Abstract
Subjective biases and errors systematically affect market equilibria, whether at the population level or in bilateral trading. Here, we consider the possibility that an agent engaged in bilateral trading is mistaken about her own value of the good she expects to trade. Although it may sound paradoxical that a subjective private valuation is something an agent can be mistaken about, as it is up to her to fix it, we consider the case in which that agent, seller or buyer, consciously or not, given the structure of a market, a type of goods, and a temporary lack of information, may, more or less consciously, state an erroneous valuation. The typical context through which this possibility may arise is in relation with so-called experience goods which are sold while all their intrinsic qualities are still unknown (like, e.g. untasted bottled fine wines). We model that “private misvaluation” phenomenon. The agents can also be mistaken about how their exchange counterparts are themselves mistaken. We analyse and simulate the consequences of first-order and second-order private misvaluation on market equilibria and bubbles, and notably focus on the context where the second-order expectations about the other agent’s misvaluation are not met.
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Notes
- 1.
Following Squintani in [7] we consider two situations in our paper depending on whether the agents try to rationalize or not the signals they receive.
- 2.
In the simple case discussed in this paper when the updating process keeps the difference between first and second order misvaluation levels constant there will be no difference in bid and ask prices for these two updating strategies.
- 3.
This is the price, from a seller’s perspective, that would be quoted by a seller having a maximum possible private value. The value can be calculated by substituting a value \(\overline{v}_s\) for a variable \(v_s\) in Eq. 4.
- 4.
This is the price, from a seller’s perspective, that would be quoted by a buyer having a maximum possible private value. The value can be calculated by substituting a value \(\overline{v}_b\) for a variable \(v_b\) in Eq. 10 and replacing \(\delta _b\) with \(\delta _s'\) and \(\delta _b'\) with \(\delta _s\).
- 5.
The parameter \(\beta \) represents the stubbornness of a seller.
- 6.
This is the price, from a seller’s perspective, that would be quoted by a buyer having a minimum possible private value. The value can be calculated by substituting a value \(\underline{v}_b\) for a variable \(v_b\) in Eq. 10 and replacing \(\delta _b\) with \(\delta _s'\) and \(\delta _b'\) with \(\delta _s\).
- 7.
Mean price is calculated based on the prices of successful trades.
- 8.
Trading frequency is defined as the ratio of the buyers (or sellers) that successfully traded to the total number of buyers (respectively sellers).
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Bourgeois-Gironde, S., Czupryna, M. (2022). On the Impact of Misvaluation on Bilateral Trading. In: Czupryna, M., Kamiński, B. (eds) Advances in Social Simulation. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-92843-8_23
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DOI: https://doi.org/10.1007/978-3-030-92843-8_23
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