paper-with-me

홈 › Papers

Fragmentation in trader preferences among multiple markets: Market coexistence versus single market dominance

2020-12-07 · Robin Nicole, Aleksandra Alorić, Peter Sollich

Technological advancement has lead to an increase in number and type of trading venues and diversification of goods traded. These changes have re-emphasized the importance of understanding the effects of market competition: does proliferation of trading venues and increased competition lead to dominance of a single market or coexistence of multiple markets? In this paper, we address these questions in a stylized model of Zero Intelligence traders who make repeated decisions at which of three available markets to trade. We analyse the model numerically and analytically and find that parameters that govern traders' decisions -- memory length and intensity of choice, e.g. how strongly decisions are based on past success -- make the key distinctions between consolidated and fragmented steady states of the population of traders. All three markets coexist with equal shares of traders only when either learning is too weak and traders choose randomly, or when markets are identical. In the latter case, the population of traders is fragmented across the markets. For the more general case of markets with different biases, we note that market dominance is the more typical scenario. These results are interesting because previously either strong differentiation of markets or heterogeneity in the needs of traders was found to be a necessary condition for market coexistence. We show that, in contrast, these states can emerge simply as a consequence of co-adaptation of an initially homogeneous population of traders.

📄 PDF Abstract BibTeX arXiv:2012.04103

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Price Formation in Field Prediction Markets: the Wisdom in the Crowd

2022-09-19 · Frederik Bossaerts, Nitin Yadav, Peter Bossaerts, Chad Nash 외

Prediction markets are a popular, prominent, and successful structure for a collective intelligence platform. However the exact mechanism by which information known to the participating traders is incorporated into the m…

Prediction

Trader-Company Method: A Metaheuristic for Interpretable Stock Price Prediction

2020-12-18 · Katsuya Ito, Kentaro Minami, Kentaro Imajo, Kei Nakagawa

Investors try to predict returns of financial assets to make successful investment. Many quantitative analysts have used machine learning-based methods to find unknown profitable market rules from large amounts of market…

BIG-bench Machine LearningStock Price Prediction

Continuous-time Equilibrium Returns in Markets with Price Impact and Transaction Costs

2024-05-23 · Michail Anthropelos, Constantinos Stefanakis

We consider an Ito-financial market at which the risky assets' returns are derived endogenously through a market-clearing condition amongst heterogeneous risk-averse investors with quadratic preferences and random endowm…

Margin Trader: A Reinforcement Learning Framework for Portfolio Management with Margin and Constraints

2023-11-25 · The 4th ACM International Conference on AI in Finance 2023 11 · Jingyi Gu, Wenlu Du, A M Muntasir Rahman, Guiling Wang

In the field of portfolio management using reinforcement learn- ing, existing approaches have mainly focused on cash-only trading, overlooking the potential benefits and risks of margin trading. Incor- porating margin ac…

Deep Reinforcement LearningManagementPortfolio Optimizationreinforcement-learning+2

Periodic Trading Activities in Financial Markets: Mean-field Liquidation Game with Major-Minor Players

2024-08-18 · Yufan Chen, Lan Wu, Renyuan Xu, Ruixun Zhang

Motivated by recent empirical findings on the periodic phenomenon of aggregated market volumes in equity markets, we aim to understand the causes and consequences of periodic trading activities through a game-theoretic p…