The Random Matrix Theory of the Classical Compact Groups
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Random Matrix Theory and Covariance Estimation
Introduction Random matrix theory Estimating correlations Comparison with Barra Conclusion Appendix Random Matrix Theory and Covariance Estimation Jim Gatheral New York, October 3, 2008 Introduction Random matrix theory Estimating correlations Comparison with Barra Conclusion Appendix Motivation Sophisticated optimal liquidation portfolio algorithms that balance risk against impact cost involve inverting the covariance matrix. Eigenvalues of the covariance matrix that are small (or even zero) correspond to portfolios of stocks that have nonzero returns but extremely low or vanishing risk; such portfolios are invariably related to estimation errors resulting from insuffient data. One of the approaches used to eliminate the problem of small eigenvalues in the estimated covariance matrix is the so-called random matrix technique. We would like to understand: the basis of random matrix theory. (RMT) how to apply RMT to the estimation of covariance matrices. whether the resulting covariance matrix performs better than (for example) the Barra covariance matrix. Introduction Random matrix theory Estimating correlations Comparison with Barra Conclusion Appendix Outline 1 Random matrix theory Random matrix examples Wigner’s semicircle law The Marˇcenko-Pastur density The Tracy-Widom law Impact of fat tails 2 Estimating correlations Uncertainty in correlation estimates. Example with SPX stocks A recipe for filtering the sample correlation matrix 3 Comparison with Barra Comparison of eigenvectors The minimum variance portfolio Comparison of weights In-sample and out-of-sample performance 4 Conclusions 5 Appendix with a sketch of Wigner’s original proof Introduction Random matrix theory Estimating correlations Comparison with Barra Conclusion Appendix Example 1: Normal random symmetric matrix Generate a 5,000 x 5,000 random symmetric matrix with entries aij N(0, 1). -
Geometric Integration Theory Contents
Steven G. Krantz Harold R. Parks Geometric Integration Theory Contents Preface v 1 Basics 1 1.1 Smooth Functions . 1 1.2Measures.............................. 6 1.2.1 Lebesgue Measure . 11 1.3Integration............................. 14 1.3.1 Measurable Functions . 14 1.3.2 The Integral . 17 1.3.3 Lebesgue Spaces . 23 1.3.4 Product Measures and the Fubini–Tonelli Theorem . 25 1.4 The Exterior Algebra . 27 1.5 The Hausdorff Distance and Steiner Symmetrization . 30 1.6 Borel and Suslin Sets . 41 2 Carath´eodory’s Construction and Lower-Dimensional Mea- sures 53 2.1 The Basic Definition . 53 2.1.1 Hausdorff Measure and Spherical Measure . 55 2.1.2 A Measure Based on Parallelepipeds . 57 2.1.3 Projections and Convexity . 57 2.1.4 Other Geometric Measures . 59 2.1.5 Summary . 61 2.2 The Densities of a Measure . 64 2.3 A One-Dimensional Example . 66 2.4 Carath´eodory’s Construction and Mappings . 67 2.5 The Concept of Hausdorff Dimension . 70 2.6 Some Cantor Set Examples . 73 i ii CONTENTS 2.6.1 Basic Examples . 73 2.6.2 Some Generalized Cantor Sets . 76 2.6.3 Cantor Sets in Higher Dimensions . 78 3 Invariant Measures and the Construction of Haar Measure 81 3.1 The Fundamental Theorem . 82 3.2 Haar Measure for the Orthogonal Group and the Grassmanian 90 3.2.1 Remarks on the Manifold Structure of G(N,M).... 94 4 Covering Theorems and the Differentiation of Integrals 97 4.1 Wiener’s Covering Lemma and its Variants . -
Rotation Matrix Sampling Scheme for Multidimensional Probability Distribution Transfer
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume III-7, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic ROTATION MATRIX SAMPLING SCHEME FOR MULTIDIMENSIONAL PROBABILITY DISTRIBUTION TRANSFER P. Srestasathiern ∗, S. Lawawirojwong, R. Suwantong, and P. Phuthong Geo-Informatics and Space Technology Development Agency (GISTDA), Laksi, Bangkok, Thailand (panu,siam,rata,pattrawuth)@gistda.or.th Commission VII,WG VII/4 KEY WORDS: Histogram specification, Distribution transfer, Color transfer, Data Gaussianization ABSTRACT: This paper address the problem of rotation matrix sampling used for multidimensional probability distribution transfer. The distri- bution transfer has many applications in remote sensing and image processing such as color adjustment for image mosaicing, image classification, and change detection. The sampling begins with generating a set of random orthogonal matrix samples by Householder transformation technique. The advantage of using the Householder transformation for generating the set of orthogonal matrices is the uniform distribution of the orthogonal matrix samples. The obtained orthogonal matrices are then converted to proper rotation matrices. The performance of using the proposed rotation matrix sampling scheme was tested against the uniform rotation angle sampling. The applications of the proposed method were also demonstrated using two applications i.e., image to image probability distribution transfer and data Gaussianization. 1. INTRODUCTION is based on the Monge’s transport problem which is to find mini- mal displacement for mass transportation. The solution from this In remote sensing, the analysis of multi-temporal data is widely linear approach can be used as initial solution for non-linear prob- used in many applications such as urban expansion monitoring, ability distribution transfer methods. -
An Overview of Topological Groups: Yesterday, Today, Tomorrow
axioms Editorial An Overview of Topological Groups: Yesterday, Today, Tomorrow Sidney A. Morris 1,2 1 Faculty of Science and Technology, Federation University Australia, Victoria 3353, Australia; [email protected]; Tel.: +61-41-7771178 2 Department of Mathematics and Statistics, La Trobe University, Bundoora, Victoria 3086, Australia Academic Editor: Humberto Bustince Received: 18 April 2016; Accepted: 20 April 2016; Published: 5 May 2016 It was in 1969 that I began my graduate studies on topological group theory and I often dived into one of the following five books. My favourite book “Abstract Harmonic Analysis” [1] by Ed Hewitt and Ken Ross contains both a proof of the Pontryagin-van Kampen Duality Theorem for locally compact abelian groups and the structure theory of locally compact abelian groups. Walter Rudin’s book “Fourier Analysis on Groups” [2] includes an elegant proof of the Pontryagin-van Kampen Duality Theorem. Much gentler than these is “Introduction to Topological Groups” [3] by Taqdir Husain which has an introduction to topological group theory, Haar measure, the Peter-Weyl Theorem and Duality Theory. Of course the book “Topological Groups” [4] by Lev Semyonovich Pontryagin himself was a tour de force for its time. P. S. Aleksandrov, V.G. Boltyanskii, R.V. Gamkrelidze and E.F. Mishchenko described this book in glowing terms: “This book belongs to that rare category of mathematical works that can truly be called classical - books which retain their significance for decades and exert a formative influence on the scientific outlook of whole generations of mathematicians”. The final book I mention from my graduate studies days is “Topological Transformation Groups” [5] by Deane Montgomery and Leo Zippin which contains a solution of Hilbert’s fifth problem as well as a structure theory for locally compact non-abelian groups. -
Measure Theory John K. Hunter
Measure Theory John K. Hunter Department of Mathematics, University of California at Davis Abstract. These are some brief notes on measure theory, concentrating on n Lebesgue measure on R . Some missing topics I would have liked to have in- cluded had time permitted are: the change of variable formula for the Lebesgue n integral on R ; absolutely continuous functions and functions of bounded vari- ation of a single variable and their connection with Lebesgue-Stieltjes measures n on R; Radon measures on R , and other locally compact Hausdorff topological spaces, and the Riesz representation theorem for bounded linear functionals on spaces of continuous functions; and other examples of measures, including n k-dimensional Hausdorff measure in R , Wiener measure and Brownian mo- tion, and Haar measure on topological groups. All these topics can be found in the references. c John K. Hunter, 2011 Contents Chapter 1. Measures 1 1.1. Sets 1 1.2. Topological spaces 2 1.3. Extended real numbers 2 1.4. Outer measures 3 1.5. σ-algebras 4 1.6. Measures 5 1.7. Sets of measure zero 6 Chapter 2. Lebesgue Measure on Rn 9 2.1. Lebesgue outer measure 10 2.2. Outer measure of rectangles 12 2.3. Carath´eodory measurability 14 2.4. Null sets and completeness 18 2.5. Translational invariance 19 2.6. Borel sets 20 2.7. Borel regularity 22 2.8. Linear transformations 27 2.9. Lebesgue-Stieltjes measures 30 Chapter 3. Measurable functions 33 3.1. Measurability 33 3.2. Real-valued functions 34 3.3. -
An Introduction to Random Walks on Groups
An introduction to random walks on groups Jean-Fran¸coisQuint School on Information and Randomness, Puerto Varas, December 2014 Contents 1 Locally compact groups and Haar measure 2 2 Amenable groups 4 3 Invariant means 9 4 Almost invariant vectors 13 5 Random walks and amenable groups 15 6 Growth of groups 18 7 Speed of escape 21 8 Subgroups of SL2(R) 24 1 In these notes, we will study a basic question from the theory of random walks on groups: given a random walk e; g1; g2g1; : : : ; gn ··· g1;::: on a group G, we will give a criterion for the trajectories to go to infinity with linear speed (for a notion of speed which has to be defined). We will see that this property is related to the notion of amenability of groups: this is a fun- damental theorem which was proved by Kesten in the case of discrete groups and extended to the case of continuous groups by Berg and Christensen. We will give examples of this behaviour for random walks on SL2(R). 1 Locally compact groups and Haar measure In order to define random walks on groups, I need to consider probability measures on groups, which will be the distribution of the random walks. When the group is discrete, there is no technical difficulty: a probability measure is a function from the group to [0; 1], the sum of whose values is one. But I also want to consider non discrete groups, such as vector spaces, groups of matrices, groups of automorphisms of trees, etc. -
Workshop on Applied Matrix Positivity International Centre for Mathematical Sciences 19Th – 23Rd July 2021
Workshop on Applied Matrix Positivity International Centre for Mathematical Sciences 19th { 23rd July 2021 Timetable All times are in BST (GMT +1). 0900 1000 1100 1600 1700 1800 Monday Berg Bhatia Khare Charina Schilling Skalski Tuesday K¨ostler Franz Fagnola Apanasovich Emery Cuevas Wednesday Jain Choudhury Vishwakarma Pascoe Pereira - Thursday Sharma Vashisht Mishra - St¨ockler Knese Titles and abstracts 1. New classes of multivariate covariance functions Tatiyana Apanasovich (George Washington University, USA) The class which is refereed to as the Cauchy family allows for the simultaneous modeling of the long memory dependence and correlation at short and intermediate lags. We introduce a valid parametric family of cross-covariance functions for multivariate spatial random fields where each component has a covariance function from a Cauchy family. We present the conditions on the parameter space that result in valid models with varying degrees of complexity. Practical implementations, including reparameterizations to reflect the conditions on the parameter space will be discussed. We show results of various Monte Carlo simulation experiments to explore the performances of our approach in terms of estimation and cokriging. The application of the proposed multivariate Cauchy model is illustrated on a dataset from the field of Satellite Oceanography. 1 2. A unified view of covariance functions through Gelfand pairs Christian Berg (University of Copenhagen) In Geostatistics one examines measurements depending on the location on the earth and on time. This leads to Random Fields of stochastic variables Z(ξ; u) indexed by (ξ; u) 2 2 belonging to S × R, where S { the 2-dimensional unit sphere { is a model for the earth, and R is a model for time. -
Curriculum Vitae
Curriculum Vitae Assaf Naor Address: Princeton University Department of Mathematics Fine Hall 1005 Washington Road Princeton, NJ 08544-1000 USA Telephone number: +1 609-258-4198 Fax number: +1 609-258-1367 Electronic mail: [email protected] Web site: http://web.math.princeton.edu/~naor/ Personal Data: Date of Birth: May 7, 1975. Citizenship: USA, Israel, Czech Republic. Employment: • 2002{2004: Post-doctoral Researcher, Theory Group, Microsoft Research. • 2004{2007: Permanent Member, Theory Group, Microsoft Research. • 2005{2007: Affiliate Assistant Professor of Mathematics, University of Washington. • 2006{2009: Associate Professor of Mathematics, Courant Institute of Mathematical Sciences, New York University (on leave Fall 2006). • 2008{2015: Associated faculty member in computer science, Courant Institute of Mathematical Sciences, New York University (on leave in the academic year 2014{2015). • 2009{2015: Professor of Mathematics, Courant Institute of Mathematical Sciences, New York University (on leave in the academic year 2014{2015). • 2014{present: Professor of Mathematics, Princeton University. • 2014{present: Associated Faculty, The Program in Applied and Computational Mathematics (PACM), Princeton University. • 2016 Fall semester: Henry Burchard Fine Professor of Mathematics, Princeton University. • 2017{2018: Member, Institute for Advanced Study. • 2020 Spring semester: Henry Burchard Fine Professor of Mathematics, Princeton University. 1 Education: • 1993{1996: Studies for a B.Sc. degree in Mathematics at the Hebrew University in Jerusalem. Graduated Summa Cum Laude in 1996. • 1996{1998: Studies for an M.Sc. degree in Mathematics at the Hebrew University in Jerusalem. M.Sc. thesis: \Geometric Problems in Non-Linear Functional Analysis," prepared under the supervision of Joram Lindenstrauss. Graduated Summa Cum Laude in 1998. -
Doubling Algorithms with Permuted Lagrangian Graph Bases
DOUBLING ALGORITHMS WITH PERMUTED LAGRANGIAN GRAPH BASES VOLKER MEHRMANN∗ AND FEDERICO POLONI† Abstract. We derive a new representation of Lagrangian subspaces in the form h I i Im ΠT , X where Π is a symplectic matrix which is the product of a permutation matrix and a real orthogonal diagonal matrix, and X satisfies 1 if i = j, |Xij | ≤ √ 2 if i 6= j. This representation allows to limit element growth in the context of doubling algorithms for the computation of Lagrangian subspaces and the solution of Riccati equations. It is shown that a simple doubling algorithm using this representation can reach full machine accuracy on a wide range of problems, obtaining invariant subspaces of the same quality as those computed by the state-of-the-art algorithms based on orthogonal transformations. The same idea carries over to representations of arbitrary subspaces and can be used for other types of structured pencils. Key words. Lagrangian subspace, optimal control, structure-preserving doubling algorithm, symplectic matrix, Hamiltonian matrix, matrix pencil, graph subspace AMS subject classifications. 65F30, 49N10 1. Introduction. A Lagrangian subspace U is an n-dimensional subspace of C2n such that u∗Jv = 0 for each u, v ∈ U. Here u∗ denotes the conjugate transpose of u, and the transpose of u in the real case, and we set 0 I J = . −I 0 The computation of Lagrangian invariant subspaces of Hamiltonian matrices of the form FG H = H −F ∗ with H = H∗,G = G∗, satisfying (HJ)∗ = HJ, (as well as symplectic matrices S, satisfying S∗JS = J), is an important task in many optimal control problems [16, 25, 31, 36]. -
Integral Geometry – Measure Theoretic Approach and Stochastic Applications
Integral geometry – measure theoretic approach and stochastic applications Rolf Schneider Preface Integral geometry, as it is understood here, deals with the computation and application of geometric mean values with respect to invariant measures. In the following, I want to give an introduction to the integral geometry of polyconvex sets (i.e., finite unions of compact convex sets) in Euclidean spaces. The invariant or Haar measures that occur will therefore be those on the groups of translations, rotations, or rigid motions of Euclidean space, and on the affine Grassmannians of k-dimensional affine subspaces. How- ever, it is also in a different sense that invariant measures will play a central role, namely in the form of finitely additive functions on polyconvex sets. Such functions have been called additive functionals or valuations in the literature, and their motion invariant specializations, now called intrinsic volumes, have played an essential role in Hadwiger’s [2] and later work (e.g., [8]) on integral geometry. More recently, the importance of these functionals for integral geometry has been rediscovered by Rota [5] and Klain-Rota [4], who called them ‘measures’ and emphasized their role in certain parts of geometric probability. We will, more generally, deal with local versions of the intrinsic volumes, the curvature measures, and derive integral-geometric results for them. This is the third aspect of the measure theoretic approach mentioned in the title. A particular feature of this approach is the essential role that uniqueness results for invariant measures play in the proofs. As prerequisites, we assume some familiarity with basic facts from mea- sure and integration theory. -
January 2011 Prizes and Awards
January 2011 Prizes and Awards 4:25 P.M., Friday, January 7, 2011 PROGRAM SUMMARY OF AWARDS OPENING REMARKS FOR AMS George E. Andrews, President BÔCHER MEMORIAL PRIZE: ASAF NAOR, GUNTHER UHLMANN American Mathematical Society FRANK NELSON COLE PRIZE IN NUMBER THEORY: CHANDRASHEKHAR KHARE AND DEBORAH AND FRANKLIN TEPPER HAIMO AWARDS FOR DISTINGUISHED COLLEGE OR UNIVERSITY JEAN-PIERRE WINTENBERGER TEACHING OF MATHEMATICS LEVI L. CONANT PRIZE: DAVID VOGAN Mathematical Association of America JOSEPH L. DOOB PRIZE: PETER KRONHEIMER AND TOMASZ MROWKA EULER BOOK PRIZE LEONARD EISENBUD PRIZE FOR MATHEMATICS AND PHYSICS: HERBERT SPOHN Mathematical Association of America RUTH LYTTLE SATTER PRIZE IN MATHEMATICS: AMIE WILKINSON DAVID P. R OBBINS PRIZE LEROY P. S TEELE PRIZE FOR LIFETIME ACHIEVEMENT: JOHN WILLARD MILNOR Mathematical Association of America LEROY P. S TEELE PRIZE FOR MATHEMATICAL EXPOSITION: HENRYK IWANIEC BÔCHER MEMORIAL PRIZE LEROY P. S TEELE PRIZE FOR SEMINAL CONTRIBUTION TO RESEARCH: INGRID DAUBECHIES American Mathematical Society FOR AMS-MAA-SIAM LEVI L. CONANT PRIZE American Mathematical Society FRANK AND BRENNIE MORGAN PRIZE FOR OUTSTANDING RESEARCH IN MATHEMATICS BY AN UNDERGRADUATE STUDENT: MARIA MONKS LEONARD EISENBUD PRIZE FOR MATHEMATICS AND OR PHYSICS F AWM American Mathematical Society LOUISE HAY AWARD FOR CONTRIBUTIONS TO MATHEMATICS EDUCATION: PATRICIA CAMPBELL RUTH LYTTLE SATTER PRIZE IN MATHEMATICS M. GWENETH HUMPHREYS AWARD FOR MENTORSHIP OF UNDERGRADUATE WOMEN IN MATHEMATICS: American Mathematical Society RHONDA HUGHES ALICE T. S CHAFER PRIZE FOR EXCELLENCE IN MATHEMATICS BY AN UNDERGRADUATE WOMAN: LOUISE HAY AWARD FOR CONTRIBUTIONS TO MATHEMATICS EDUCATION SHERRY GONG Association for Women in Mathematics ALICE T. S CHAFER PRIZE FOR EXCELLENCE IN MATHEMATICS BY AN UNDERGRADUATE WOMAN FOR JPBM Association for Women in Mathematics COMMUNICATIONS AWARD: NICOLAS FALACCI AND CHERYL HEUTON M. -
Covering Group Theory for Compact Groups
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of Pure and Applied Algebra 161 (2001) 255–267 www.elsevier.com/locate/jpaa Covering group theory for compact groups Valera Berestovskiia, Conrad Plautb;∗ aDepartment of Mathematics, Omsk State University, Pr. Mira 55A, Omsk 77, 644077, Russia bDepartment of Mathematics, University of Tennessee, Knoxville, TN 37919, USA Received 27 May 1999; received in revised form 27 March 2000 Communicated by A. Carboni Abstract We present a covering group theory (with a generalized notion of cover) for the category of compact connected topological groups. Every such group G has a universal covering epimorphism 2 K : G → G in this category. The abelian topological group 1 (G):=ker is a new invariant for compact connected groups distinct from the traditional fundamental group. The paper also describes a more general categorial framework for covering group theory, and includes some examples and open problems. c 2001 Elsevier Science B.V. All rights reserved. MSC: Primary: 22C05; 22B05; secondary: 22KXX 1. Introduction and main results In [1] we developed a covering group theory and generalized notion of fundamental group that discards such traditional notions as local arcwise connectivity and local simple connectivity. The theory applies to a large category of “coverable” topological groups that includes, for example, all metrizable, connected, locally connected groups and even some totally disconnected groups. However, for locally compact groups, being coverable is equivalent to being arcwise connected [2]. Therefore, many connected compact groups (e.g. solenoids or the character group of ZN ) are not coverable.