Izvorni znanstveni članak
https://doi.org/10.1080/1331677X.2021.2021098
Agent-based artificial financial market with evolutionary algorithm
Yan Chen
Zezhou Xu
Wenqiang Yu
Sažetak
In traditional financial studies, existing approaches are unable to
address increasingly complex problems. In this paper, an artificial
financial market is proposed, in accordance with the adaptation
market hypothesis, using artificial intelligence algorithms. This
market includes three types of agents with different investments
and risk preferences, representing the heterogeneity of traders.
Genetic network programming is combined with a state-actionreward-state-action (SARSA)(k) algorithm for designing the market
to reflect the adaptation of technical agents. A pricing mechanism
is taken into consideration, based on the auction mechanism of
the Chinese securities market. The characteristics of price time
series are analyzed to determine whether excessive volatility
exists in four different markets. Explanations are provided for the
corresponding financial phenomena considering the hypotheses
under the proposed novel artificial financial market.
Ključne riječi
Artificial financial market; evolutionary algorithm; genetic network programming; SARSA(k) algorithm
Hrčak ID:
302787
URI
Datum izdavanja:
31.3.2023.
Posjeta: 165 *