Optimal Trading with Differing Trade Signals
Ryan Donnelly and
Matthew Lorig
Applied Mathematical Finance, 2020, vol. 27, issue 4, 317-344
Abstract:
We consider the problem of maximizing portfolio value when an agent has a subjective view on asset value which differs from the traded market price. The agent’s trades will have a price impact which affects the price at which the asset is traded. In addition to the agent’s trades affecting the market price, the agent may change his view on the asset’s value if its difference from the market price persists. We also consider a situation of several agents interacting and trading simultaneously when they have a subjective view of the asset value. Two cases of the subjective views of agents are considered: one in which they all share the same information, and one in which they all have an individual signal correlated with price innovations. To study the large agent problem we take a mean-field game approach which remains tractable. After classifying the mean-field equilibrium we compute the cross-sectional distribution of agents’ inventories and the dependence of price distribution on the amount of shared information among the agents.
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://hdl.handle.net/10.1080/1350486X.2020.1847672 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:apmtfi:v:27:y:2020:i:4:p:317-344
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAMF20
DOI: 10.1080/1350486X.2020.1847672
Access Statistics for this article
Applied Mathematical Finance is currently edited by Professor Ben Hambly and Christoph Reisinger
More articles in Applied Mathematical Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().