Margin, Short Selling, and Lotteries in Experimental Asset Markets

Ackert, Lucy F.; Charupat, Narat; Church, Bryan K.; Deaves, Richard

doi:10.2307/20111899

Cited by 75 publications

(60 citation statements)

References 26 publications

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“…They made the intriguing finding that assets are often traded in high volume at prices substantially above their fundamental values. The same finding was later confirmed by many other studies under a variety of treatments (e.g., Porter and Smith (1995), Lei, Noussair, and Plott (2001), Dufwenberg, Lindqvist, and Moore (2005), Ackert, et al (2006), Haruvy and Noussair (2006), Haruvy, Lahav, and Noussair (2007), Hirota and Sunder (2007), and Hussam, Porter and Smith (2008)). …”

Section: Bubbles In Labssupporting

confidence: 78%

“…The experimental studies have identified short-sales constraints and investor experience as important factors for the appearance of asset bubbles. Ackert, et al (2006) and Haruvy and Noussair (2006) find that relaxing short-sales constraints tends to lower prices, while Dufwenberg, Lindqvist, and Moore (2005), Haruvy, Lahav, and Noussair (2007), and Hussam, Porter and Smith (2008), find that as traders gain more trading experience, the divergence in their price expectations is attenuated, and markets become thinner.…”

Section: Bubbles In Labsmentioning

confidence: 99%

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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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Section: Bubbles In Labssupporting

confidence: 78%

Section: Bubbles In Labsmentioning

confidence: 99%

Bubbles, Crises, and Heterogeneous Beliefs

Xiong

2013

Handbook on Systemic Risk

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“…This phenomenon was first discovered by the classic study of Smith, Suchanek, and Williams (1988) and since then has been replicated in many other studies, e.g., Porter and Smith (1995); Lei, Noussair, and Plott (2001) ;Dufwenberg, Lindqvist, and Moore (2005); Ackert et al (2006); Haruvy and Noussair (2006) ;Haruvy, Lahav, and Noussair (2007);Hirota and Sunder (2007);and Hussam, Porter, and Smith (2008), under a variety of treatments. As is typical in these studies, markets are created for traders to trade dividendpaying assets with a lifetime of a finite number of periods.…”

Section: F Noncommon Knowledge Of Rationalitymentioning

confidence: 69%

The Chinese Warrants Bubble

Xiong

Yu²

2011

American Economic Review

254

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In 2005-2008, over a dozen put warrants traded in China went so deep out of the money that they were almost certain to expire worthless. Nonetheless, each warrant was traded more than three times each day at substantially inflated prices. This bubble is unique in that the underlying stock prices make warrant fundamentals publicly observable and that warrants have predetermined finite maturities. This sample allows us to examine a set of bubble theories. In particular, our analysis highlights the joint effects of short-sales constraints and heterogeneous beliefs in driving bubbles and confirms several key findings of the experimental bubble literature. (JEL G12, G13, O16, P34)

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“…Another major task for future research is to probe whether our results generalize to other subject pools, including professional investors (e.g., Ackert and Church, 2001;Biais and Weber, 2009;Chen et al, 2007;Haigh and List, 2005;Lo et al, 2005). Further, moderating effects of market microstructure (Ackert et al, 2006;Theissen, 2000;O'Hara 1995) Table 6: Regression results for effects of market composition (BIS, BAS) on market-level performance measures during (a) POST-SHOCK trading vs. PRE-SHOCK trading following a positive shock, and (b) POST-SHOCK trading vs. PRE-SHOCK trading following a negative shock (* p<0.1, ** p<0.05, *** p<0.01; [t-values in parentheses; heteroskedasticity-consistent (robust) standard errors (clustered) at session level]). Results for all post-pre shock trading comparisons are qualitatively robust to the use of standardized measures.…”

Section: General Discussion and Conclusionmentioning

confidence: 92%

Fight or freeze? Individual differences in investors’ motivational systems and trading in experimental asset markets

Muehlfeld¹,

Weitzel²,

Witteloostuijn³

2013

Journal of Economic Psychology

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We analyze investors' trading behavior, particularly their coping with fundamental shocks in asset value, depending on individual differences in the sensitivity of two basic neurophysiological systems-the Behavioral Approach System (BAS), the 'driving force' of human behavior, and the Behavioral Inhibition System (BIS), its 'braking system'. By analyzing 15 independent experimental asset markets with a total of 171 participants, we find that differences in BAS and BIS sensitivity affect trading in both 'normal' and shocktrading environments: under normal trading conditions, individuals with a more sensitive BAS are more active traders, prefer riskier portfolios, and generate higher individual overall profits. High BIS subjects generate lower scalping and overall profits. Fundamental shocks generally reinforce the preference of high BAS investors for riskier portfolios, while positive shocks 'unfreeze' high BIS investors: they trade more frequently and generate higher profits. At the market level, normal trading in markets with a high BIS median is associated with lower volatility, compared to low BIS median markets, while greater concentration of traders' BAS scores around the mean is associated with better efficiency and liquidity, compared to markets with lower BAS kurtosis. In high BIS median markets, positive shocks lead to improved efficiency, lower bid-ask spread, and lower volatility. We observe no significant differences in market-level reactions to negative shocks.

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Margin, Short Selling, and Lotteries in Experimental Asset Markets

Cited by 75 publications

References 26 publications

Bubbles, Crises, and Heterogeneous Beliefs

Bubbles, Crises, and Heterogeneous Beliefs

The Chinese Warrants Bubble

Fight or freeze? Individual differences in investors’ motivational systems and trading in experimental asset markets

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