scholarly journals An Experimental Test of the Lucas Asset Pricing Model

2018 ◽  
Vol 86 (2) ◽  
pp. 627-667 ◽  
Author(s):  
Sean Crockett ◽  
John Duffy ◽  
Yehuda Izhakian

Abstract We implement a dynamic asset pricing experiment in the spirit of Lucas (1978) with storable assets and non-storable cash. In the first treatment, we impose diminishing marginal returns to cash to incentivize consumption smoothing across periods. We find that subjects use the asset to smooth consumption, although the asset trades at a discount relative to the risk-neutral fundamental price. This under-pricing is a departure from the asset price “bubbles” observed in the large experimental asset pricing literature originating with Smith et al. (1988) and can be rationalized by considering subjects’ risk aversion with respect to uncertain money earnings. In a second treatment, with no induced motivation for trade à la the Smith et al. design, we find that the asset trades at a premium relative to its expected value and that shareholdings are highly concentrated. Elimination of asset price uncertainty in additional experimental treatments serves to reinforce the same observations, and suggests that speculative behaviour explains the departure of prices from fundamental value in the absence of a consumption-smoothing motive for asset trades.

2018 ◽  
Author(s):  
Anita Kopanyi-Peuker ◽  
Matthias Weber

We study the role of experience in the formation of asset price bubbles. Therefore, we conduct two related experiments. One is a call market experiment in which participants trade assets with each other. The other is a learning-to-forecast experiment in which participants only forecast future prices, while the trade, which is based on these forecasts, is computerized. Each experiment comprises three treatments that vary the amount of information about the fundamental value that participants receive. Each market is repeated three times. In both experiments and in all treatments, we observe sizable bubbles. These bubbles do not disappear with experience. Our findings in the call market experiment stand in contrast to the literature. Our findings in the learning- to-forecast experiment are novel. Interestingly, the shape of the bubbles is different between the two experiments. We observe flat bubbles in the call market experiment and boom-and-bust cycles in the learning-to-forecast experiment.


Author(s):  
Anita Kopányi-Peuker ◽  
Matthias Weber

Abstract We study the role of investor experience in the formation of asset price bubbles. We conduct a call market experiment in which participants trade assets with each other and a learning-to-forecast experiment in which participants only forecast future prices (while trade based on these forecasts is computerized). Each experiment comprises three treatments varying the information that participants receive about the fundamental value. Each experimental market is repeated three times. Throughout, we observe sizable bubbles that persist despite participant experience. Our findings in the call market experiment contrast with those in the literature. Our findings in the learning-to-forecast experiment are novel.


2016 ◽  
Vol 19 (01) ◽  
pp. 1650007 ◽  
Author(s):  
ROBERT JARROW

This paper derives a multiple-factor asset pricing model with asset price bubbles in an arbitrage-free, competitive, and frictionless market. As such it generalizes existing asset pricing models, all of which implicitly assume asset price bubbles do not exist. This generalization leads to two new empirical implications. The first is that positive alphas can exist in an arbitrage-free market due to the existence of asset price bubbles. These positive alphas do not represent abnormal profit opportunities. The second is that bubble risk factors can exist with positive risk premiums. The testing of these new empirical implications awaits subsequent research.


2015 ◽  
Vol 17 (3) ◽  
pp. 35-56 ◽  
Author(s):  
Robert Jarrow ◽  
Felipe Bastos G. Silva

2021 ◽  
Vol 187 ◽  
pp. 36-41
Author(s):  
Kun Zhang ◽  
Tianyi Gu ◽  
Yuanyuan Wang

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