Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics

Tomasz Makarewicz

Journal of Economic Behavior & Organization, 2021, vol. 190, issue C, 626-673

Abstract: Bao et al. (2017) show that in laboratory subjects have problems with both trading an experimental asset and forecasting its price. In this paper I explore these experimental results, by investigating a model in which financial traders individually learn how to use forecasting and/or trading anchor and adjustment heuristics, by updating them with Genetic Algorithms. The model replicates main outcomes of the Bao et al. (2017) experiment, and shows that both forecasters and traders coordinate on asset price oscillations, albeit the trading markets generate larger cycles. Both forecasters and traders learn to chase market trends, and this behavior is reinforced when agents have to perform both tasks. As a result, the famous positive feedback between financial expectations and price trends becomes enhanced and markets generate prices that oscillate between 10% and 350% of the fundamental value.

Keywords: Financial instability; Learning-to-Forecast and Learning-to-optimize experiments; Genetic algorithm model of individual learning (search for similar items in EconPapers)
JEL-codes: C53 C63 C91 D03 D83 D84 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:190:y:2021:i:c:p:626-673

DOI: 10.1016/j.jebo.2021.07.008

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