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Convergence of trading strategies in continuous double auction markets with boundedly-rational networked traders.
- Source :
- Review of Quantitative Finance & Accounting; Jan2018, Vol. 50 Issue 1, p301-352, 52p
- Publication Year :
- 2018
-
Abstract
- This paper considers the convergence of trading strategies among artificial traders connected to one another in a social network and trading in a continuous double auction financial marketplace. Convergence is studied by means of an agent-based simulation model called the Social Network Artificial stoCk marKet model. Six different canonical network topologies (including no-network) are used to represent the possible connections between artificial traders. Traders learn from the trading experiences of their connected neighbours by means of reinforcement learning. The results show that the proportions of traders using particular trading strategies are eventually stable. Which strategies dominate in these stable states depends to some extent on the particular network topology of trader connections and the types of traders. [ABSTRACT FROM AUTHOR]
- Subjects :
- ECONOMIC convergence
MARKETPLACES
AUCTIONS
STRATEGIC planning
SOCIAL network theory
Subjects
Details
- Language :
- English
- ISSN :
- 0924865X
- Volume :
- 50
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Review of Quantitative Finance & Accounting
- Publication Type :
- Academic Journal
- Accession number :
- 127194063
- Full Text :
- https://doi.org/10.1007/s11156-017-0631-3