Dividend timing and behavior in laboratory asset markets

Boening, Mark Van; Smith, Vernon L.; Wellford, Charissa P.

doi:10.1007/pl00020943

Cited by 77 publications

(11 citation statements)

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“…Noussair et al (2001), Bostian et al (2005) and Holt et al (2017) all report bubbles using designs with a flat fundamental value pattern. While St€ ockl et al (2015) find fewer bubbles and improved pricing when fundamentals are flat, Smith et al (2000) report bubbles in such markets only when there was a large cash injection before the first period. Huber et al (2019) explore how several design features (for example, how past periods' prices are displayed) affect bubble frequency and severity in SSW flat experimental markets.…”

Section: Prior Researchmentioning

confidence: 98%

Asset market bubbles in an experiment with sequential information releases

Kluger

2021

RBF

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PurposeMuch of the author’s understanding of experimental asset market bubbles is based on the Smith, Suchanek and Williams (SSW) design. The purpose of this paper is to find alternative bubble-producing designs, which is a promising path for new insights.Design/methodology/approachThe Smith et al. (1988) experimental design has been widely used to study bubbles. This paper introduces a novel modification, where the asset has a binary liquidation value and no dividends. Dividends are replaced by the events affecting the liquidation value probability distribution.FindingsOverpricing is common and consistent with subject optimism concerning the random liquidation value. Bubbles are also observed, as the degree of overpricing often rises and then fall during the experiments. However, crashes where the asset price drops below fundamental values are not observed.Research limitations/implicationsSubject over optimism, speculation and/or subject confusion are possible bubble ingredients. More research is needed to determine how much the factors responsible for these bubbles differ from the factors responsible for the SSW design. However, it seems likely that there are at least some common factors given the structural similarities between the two designs.Originality/valueThe present design is novel and may provide a means to better generalize results from previous experiments based on the SSW design.

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Section: Prior Researchmentioning

confidence: 98%

Asset market bubbles in an experiment with sequential information releases

Kluger

2021

RBF

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“…We employ the Smith et al (1988) and Smith et al (2000) paradigm, where participants use experimental currency units (ECU) to trade an asset with a common dividend process. Trading is done over 15 trading periods.…”

Section: Experimental Asset Marketmentioning

confidence: 99%

“…This paper, using a controlled laboratory setting, aims to test whether the PoW mechanism and its implied properties, discussed above, fuel bubbles in cryptocurrency markets. Our experimental setup follows Smith et al (2000) where market participants can trade an asset with a random redemption value. There are several advantages of using this design.…”

Section: Introductionmentioning

confidence: 99%

Does Mining Fuel Bubbles? An Experimental Study on Cryptocurrency Markets

Lambrecht,

Sofianos,

2024

Management Science

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We investigate how key features associated with the Proof-of-Work consensus mechanism of Bitcoin (commonly referred to as mining) affect pricing. In a controlled laboratory experiment, we observe that price bubble formation can be attributed to mining. Moreover, overpricing is more pronounced if the mining capacity is centralized to a small group of individuals. The order book data reveal that miners seem to play a crucial role in bubble formation. Further probing the mechanism in a second study, we find that both mining costs and decisions jointly with the sluggish rate of supply of the asset contribute to the bubble formation. Our results demonstrate that erratic pricing is an inherent feature of cryptocurrencies based on a mining protocol, thus seriously limiting any prospects for such assets becoming a medium of exchange. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: The funding provided by the University of Heidelberg, Hanken Foundation [Grant 271-6250], and Durham University is gratefully acknowledged. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01238 .

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“…This means that its liquidity is overvalued or mispriced in relation to the values of its assets. Smith et al, [31] held that more bubbles are associated with stocks that pay dividends than with those that do not. In line, Caginalpet al, [32] debate that the frequent payment of dividend makes investors to trade more myopically in the short term than in the long term, thus, the higher the dividends and liquidity positions of the firm, the more bubbles is experienced [33].…”

Section: Introductionmentioning

confidence: 99%

Testing for Multiple Bubbles in the Nigerian Stock Exchange

Olulu-Briggs¹,

Sunday²

2023

Saudi J Econ Fin

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Monthly All Share Index data from 1985M01-2021M12 was sourced from the Central Bank of Nigeria and the Central Securities Clearing System of the Nigerian Stock Exchange; to analyze multiple bubble periods. The supremum Augmented Dickey Fuller (SADF) and Generalized supremum Augmented Dickey Fuller (GSADF) quantitative model with 1000 repetitions along with a window size of 42 was selected to carry out the Monte Carlo simulation at the 95% confidence level. From the Backward SADF estimation, three periods of explosive pricing and collapses were detected. The study therefore recommends that market regulators should promote market information and support regular training of market participants to stem speculations and reduce arbitrage. Overall, well-informed risk management practices should be established to guard against market losses.

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Dividend timing and behavior in laboratory asset markets

Cited by 77 publications

References 0 publications

Asset market bubbles in an experiment with sequential information releases

Asset market bubbles in an experiment with sequential information releases

Does Mining Fuel Bubbles? An Experimental Study on Cryptocurrency Markets

Testing for Multiple Bubbles in the Nigerian Stock Exchange

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