Learning Whether to Be Informed in an Agent-Based Evolutionary Market Model

Paolo Pellizzari

No 2024: 03, Working Papers from Department of Economics, University of Venice "Ca' Foscari"

Abstract: Can traders in a financial market learn whether to be informed and which information to use in their demand for risky assets? We describe in this paper an agent-based model where heterogeneous traders seek short-term profits and differ in their choices to use or discard some signals. In the model, a vector of fresh news/signals is available at every period and some (but not all) the signals affect the stochastic payoff of the stock. Under an evolutionary dynamics favouring higher myopic returns we find that, in equilibrium, traders mostly end up in either discarding all signals or being (perfectly) informed using all the relevant signals (paying the related costs). Moreover, the rate of use of information strongly depends on the "complexity" of the market: an excessively large abundance of signals to be screened or a high volatility of the market, result in large shares of passive agents who overestimate the market's risk; conversely, low market complexity is associated with a more intense use of information and aggressiveness of informed traders. Evolutionary models and Agent-based models and Information in financial markets

Keywords: financial markets w information; agent-based models; evolutionary game theory; equity premium puzzle (search for similar items in EconPapers)
JEL-codes: D83 D91 G17 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2024
New Economics Papers: this item is included in nep-cmp, nep-evo, nep-gth and nep-hme
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