Polynomial processes in stochastic portfolio theory

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.     

Analytical representation of concave and quasiconcave homogeneous functions

The formula which implements bijection between the class of concave linearly homogeneous functions defined on the nonnegative orthant of an arithmetic space and the simpler class of concave functions defined on the standard (probabilistic) simplex is presented. Two generalizations of this formula for analytical representation of quasiconcave homogeneous function are also proposed. These formulas particularly extend opportunities of modelling production objects and consumption.     

Use of stochastic and mathematical programming in?portfolio theory and practice

Standard finance portfolio theory draws graphs and writes equations usually with no constraints and frequently in the univariate case. However, in reality, there are multivariate random variables and multivariate asset weights to determine with constraints. Also there are the effects of transaction costs on asset prices in the theory and calculation of optimal portfolios in the static and dynamic cases. There we use various stochastic programming, linear complementary, quadratic programming and nonlinear programming problems. This paper begins with the simplest problems and builds the theory to the more complex cases and then applies it to real financial asset allocation problems, hedge funds and professional racetrack betting. This paper is based on a keynote lecture at the APMOD conference in Madrid in June 2006. It was also presented at the London Business School. Many thanks are due to APMOD organizers Antonio Alonso-Ayuso, Laureano Escudero, and Andres Ramos for inviting me and for excellent hospitality in Madrid. Thanks are also due to my teachers at Berkeley who got me on the right track on stochastic and mathematical programming, especially Olvi Mangasarian, Roger Wets and Willard Zangwill, and my colleagues and co-authors on portfolio theory in finance and horseracing, especially Chanaka Edirishinge, Donald Hausch, Jarl Kallberg, Victor Lo, Leonard MacLean, Raymond Vickson and Yonggan Zhao.     

Generalized-Hukuhara penalty method for optimization problem with interval-valued functions and its application in interval-valued portfolio optimization problems

In this study, a gH-penalty method is developed to obtain efficient solutions to constrained optimization problems with interval-valued functions. The algorithmic implementation of the proposed method is illustrated. In order to develop the gH-penalty method, an interval-valued penalty function is defined and the characterization of efficient solutions of a CIOP is done. As an application of the proposed method, a portfolio optimization problem with interval-valued return is solved.     

Inframonogenic functions and their applications in 3‐dimensional elasticity theory

Solutions of the sandwich equation , where stands for the first‐order differential operator (called Dirac operator) in the Euclidean space , are known as inframonogenic functions. These functions generalize in a natural way the theory of kernels associated with , the nowadays well‐known monogenic functions, and can be viewed also as a refinement of the biharmonic ones. In this paper we deepen study the connections between inframonogenic functions and the solutions of the homogeneous Lamé‐Navier system in . Our findings allow to shed some new light on the structure of the solutions of this fundamental system in 3‐dimensional elasticity theory.     

Möbius functions and semigroup representation theory

This paper explores several applications of Möbius functions to the representation theory of finite semigroups. We extend Solomon's approach to the semigroup algebra of a finite semilattice via Möbius functions to arbitrary finite inverse semigroups. This allows us to explicitly calculate the orthogonal central idempotents decomposing an inverse semigroup algebra into a direct product of matrix algebras over group rings. We also extend work of Bidigare, Hanlon, Rockmore and Brown on calculating eigenvalues of random walks associated to certain classes of finite semigroups; again Möbius functions play an important role.