International Sentiment Spillovers in Equity Returns

This paper examines the extent of spillovers from US investor sentiment on G7 aggregate market, value and growth stock returns. As a proxy for investor sentiment, we include individual investor survey, measured by the University of Michigan consumer confidence index and market sentiment measured by Baker and Wurgler composite sentiment index. Using monthly data for the period January 1991 to December 2013, our results indicate the presence of significant spillover effects of US investor sentiment on G7 stock returns. Our findings from generalized impulse response functions show that aggregate market and growth stocks of all non-US G7 countries are significantly affected by the propagation of the US market sentiment. The financial crisis of 2007 has played a significant role in affecting value stock returns in these countries. Our findings further reveal that both the rational and irrational components of the US individual investor sentiment do not play any significant role in affecting international stock returns

Factor modeling for high dimensional time series.

Chapter 1: Identifying the finite dimensionality of curve time series The curve time series framework provides a convenient vehicle to model some types of nonstationary time series in a stationary framework. We propose a new method to identify the finite dimensionality of curve time series based on the autocorrelation between different curves. Based upon the duality relation between row and column subspaces of a data matrix, we show that the practical implementation of our methodology reduces to the eigenanalysis of a real matrix. Furthermore, the determination of the dimensionality is equivalent to indentifying the number of non-zero eigenvalues of this same matrix. For this purpose we propose a simple bootstrap test. Asymptotic properties of our methodology are investigated. The proposed methodology is illustrated with some simulation studies as well as an application to IBM intraday return densities. Chapter 2: Methodology and convergence rates for factor modeling of multiple time series An important task in modeling multiple time series is to obtain some form of dimension reduction. We tackle this problem using a factor model where the estimation of the factor loading space is constructed via eigenanalysis of a matrix which is a simple function of the sample autocovariance matrices. The number of factors is then equal to the number of "non-zero" eigenvalues of this matrix. We use the term "non-zero" loosely because in practice it is unlikely that there will be any eigenvalues which are exactly zero. However, our theoretical results suggest that the sample eigenvalues whose population counterparts are zero are "super-consistent" (i.e. they converge to zero at a n rate) whereas the sample eigenvalues whose population counterparts are non-zero converge at an ordinary parametric rate of root-n. Here n denotes the sample size. This striking result is supported by simulation evidence and consequences for inference are discussed. In addition, we study the properties of the factor loading space under very general conditions (including possible non-stationarity) and a simple white noise test for empirically determining the number of non-zero eigenvalues is proposed and theoretically justified. We also provide an example of a heuristic threshold based estimator for the number of factors and prove that it yields a consistent estimator provided that the threshold is chosen to be of an appropriate order. Finally we conclude with an analysis of some implied volatility datasets

Quantum critical scaling of the geometric tensors

Berry phases and the quantum-information theoretic notion of fidelity have been recently used to analyze quantum phase transitions from a geometrical perspective. In this paper we unify these two approaches showing that the underlying mechanism is the critical singular behavior of a complex tensor over the Hamiltonian parameter space. This is achieved by performing a scaling analysis of this quantum geometric tensor in the vicinity of the critical points. In this way most of the previous results are understood on general grounds and new ones are found. We show that criticality is not a sufficient condition to ensure superextensive divergence of the geometric tensor, and state the conditions under which this is possible. The validity of this analysis is further checked by exact diagonalization of the spin-1/2 XXZ Heisenberg chain.Comment: Typos correcte

Universal geometric entanglement close to quantum phase transitions

Under successive Renormalization Group transformations applied to a quantum state $\ket{\Psi}$ of finite correlation length $\xi$, there is typically a loss of entanglement after each iteration. How good it is then to replace $\ket{\Psi}$ by a product state at every step of the process? In this paper we give a quantitative answer to this question by providing first analytical and general proofs that, for translationally invariant quantum systems in one spatial dimension, the global geometric entanglement per region of size $L \gg \xi$ diverges with the correlation length as $(c/12) \log{(\xi/\epsilon)}$ close to a quantum critical point with central charge $c$, where $\epsilon$ is a cut-off at short distances. Moreover, the situation at criticality is also discussed and an upper bound on the critical global geometric entanglement is provided in terms of a logarithmic function of $L$.Comment: 4 pages, 3 figure

Spatial models of essential fish habitat (South Inshore and Offshore marine plan areas)

The aim of the project was to improve the spatial resolution of data on essential fish habitats for key fish species (both of commercial and ecological relevance) in the South Inshore and South Offshore marine plan areas, and to assess the relative value of these fish habitats to the regional commercial fisheries productivity and the ecosystem function.The report's recommendations were formulated on how to address the limitations in future studies to allow improvement of the methodology and its application

Considerations on Neuberger's operator

We discuss new approaches to the numerical implementation of Neuberger's operator for lattice fermions and the possible use of block spin transformations.Comment: LATTICE 99 (Improvement and Renormalization

EFFECT OF MULLIGAN’S CALCANEAL TAPING VERSUS KINESIOTAPING IN PLANTAR FASCIITIS

Objective: The objective of this study is to compare the effect of Mulligan’s calcaneal taping versus kinesiotaping in plantar fasciitis. Methods: A total of 44 subjects diagnosed with plantar fasciitis were included in this study. The mean age was 31.93 years. This subjects were allocated by lottery method into two groups (Group A - therapeutic ultrasound (US), exercises, and Mulligan’s calcaneal taping and Group B - therapeutic US, exercises, and Kinesio taping). Before and after the treatment protocol, the subjects were assessed for pain by visual analog scale (VAS) and foot function by revised-foot function index (FFI-R) questionnaire. Result: Pre- and post-treatment protocol was analyzed using paired and unpaired t-test. Intragroup analysis of VAS revealed statistically reduction in VAS post-intervention for both groups. This was performed using paired t-test Group A (p<0.0001) and Group B (p<0.0001). Intragroup analysis of total (FFI-R) revealed statistically reduction in FFI-R score post-intervention for both groups. This was done using paired t-test Group A (p<0.0001) and Group B (p<0.0001). Conclusion: Mulligan’s calcaneal taping was more effective than kinesiotaping in reducing VAS and FFI-R score in subject with plantar fasciitis

On the optimal feedback control of linear quantum systems in the presence of thermal noise

We study the possibility of taking bosonic systems subject to quadratic Hamiltonians and a noisy thermal environment to non-classical stationary states by feedback loops based on weak measurements and conditioned linear driving. We derive general analytical upper bounds for the single mode squeezing and multimode entanglement at steady state, depending only on the Hamiltonian parameters and on the number of thermal excitations of the bath. Our findings show that, rather surprisingly, larger number of thermal excitations in the bath allow for larger steady-state squeezing and entanglement if the efficiency of the optimal continuous measurements conditioning the feedback loop is high enough. We also consider the performance of feedback strategies based on homodyne detection and show that, at variance with the optimal measurements, it degrades with increasing temperature.Comment: 10 pages, 2 figures. v2: minor changes to the letter; better explanation of the necessary and sufficient conditions to achieve the bounds (in the supplemental material); v3: title changed; comparison between optimal general-dyne strategy and homodyne strategy is discussed; supplemental material included in the manuscript and few references added. v4: published versio