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

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.

Herding interactions as an opportunity to prevent extreme events in financial markets

The European Physical Journal B, 2015

A characteristic feature of complex systems in general is a tight coupling between their constituent parts. In complex socioeconomic systems this kind of behavior leads to self-organization, which may be both desirable (e.g. social cooperation) and undesirable (e.g. mass panic, financial "bubbles" or "crashes"). Abundance of the empirical data as well as general insights into the trading behavior enables the creation of simple agentbased models reproducing sophisticated statistical features of the financial markets. In this contribution we consider a possibility to prevent self-organized extreme events in financial market modeling its behavior using agent-based herding model, which reproduces main stylized facts of the financial markets. We show that introduction of agents with predefined fundamentalist trading behavior helps to significantly reduce the probability of the extreme price fluctuations events. We also investigate random trading, which was previously found to be promising extreme event prevention strategy, and find that its impact on the market has to be considered among other opportunities to stabilize the markets.

Herding Behavior Under Markets Condition: Empirical Evidence on the European Financial Markets

International Journal of Economics and Financial Issues, 2012

This study presents four main contributions to the literature of behavior herding. Firstly, it extends the behavioral researches of herding of the investors on a developed market and mainly on a European market as a whole. Secondly, we are interested in examination of herding behavior at the level of sectors by using data at the levels of companies. Thirdly, this document estimates the implications of herding behavior in terms of returns, volatility and volume of transaction. Fourthly, the herding behavior is revealed as well during the period of the recent global financial crisis in 2007-2008 and of Asian crisis. Our results reveal a strong evidence of herding behavior sharply contributed to a bearish situation characterized by a strong volatility and a trading volume. The repercussion of herding during the period of the recent financial crisis is clearly revealed for the sectors of the finance and the technology.

HERD BEHAVIOR AND NONFUNDAMENTAL ASSET PRICE FLUCTUATIONS IN FINANCIAL MARKETS

Macroeconomic Dynamics, 2006

In this paper we investigate the effects of herding on asset price dynamics during continuous trading. We focus on the role of interaction among traders, and we investigate the dynamics emerging when we allow for a tendency to mimic the actions of other investors, that is, to engage in herd behavior. The model, built as a mean field in a binary setting (buy/sell decisions of a risky asset), is expressed by a three-dimensional discrete dynamical system describing the evolution of the asset price, its expected price, and its excess demand. We show that such dynamical system can be reduced to a unidirectionally coupled system. In line with the rational herd behavior literature , Herd Behavior in Financial Markets: A Review. Working paper, IMF, WP/00/48], situations of multistability are observed, characterized by strong path dependence; that is, the dynamics of the system are strongly influenced by historical accidents. We describe the different kinds of dynamic behavior observed, and we characterize the bifurcations that mark the transitions between qualitatively different time evolutions. Some situations give rise to high sensitivity with respect to small changes of the parameters and/or initial conditions, including the possibility of invest or reject cascades (i.e., sudden uncontrolled increases or crashes of the prices).

Herding Behaviour in Equity Market: A Systematic Literature Review

Orissa journal of commerce, 2022

Performance of financial markets across the globe are not only influenced by the fundamentals but also by the behaviour of investors and their psychology (also known as behavioural finance). This has deepened the interest of researchers in exploring various types of biases that affect investors' decisions. This paper is based on exploring one such bias, herding behaviour. Herding behaviour involves an investor mimicking the behaviour of other investors in the market for investment decision making irrespective of fundamentals. The current paper systematically reviews the literature based on 76 empirical studies during 1991-2022 detecting herding behaviour in equity markets, the nature of the herding and the reasons behind the herding behaviour. Findings of study reveal that herding behaviour is a phenomenon which has occurrences in the short run and not in the medium and long run, herding is more prominent in developing nations than developed nations, and herding is more prevalent during the crisis period and is contagious in nature.

Herd behavior and aggregate fluctuations in financial markets

Arxiv preprint cond-mat/9712318, 1997

We present a simple model of a stock market where a random communication structure between agents generically gives rise to heavy tails in the distribution of stock price variations in the form of an exponentially truncated power law, similar to distributions observed in recent empirical studies of high-frequency market data. Our model provides a link between two well-known market phenomena: the heavy tails observed in the distribution of stock market returns on one hand and herding behavior in financial markets on the other hand. In particular, our study suggests a relation between the excess kurtosis observed in asset returns, the market order flow, and the tendency of market participants to imitate each other.

Transmission of information and herd Behavior: an application to financial markets

Physical Review Letters, 2000

We propose a model for stochastic formation of opinion clusters, modeled by an evolving network, and herd behavior to account for the observed fat-tail distribution in returns of financial-price data. The only parameter of the model is h, the rate of information dispersion per trade, which is a measure of herding behavior. For h below a critical h∗ the system displays a power-law distribution of the returns with exponential cutoff. However, for h>h∗ an increase in the probability of large returns is found and may be associated with the occurrence of large crashes.

Supplementary Appendix for Herding and Contrarian Behavior in Financial Markets

2009

This document contains additional material that was not included in the main version of the paper. Email: andreas.park@utoronto.ca. Web: www.chass.utoronto.ca/∼apark/. Email: hamid.sabourian@econ.cam.ac.uk. A Proofs Omitted from the Paper A.1 Proof of Lemma 1 Observe first that E[V |S,H ] − E[V |H ] = Vq 2 ( Pr(S|V2) Pr(S) − 1 ) + 2Vq 3 ( Pr(S|V3) Pr(S) − 1 ) . The RHS of the the above equality has the same sign as q 2 (

An Empirical Investigation on Herding Behavior in Indian Stock Markets

When individuals synchronize their hand claps, empathize with a friend's sorrow, or conform to peer standards, they are aligning their behaviour with others. As social creatures, humans are readily influenced by others. Herding denotes a form of collective social behaviour in which individuals within a group (the herd) synchronize their thoughts or actions through localized interactions, rather than relying on centralized coordination. This empirical research aimed to measure herding among knowledgeable Indian investors in the stock market. The study gathered data from 327 individual investors using structured questionnaires. Of 400 questionnaires distributed, 358 were completed and returned, with 31 rejected due to incomplete or duplicate responses. This targeted approach helped investigate the factors that influence herding behaviour in Indian investors. The results of this study are of interest to both market practitioners and investors who have access to market analysis tools. By identifying the mechanisms that cause investor herding, this study contributes to the field of behavioural finance. Through collecting data from 327 individual investors, we were able to determine impact of herding in stock markets. Furthermore, this study provides insight into how individual investors view herding, and understanding the reasons behind this behaviour can aid in mitigating potential risks to the stock markets. The study found that herding behaviour among Indian investors is influenced by emotion, risk tolerance, fear of missing out, and heuristics. Risk aversion is positively

Herding behaviour in extreme market conditions : the case of the Athens Stock Exchange Guglielmo

2008

This paper examines herd behaviour in extreme market conditions using data from the Athens Stock Exchange. We test for the presence of herding as suggested by Christie and Huang (1995) and Chang, Cheng, and Khorana (2000). Results based on daily, weekly and monthly data indicate the existence of herd behaviour for the years 1998-2007. Evidence of herd behaviour over daily time intervals is much stronger, revealing the short-term nature of the phenomenon. When the testing period is broken into semi-annual sub-periods, herding is found during the stock market crisis of 1999. Investor behaviour seems to have become more rational since 2002, owing to the regulatory and institutional reforms of the Greek equity market and the intense presence of foreign institutional investors. Citation: Caporale, Guglielmo Maria, Fotini Economou, and Nikolaos Philippas, (2008) "Herding behaviour in extreme market conditions: the case of the Athens Stock Exchange." Economics Bulletin, Vol. 7, N...

The Prevalence, Sources, and Effects of Herding

SSRN Electronic Journal, 2000

The possibility that large market paricipants engage in profitable, yet destabilizing behavior is frequently debated in the academic literature. One theory is that markets can experience herd behavior in which agents follow the 'leaders', hence leading to an overshooting of market prices. This theory is in stark contrast to the traditional speculative stabilizing theory that profitable speculation must involve buying when the price is low and selling when the price is high. To test the prevalence of herding amongst Hedge Funds compared to other classes of speculative derivative traders we employ a unique dataset from the U.S. CFTC on individual positions of speculative traders in thirty two futures markets covering the period of time 2002 -2006. While others have used a more aggregated version of our data, here we test, for the first known time, whether herding exists amongst specific groups of speculative traders. While we find some evidence of herding amongst hedge funds and other types of speculators we conclude that the herding by hedge funds is not destabilizing.