Optimal Investment Under Transaction Costs: A Threshold Rebalanced Portfolio Approach

We study optimal investment in a financial market having a finite number of assets from a signal processing perspective. We investigate how an investor should distribute capital over these assets and when he should reallocate the distribution of the funds over these assets to maximize the cumulative wealth over any investment period. In particular, we introduce a portfolio selection algorithm that maximizes the expected cumulative wealth in i.i.d. two-asset discrete-time markets where the market levies proportional transaction costs in buying and selling stocks. We achieve this using "threshold rebalanced portfolios", where trading occurs only if the portfolio breaches certain thresholds. Under the assumption that the relative price sequences have log-normal distribution from the Black-Scholes model, we evaluate the expected wealth under proportional transaction costs and find the threshold rebalanced portfolio that achieves the maximal expected cumulative wealth over any investment period. Our derivations can be readily extended to markets having more than two stocks, where these extensions are pointed out in the paper. As predicted from our derivations, we significantly improve the achieved wealth over portfolio selection algorithms from the literature on historical data sets.Comment: Submitted to IEEE Transactions on Signal Processin

Improved thermal isolation of silicon suspended platforms for an all-silicon thermoelectric microgenerator based on large scale integration of Si nanowires as thermoelectric material

Special suspended micro-platforms have been designed as a part of silicon compatible planar thermoelectric microgenerators. Bottom-up grown silicon nanowires are going to bridge in the future such platforms to the surrounding silicon bulk rim. They will act as thermoelectric material thus configuring an all-silicon thermoelectric device. In the new platform design other additional bridging elements (usually auxiliary support silicon beams) are substituted by low conductance thin film dielectric membranes in order to maximize the temperature difference developed between both areas. These membranes follow a sieve-like design that allows fabricating them with a short additional wet anisotropic etch step. © Published under licence by IOP Publishing Ltd.Peer ReviewedPostprint (published version

Robust estimation in flat fading channels under bounded channel uncertainties

Cataloged from PDF version of article.We investigate channel equalization problem for time-varying flat fading channels under bounded channel uncertainties. We analyze three robust methods to estimate an unknown signal transmitted through a time-varying flat fading channel. These methods are based on minimizing certain meansquare error criteria that incorporate the channel uncertainties into their problem formulations instead of directly using the inaccurate channel information that is available. We present closed-form solutions to the channel equalization problems for each method and for both zero mean and nonzero mean signals. We illustrate the performances of the equalization methods through simulations. © 2013 Elsevier Inc. All rights reserved

Optimization of Single-Sided Charge-Sharing Strip Detectors

Simulation of the charge sharing properties of single-sided CZT strip detectors with small anode pads are presented. The effect of initial event size, carrier repulsion, diffusion, drift, trapping and detrapping are considered. These simulations indicate that such a detector with a 150 µm pitch will provide good charge sharing between neighboring pads. This is supported by a comparison of simulations and measurements for a similar detector with a coarser pitch of 225 µm that could not provide sufficient sharing. The performance of such a detector used as a gamma-ray imager is discussed

RAM: A Relativistic Adaptive Mesh Refinement Hydrodynamics Code

We have developed a new computer code, RAM, to solve the conservative equations of special relativistic hydrodynamics (SRHD) using adaptive mesh refinement (AMR) on parallel computers. We have implemented a characteristic-wise, finite difference, weighted essentially non-oscillatory (WENO) scheme using the full characteristic decomposition of the SRHD equations to achieve fifth-order accuracy in space. For time integration we use the method of lines with a third-order total variation diminishing (TVD) Runge-Kutta scheme. We have also implemented fourth and fifth order Runge-Kutta time integration schemes for comparison. The implementation of AMR and parallelization is based on the FLASH code. RAM is modular and includes the capability to easily swap hydrodynamics solvers, reconstruction methods and physics modules. In addition to WENO we have implemented a finite volume module with the piecewise parabolic method (PPM) for reconstruction and the modified Marquina approximate Riemann solver to work with TVD Runge-Kutta time integration. We examine the difficulty of accurately simulating shear flows in numerical relativistic hydrodynamics codes. We show that under-resolved simulations of simple test problems with transverse velocity components produce incorrect results and demonstrate the ability of RAM to correctly solve these problems. RAM has been tested in one, two and three dimensions and in Cartesian, cylindrical and spherical coordinates. We have demonstrated fifth-order accuracy for WENO in one and two dimensions and performed detailed comparison with other schemes for which we show significantly lower convergence rates. Extensive testing is presented demonstrating the ability of RAM to address challenging open questions in relativistic astrophysics.Comment: ApJS in press, 21 pages including 18 figures (6 color figures

Robust Least Squares Methods Under Bounded Data Uncertainties

Cataloged from PDF version of article.We study the problem of estimating an unknown deterministic signal that is observed through an unknown deterministic data matrix under additive noise. In particular, we present a minimax optimization framework to the least squares problems, where the estimator has imperfect data matrix and output vector information. We define the performance of an estimator relative to the performance of the optimal least squares (LS) estimator tuned to the underlying unknown data matrix and output vector, which is defined as the regret of the estimator. We then introduce an efficient robust LS estimation approach that minimizes this regret for the worst possible data matrix and output vector, where we refrain from any structural assumptions on the data. We demonstrate that minimizing this worst-case regret can be cast as a semi-definite programming (SDP) problem. We then consider the regularized and structured LS problems and present novel robust estimation methods by demonstrating that these problems can also be cast as SDP problems. We illustrate the merits of the proposed algorithms with respect to the well-known alternatives in the literature through our simulations

Continued Studies of Single-Sided Charge-Sharing CZT Strip Detectors

In this paper, we report progress in the study of thick single-sided charge-sharing cadmium zinc telluride (CZT) strip detector modules designed to perform gammaray spectroscopy and 3-D imaging. We report on continuing laboratory and simulation measurements of prototype detectors with 11×11 unit cells (15×15×7.5mm3 ). We report preliminary measurements of the 3-D spatial resolution. Our studies are aimed at developing compact, efficient, detector modules for 0.05 to 1 MeV gamma measurements while minimizing the number and complexity of the electronic readout channels. This is particularly important in space-based coded aperture and Compton telescope instruments that require large area, large volume detector arrays. Such arrays will be required for the NASA’s Black Hole Finder Probe (BHFP) and Advanced Compton Telescope (ACT). This design requires an anode pattern with contacts whose dimensions and spacing are roughly the size of the ionization charge cloud. The first prototype devices have 125µm anode contacts on 225µm pitch. Our studies conclude that finer pitch contacts will be required to improve imaging efficiency

Further studies of single-sided charge-sharing CZT strip detectors

We report progress in the study of a thick CZT strip detector module designed to perform gamma-ray spectroscopy and 3-D imaging. We report preliminary performance measurements of 7.5 mm thick single-sided charge-sharing strip detector prototype devices. This design features both row and column contacts on the anode surface. This electron-only approach addresses problems associated with poor hole transport in CZT that limit the thickness and energy range of double-sided strip detectors. This work includes laboratory and simulation studies aimed at developing compact, efficient, detector modules for 0.05 to 1 MeV gamma measurements while minimizing the number and complexity of the electronic readout channels. This is particularly important in space-based coded aperture and Compton telescope instruments that require large area, large volume detector arrays. Such arrays will be required for the NASA Black Hole Finder Probe (BHFP)and Advanced Compton Telescope (ACT). This new design requires an anode pattern with contacts whose dimensions and spacing are roughly the size of the ionization charge cloud. The first prototype devices have 125 μm anode contacts on 225 μm pitch. Our results demonstrate the principle of operation but suggest that even finer anode contact feature sizes will be necessary to achieve the desired performance

High carrier concentration induced effects on the bowing parameter and the temperature dependence of the band gap of Ga_xIn_1−xN

The influence of intrinsic carrier concentration on the compositional and temperature dependence of the bandgap of GaxIn1-xN is investigated in nominally undoped samples with Ga fractions of x = 0.019, 0.062, 0.324, 0.52, and 0.56. Hall Effect results show that the free carrier density has a very weak temperature dependence and increases about a factor of 4, when the Ga composition increases from x = 0.019 to 0.56. The photoluminescence (PL) peak energy has also weak temperature dependence shifting to higher energies and the PL line shape becomes increasingly asymmetrical and broadens with increasing Ga composition. The observed characteristics of the PL spectra are explained in terms of the transitions from free electron to localized tail states and the high electron density induced many-body effects. The bowing parameter of GaxIn1-xN is obtained from the raw PL data as 2.5 eV. However, when the high carrier density induced effects are taken into account, it increases by about 14% to 2.9 eV. Furthermore, the temperature dependence of the PL peak becomes more pronounced and follows the expected temperature dependence of the bandgap variation

A Deterministic Analysis of an Online Convex Mixture of Expert Algorithms

Cataloged from PDF version of article.We analyze an online learning algorithm that adaptively combines outputs of two constituent algorithms (or the experts) running in parallel to model an unknown desired signal. This online learning algorithm is shown to achieve (and in some cases outperform) the mean-square error (MSE) performance of the best constituent algorithm in the mixture in the steady-state. However, the MSE analysis of this algorithm in the literature uses approximations and relies on statistical models on the underlying signals and systems. Hence, such an analysis may not be useful or valid for signals generated by various real life systems that show high degrees of nonstationarity, limit cycles and, in many cases, that are even chaotic. In this paper, we produce results in an individual sequence manner. In particular, we relate the time-accumulated squared estimation error of this online algorithm at any time over any interval to the time-accumulated squared estimation error of the optimal convex mixture of the constituent algorithms directly tuned to the underlying signal in a deterministic sense without any statistical assumptions. In this sense, our analysis provides the transient, steady-state and tracking behavior of this algorithm in a strong sense without any approximations in the derivations or statistical assumptions on the underlying signals such that our results are guaranteed to hold. We illustrate the introduced results through examples. © 2012 IEEE