Vladimir Dobric, Lehigh University

Fractional Brownian motion and optimization by ellipsoids Let [latex](Z_{t}^{H})_{tin(0,infty)}[/latex] be a fractional Brownian motion with Hurst index H, [latex]delta>0[/latex] and [latex](X_{i}^{H})_{i=1}^{infty}[/latex] be its [latex]delta[/latex] fractional Brownian noise, that is [latex]X_{i}^{H}=Z_{idelta}^{H}-Z_{(i-1)delta}^{H}[/latex]. Set [latex]Y_{i}^{H}=(((X_{2i}^{H}+X_{2i-1}^{H})/(sqrt{2})),((X_{2i}^{H}-X_{2i-1}^{H})/(sqrt2)))[/latex] and let [latex]E_{V}[/latex] be the family of all

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Ban Kawas, Lehigh University

Log-robust portfolio management We present a robust optimization approach to portfolio management under uncertainty that (i) builds upon the well-established Lognormal model for stock prices while addressing its limitations, and (ii) incorporates the imperfect knowledge on the true distribution of

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Yuichi Takano, University of Tsukuba

Constant Rebalanced Portfolio Optimization under Nonlinear Transaction Costs In this paper, we study a multi-period portfolio optimization where the conditional value-at-risk (CVaR) is controlled as well as the expected return, and the so-called constant rebalancing strategy is employed under nonlinear

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Juan Vera, University of Waterloo

New Relaxation Schemes for Polynomial Programing We present a new representation theorem for positiveness of polynomials with degree bounds. This new result has a elementary proof, and interesting consequences for polynomial programing (PP). In particular we present how to exploit

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Zumbul Bulut, Lehigh University

A new efficient heursitic for the design and analysis of distribution systems Distribution systems are one of the most difficult network topologies to analyze and most approaches in the literature are heuristic. Assuming a FIFO allocation policy and base-stock inventory

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