The Survival of Noise Traders in Financial Markets

DeLong, J. Bradford; Shleifer, Andrei; Summers, Lawrence H.; Waldmann, Robert

doi:10.1086/296523

Cited by 483 publications

(187 citation statements)

References 26 publications

(23 reference statements)

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“…Therefore, we model the development of the average noise traders' mood ξ as a random walk with increments η. This choice of the type of stochasticity governing the noise traders' behavior is different from the related literature, in particular the paper of De Long et al [10], where the misperseption of the noise traders itself is modeled as an iid random variable. The random walk assumption, however, avoids the abrupt variations of the market price, which would occur if we would incorporate the De Long formalization.…”

Section: Market Implementationmentioning

confidence: 91%

“…N C noise traders, who are subject to "irrational" fads and moods, following the seminal contribution by De Long et al [10].…”

Section: Market Implementationmentioning

confidence: 99%

“…Note that our choice of a random development of the noise traders' mood ξ t (and derived from it, stochastic excess demand of this group) is inspired by the modelling of noise traders in the seminal paper by de Long et al [10]. Our noise traders, therefore, are characterized by random misperceptions rather than some heuristic trading rules such as trend following behavior used, for instance, in Kirman's adaptation of the ant model to foreign exchange trading [17,19].…”

Section: Market Implementationmentioning

confidence: 99%

“…which leads to the distribution given in (10). Given (49) and (10), it is straightforward to compute the mean value of the distribution of z:…”

Section: A2 Unconditional Distribution Of Zmentioning

confidence: 99%

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Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

2005

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The behavioral origins of the stylized facts of financial returns have been addressed in a growing body of agent-based models of financial markets. While the traditional efficient market viewpoint explains all statistical properties of returns by similar features of the news arrival process, the more recent behavioral finance models explain them as imprints of universal patterns of interaction in these markets. In this paper we contribute to this literature by introducing a very simple agent-based model in which the ubiquitous stylized facts (fat tails, volatility clustering) are emergent properties of the interaction among traders. The simplicity of the model allows us to estimate the underlying parameters, since it is possible to derive a closed form solution for the distribution of returns. We show that the tail shape characterizing the fatness of the unconditional distribution of returns can be directly derived from some structural variables that govern the traders' interactions, namely the herding propensity and the autonomous switching tendency.

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Section: Market Implementationmentioning

confidence: 91%

“…N C noise traders, who are subject to "irrational" fads and moods, following the seminal contribution by De Long et al [10].…”

Section: Market Implementationmentioning

confidence: 99%

Section: Market Implementationmentioning

confidence: 99%

“…which leads to the distribution given in (10). Given (49) and (10), it is straightforward to compute the mean value of the distribution of z:…”

Section: A2 Unconditional Distribution Of Zmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

2005

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“…In the recent literature, there is still an ongoing debate. By using a partial equilibrium setting, De Long et al (1991) showed that agents with inferior beliefs may survive in the long run. This is because agents with modestly optimistic beliefs will bear more risk than those agents who hold the correct beliefs and, as a result, earn greater risk premium and grow their wealth on average at a higher rate.…”

Section: Natural Selectionmentioning

confidence: 99%

Bubbles, Crises, and Heterogeneous Beliefs

Xiong

2013

Handbook on Systemic Risk

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This paper reviews the quickly growing literature that builds on heterogeneous beliefs, a widely observed attribute of individuals, to explain bubbles, crises, and endogenous risk in financial markets.Wei Xiong Princeton University Department of Economics Bendheim Center for Finance Princeton, NJ 08450 and NBER wxiong@princeton.edu 1The history of financial markets has been dotted with episodes of bubbles, during which market values of assets vastly exceeded reasonable assessments of their fundamental value. Asset price bubbles can lead to severe economic consequences ranging from wasteful over-investment and frenzied trading during booms to devastating financial crises and depressed real economies during busts. Economists have emphasized many aspects of bubbles and crises. Minsky (1974) advocated the view that excessive expansion of bank credit due to optimism can fuel a speculative euphoria and slowly lead the economy to a crisis. Kindleberger (1978) stressed that irrationally optimistic expectations frequently emerge among investors in the late stages of major economic booms and lead firm managers to over-invest, over-promise, and over-leverage, which sow the seeds for an eventual collapse after they fail to deliver on their promises.Shiller (2000) highlighted a host of psychological biases people use in forming a feedback mechanism, through which initial price increases caused by certain initial precipitating factors such as new technology innovations feed back into even higher asset prices through increased investor confidence and expectations. Allen and Gale (2007) focused on agency problems of professional managers who actively seek unwarranted risk, which leads to bubbles and crises.This chapter reviews a quickly growing body of work that was started by Harrison and Kreps (1978) that studies bubbles and crises based on heterogeneous beliefs, a widely observed attribute of individuals.In a market in which agents disagree about an asset's fundamental and short sales are constrained, an asset owner is willing to pay a price higher than his own expectation of the asset's fundamental because he expects to resell the asset to a future optimist at an even higher price. Such speculative behavior leads to a bubble component in asset prices. This approach does not require a substantial amount of aggregate belief distortions to generate a significant price bubble. Instead, the bubble component builds on the fluctuations of investors' heterogeneous beliefs. Even when investors' aggregate beliefs are unbiased, intensive fluctuations of their heterogeneous beliefs can lead to a significant price bubble through frenzied trading (e.g., Scheinkman and Xiong (2003)). This approach is flexible enough to incorporate several important aspects of bubbles and crises, such as over-investment (e.g., Bolton, ) and crashes (e.g., Abreu and Brunnermeier (2003) and Hong and Stein (2003)). Heterogeneous beliefs can also lead to credit cycles (e.g., Geanakoplos (2010)). The speculation induced by heterogeneous beliefs also lea...

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Belief and Preference‐Based Models

Szyszka

2010

Behavioral Finance

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The Survival of Noise Traders in Financial Markets

Cited by 483 publications

References 26 publications

Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

Bubbles, Crises, and Heterogeneous Beliefs

Belief and Preference‐Based Models

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