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Hyperopic Loss Aversion

Authors: Jan Krause; Patrick Ring; Ulrich Schmidt;

Hyperopic Loss Aversion

Abstract

The literature reports a tendency that future losses are discounted less than future gains, the so-called sign effect in intertemporal decision making. In this article, we study implications of the sign effect on risk taking: If future losses are discounted less than future gains, mixed lotteries involving both gains and losses should become less attractive when payments are delayed into the future. We refer to this phenomenon as Hyperopic Loss Aversion and provide experimental evidence for it: First, we provide a robust conceptual replication of the sign effect where we find non-positive discount rates for losses. Second, we confirm our hypothesis that mixed lotteries become less attractive over time. This effect can be attributed to Hyperopic Loss Aversion in our design, as a delay does not change the valuation of either pure gain and pure loss lotteries. Finally, we apply the notion of Hyperopic Loss Aversion to investment decisions and show that it offers a novel behavioral explanation for the equity premium puzzle. While our empirical analyses are entirely model-free, we also introduce a theoretical basis to analyze Hyperopic Loss Aversion. Our model, termed Discounted Prospect Theory, can be regarded as a natural extension of Prospect Theory to the intertemporal domain.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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