Peer-to-Peer Lending: a Growth-Collapse Model and its Steady-State Analysis
Onno Boxma (),
David Perry and
Wolfgang Stadje
Additional contact information
Onno Boxma: Eindhoven University of Technology
David Perry: Holon Institute of Technology
Wolfgang Stadje: University of Osnabrück
Mathematical Methods of Operations Research, 2022, vol. 96, issue 2, No 4, 233-258
Abstract:
Abstract We present a stochastic growth-collapse model for the capital process of a peer-to-peer lending platform. New lenders arrive according to a compound Poisson-type process with a state-dependent intensity function; the growth of the lending capital is from time to time interrupted by partial collapses whose arrival intensities and sizes are also state-dependent. In our model the capital level administered via the platform is the crucial quantity for the generated profit, because the brokerage fee is a fixed (small) fraction of it. Therefore we study its steady-state probability distribution as a key performance measure. In the case of exponentially distributed upward jumps we derive an explicit expression for its probability density, for quite general arrival rates of upward and downward jumps and for certain collapse mechanisms. In the case of generally distributed upward jumps, we derive an explicit expression for the Laplace transform of the steady-state cash level density in various special cases. An alternative model featuring up and down periods and a shot noise mechanism for the downward evolution is also analyzed in steady state.
Keywords: P2P lending; Compound Poisson; Growth-collapse; Shot noise (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s00186-022-00793-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:spr:mathme:v:96:y:2022:i:2:d:10.1007_s00186-022-00793-x
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/00186
DOI: 10.1007/s00186-022-00793-x
Access Statistics for this article
Mathematical Methods of Operations Research is currently edited by Oliver Stein
More articles in Mathematical Methods of Operations Research from Springer, Gesellschaft für Operations Research (GOR), Nederlands Genootschap voor Besliskunde (NGB)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().