Polynomial processes in stochastic portfolio theory

Christa Cuchiero

Stochastic Processes and their Applications, 2019, vol. 129, issue 5, 1829-1872

Abstract: We introduce polynomial processes in the context of stochastic portfolio theory to model simultaneously companies’ market capitalizations and the corresponding market weights. These models substantially extend volatility stabilized market models considered in Fernholz and Karatzas (2005), in particular they allow for correlation between the individual stocks. At the same time they remain remarkably tractable which makes them applicable in practice, especially for estimation and calibration to high dimensional equity index data. In the diffusion case we characterize the polynomial property of the market capitalizations and their weights, exploiting the fact that the transformation between absolute and relative quantities perfectly fits the structural properties of polynomial processes. Explicit parameter conditions assuring the existence of a local martingale deflator and relative arbitrages with respect to the market portfolio are given and the connection to non-attainment of the boundary of the unit simplex is discussed. We also consider extensions to models with jumps and the computation of optimal relative arbitrage strategies.

Keywords: Stochastic portfolio theory; Relative arbitrage; Polynomial processes; Diffusions on the unit simplex; Boundary attainment; Tractable modeling; Polynomial neural networks (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (18)

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DOI: 10.1016/j.spa.2018.06.007

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