HYBRID ATLAS MODELS
By Tomoyuki Ichiba, V. Papathanakos, Adrian Banner, Ioannis Karatzas, Robert Fernholz. 2009
136 citations recorded by the source corpus.
We study Atlas-type models of equity markets with local characteristics that depend on both name and rank, and in ways that induce a stable capital distribution. Ergodic properties and rankings of processes are examined with reference to the theory of reflected Brownian motions in polyhedral domains. In the context of such models we discuss properties of various investment strategies, including the so-called growth-optimal and universal portfolios.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/fe6e3fb04e32f0be4a0661fc8bf4e2e0e1291d6f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Mykhaylo Shkolnikov
- Tomoyuki Ichiba
- Soumik Pal
- Ioannis Karatzas
- Khoa Le
- Gordan Zitkovic
- Eitan Tadmor
In Finance
- Mykhaylo Shkolnikov
- Soumik Pal
- Tomoyuki Ichiba
- Ioannis Karatzas
- M'at'e Gerencs'er
- Konstantinos Dareiotis
- Khoa Le
- Constantinos Kardaras
Citations in the corpus
- Systems of Brownian particles with asymmetric collisions (2012, background): “8) in [23]), we know that the reflected Brownian motion of spacings in (2.”
- Convergence rates for rank-based models with applications to portfolio theory (2011, methodology): “By Theorem 2 in [24] the probability measure ν is a product of Exponential distributions with parameters α̃k, k = 1, .”
- Strong solutions of stochastic equations with rank-based coefficients (2011, methodology): “ of triple collisions under conditions of sufficiently strong repulsion. Preview: The present paper is organized as follows. Section 2 collects a number of preliminaries, most notably results from [1], [12], [7] and [16] that are crucial in our 4 TOMOYUKIICHIBA,IOANNISKARATZASANDMYKHAYLOSHKOLNIKOV con”
- Quantifying a convergence theorem of Gyöngy and Krylov (2021, background): “As a few examples, they are used in finance for modelling equity markets (see, [16]), in neuroscience for modelling interacting neurons that follow integrate-and-fire type dynamics (see, [12]), and also in the modelling of energy storage problems (see, [39]).”