior, i.e, the choice to follow the actions of one's predecessors, can arise as the outcome of a rational choice because there are multiple sources of asymmetric information in the economy. We estimate the model using transaction data on a NYSE stock in the …rst quarter of 1995. We are able to detect the periods of the trading day in which traders herd, and …nd that they account for 15% of trading periods. Moreover, we …nd that in more than 10% of days, herding accounts for more than 30% of all trading activity. Finally, by simulating the model, we estimate the informational ine¢ ciency generated by herding. On average, because of herding, the actual price is 0:4% distant from the full informtion price. Moreover, in 2:8% of trading periods, the distance between actual and full information prices is larger than 10%. This suggests that the informational ine¢ ciency caused by herding, although not extremely large on average, is very signi…cant in certain days.

Herd Behavior and Contagion in Financial Markets

B E Journal of Theoretical Economics, 2008

We study a sequential trading financial market where there are gains from trade, that is, where informed traders have heterogeneous private values. We show that an informational cascade (i.e., a complete blockage of information) arises and prices fail to aggregate information dispersed among traders. During an informational cascade, all traders with the same preferences choose the same action, following the market (herding) or going against it (contrarianism). We also study financial contagion by extending our model to a two-asset economy. We show that informational cascades in one market can be generated by informational spillovers from the other. Such spillovers have pathological consequences, generating long-lasting misalignments between prices and fundamentals. . We are indebted to our advisor, Douglas Gale, for his invaluable guidance. We also owe a special debt to Marco LiCalzi for a very careful reading of the paper. We thank show that, when there there is multidimensional uncertainty (i.e., uncertainty not only on the direction of a shock to the asset fundamental, but also on the existence of the shock itself), herd behavior can arise even in their framework. Their definition of herding, however, is not the standard one in the literature (see footnote 24). Even with multidimensional uncertainty, informational cascades cannot arise in their study (see their Proposition 2 and their comments at page 733). See also the considerations of

An empirical analysis of herd behavior in global stock markets

This paper examines herding behavior in global markets. By applying daily data for 18 countries from May 25, 1988, through April 24, 2009, we find evidence of herding in advanced stock markets (except the US) and in Asian markets. No evidence of herding is found in Latin American markets. Evidence suggests that stock return dispersions in the US play a significant role in explaining the non-US market’s herding activity. With the exceptions of the US and Latin American markets, herding is present in both up and down markets, although herding asymmetry is more profound in Asian markets during rising markets. Evidence suggests that crisis triggers herding activity in the crisis country of origin and then produces a contagion effect, which spreads the crisis to neighboring countries. During crisis periods, we find supportive evidence for herding formation in the US and Latin American markets.