4,083 research outputs found
Large Dimensional Analysis and Optimization of Robust Shrinkage Covariance Matrix Estimators
This article studies two regularized robust estimators of scatter matrices
proposed (and proved to be well defined) in parallel in (Chen et al., 2011) and
(Pascal et al., 2013), based on Tyler's robust M-estimator (Tyler, 1987) and on
Ledoit and Wolf's shrinkage covariance matrix estimator (Ledoit and Wolf,
2004). These hybrid estimators have the advantage of conveying (i) robustness
to outliers or impulsive samples and (ii) small sample size adequacy to the
classical sample covariance matrix estimator. We consider here the case of
i.i.d. elliptical zero mean samples in the regime where both sample and
population sizes are large. We demonstrate that, under this setting, the
estimators under study asymptotically behave similar to well-understood random
matrix models. This characterization allows us to derive optimal shrinkage
strategies to estimate the population scatter matrix, improving significantly
upon the empirical shrinkage method proposed in (Chen et al., 2011).Comment: Journal of Multivariate Analysi
A Monte Carlo Study of Growth Regressions
Using Monte Carlo simulations, this paper evaluates the bias properties of common estimators used in growth regressions derived from the Solow model. We explicitly allow for measurement error in the right-hand side variables, as well as country-specific effects that are correlated with the regressors. Our results suggest that using an OLS estimator applied to a single cross-section of variables averaged over time (the between estimator) performs best in terms of the extent of bias on each of the estimated coefficients. The fixed-effects estimator and the Arellano-Bond estimator greatly overstate the speed of convergence under a wide variety of assumptions concerning the type and extent of measurement error, while between understates it somewhat. Finally, fixed effects and Arellano-Bond bias towards zero the slope estimates on the human and physical capital accumulation variables.
A Robust Statistics Approach to Minimum Variance Portfolio Optimization
We study the design of portfolios under a minimum risk criterion. The
performance of the optimized portfolio relies on the accuracy of the estimated
covariance matrix of the portfolio asset returns. For large portfolios, the
number of available market returns is often of similar order to the number of
assets, so that the sample covariance matrix performs poorly as a covariance
estimator. Additionally, financial market data often contain outliers which, if
not correctly handled, may further corrupt the covariance estimation. We
address these shortcomings by studying the performance of a hybrid covariance
matrix estimator based on Tyler's robust M-estimator and on Ledoit-Wolf's
shrinkage estimator while assuming samples with heavy-tailed distribution.
Employing recent results from random matrix theory, we develop a consistent
estimator of (a scaled version of) the realized portfolio risk, which is
minimized by optimizing online the shrinkage intensity. Our portfolio
optimization method is shown via simulations to outperform existing methods
both for synthetic and real market data
PROSPECTS FOR THE CANADIAN DAIRY SECTOR FOLLOWING THE UPCOMING NAFTA PANEL RULING
International Relations/Trade,
Observation and inverse problems in coupled cell networks
A coupled cell network is a model for many situations such as food webs in
ecosystems, cellular metabolism, economical networks... It consists in a
directed graph , each node (or cell) representing an agent of the network
and each directed arrow representing which agent acts on which one. It yields a
system of differential equations , where the component
of depends only on the cells for which the arrow
exists in . In this paper, we investigate the observation problems in
coupled cell networks: can one deduce the behaviour of the whole network
(oscillations, stabilisation etc.) by observing only one of the cells? We show
that the natural observation properties holds for almost all the interactions
Sequential resonant tunneling in quantum cascade lasers
A model of sequential resonant tunneling transport between two-dimensional
subbands that takes into account explicitly elastic scattering is investigated.
It is compared to transport measurements performed on quantum cascade lasers
where resonant tunneling processes are known to be dominating. Excellent
agreement is found between experiment and theory over a large range of current,
temperature and device structures
Ring-opening copolymerization (ROCOP): synthesis and properties of polyesters and polycarbonates
Controlled routes to prepare polyesters and polycarbonates are of interest due to the widespread application of these materials and the opportunities provided to prepare new copolymers. Furthermore, ring-opening copolymerization may enable new poly(ester–carbonate) materials to be prepared which are inaccessible using alternative polymerizations. This review highlights recent advances in the ring-opening copolymerization catalysis, using epoxides coupled with anhydrides or CO2, to produce polyesters and polycarbonates. In particular, the structures and performances of various homogeneous catalysts are presented for the epoxide–anhydride copolymerization. The properties of the resultant polyesters and polycarbonates are presented and future opportunities highlighted for developments of both the materials and catalysts
A cognitive approach to the expected value of work integration social enterprises
Research Summary
Oftentimes, social enterprises simultaneously pursue competing organizational goals. For example, this can mean having a social goal (e.g., integrating vulnerable populations into the labor market) and a commercial goal (e.g., being profitable). I propose a theory according to which for such social enterprises, how they are perceived depends on how their goals are presented and on the type of categorization process used by their evaluating audience. These two factors together impact a venture's legitimacy and expected value. I also show that these effects vary with the level of knowledgeability of the audience performing the evaluation. Taken together, the results of this paper have implications for the cognitive perspective on strategic entrepreneurship as well as the literature on categories in markets and on hybrid organizations.
Managerial Summary
I study the different category primings that influence the customer's perception of work integration social enterprises (WISEs). These social enterprises can either direct their customers' attention toward comparability with a category prototype (prototype-based categorization), or toward a customer goal (goal-based categorization). I find support for the idea that, depending on which organizational goal is emphasized first and foremost by a WISE (e.g., social or commercial), the activation of either category priming impacts the venture's capacity to create value. Ultimately, this work establishes the cognitive foundations of social enterprises' competitive advantage by showing the type of category priming (goal-based vs. prototype-based categorization) that positively impacts a WISE's expected value as a function of “who” the targeted customers (less vs. more knowledgeable customers) are
Synchronization of Bloch oscillations by a ring cavity
We consider Bloch oscillations of ultracold atoms stored in a one-dimensional
vertical optical lattice and simultaneously interacting with a unidirectionally
pumped optical ring cavity whose vertical arm is collinear with the optical
lattice. We find that the feedback provided by the cavity field on the atomic
motion synchronizes Bloch oscillations via a mode-locking mechanism, steering
the atoms to the lowest Bloch band. It also stabilizes Bloch oscillations
against noise, and even suppresses dephasing due to atom-atom interactions.
Furthermore, it generates periodic bursts of light emitted into the
counter-propagating cavity mode, providing a non-destructive monitor of the
atomic dynamics. All these features may be crucial for future improvements of
the design of atomic gravimeters based on recording Bloch oscillations.Comment: 14 pages, 7 figure
Rotational intermittency and turbulence induced lift experienced by large particles in a turbulent flow
The motion of a large, neutrally buoyant, particle, freely advected by a
turbulent flow is determined experimentally. We demonstrate that both the
translational and angular accelerations exhibit very wide probability
distributions, a manifestation of intermittency. The orientation of the angular
velocity with respect to the trajectory, as well as the translational
acceleration conditioned on the spinning velocity provide evidence of a lift
force acting on the particle.Comment: 4 page, 4 figure
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