Increasing risk: Dynamic mean-preserving spreads
Jean-Louis Arcand (),
Max-Olivier Hongler and
Journal of Mathematical Economics, 2020, vol. 86, issue C, 69-82
We extend the celebrated Rothschild and Stiglitz (1970) definition of Mean-Preserving Spreads to a dynamic framework. We adapt the original integral conditions to transition probability densities, and give sufficient conditions for their satisfaction. We then focus on a class of nonlinear scalar diffusion processes, the super-diffusive ballistic process, and prove that it satisfies the integral conditions. We further prove that this class is unique among Brownian bridges. This class of processes can be generated by a random superposition of linear Markov processes with constant drifts. This exceptionally simple representation enables us to systematically revisit, by means of the properties of dynamic mean-preserving spreads, workhorse economic models originally based on White Gaussian Noise. A selection of four examples is presented and explicitly solved.
Keywords: Increasing dynamic risk; Dynamic mean-preserving spreads; Stochastic differential equations; Non-Gaussian diffusion; Super-diffusive noise source (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:mateco:v:86:y:2020:i:c:p:69-82
Access Statistics for this article
Journal of Mathematical Economics is currently edited by Atsushi (A.) Kajii
More articles in Journal of Mathematical Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().