Obituary Andrei Nikolaevich Kolmogorov
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[Math.PR] 9 Dec 2004
On local martingale and its supremum: harmonic functions and beyond. Dedicated to Professor A.N. Shiryaev for his 70th birthday Jan Ob l´oj1,2 and Marc Yor1 1 Laboratoire de Probabilit´es et Mod`eles Al´eatoires, Universit´eParis 6, 4 pl. Jussieu, Boˆite 188, 75252 Paris Cedex 05, France 2 Wydzia lMatematyki, Uniwersytet Warszawski Banacha 2, 02-097 Warszawa, Poland email: [email protected] Version du 8 D´ecembre 2004 We discuss certain facts involving a continuous local martingale N and its supre- mum N. A complete characterization of (N, N)-harmonic functions is proposed. This yields an important family of martingales, the usefulness of which is demonstrated, by means of examples involving the Skorokhod embedding problem, bounds on the law of the supremum, or the local time at 0, of a martingale with a fixed terminal distribution, or yet in some Brownian penalization problems. In particular we obtain new bounds on the law of the local time at 0, which involve the excess wealth order. Key words: continuous local martingale, supremum process, harmonic function, Skorokhod’s embedding problem, excess wealth order. Mathematics Subject Classification (2000): 60G44 (Primary), 60G42, 60G40, 60E15 arXiv:math/0412196v1 [math.PR] 9 Dec 2004 2 Jan Ob l´oj and Marc Yor Dedication. The first time I met Prof. A. Shiryaev was in January 1977, during a meeting dedicated to Control and Filtering theories, in Bonn. This was a time when meeting a Soviet mathematician was some event! Among the participants to that meeting, were, apart from A. Shiryaev, Prof. B. Grige- lionis, and M. -
Stochastics, Statistics, Financial Mathematics 13-15 October, 2014, Steklov Mathematical Institute, Moscow Conference Program
Stochastics, Statistics, Financial Mathematics 13-15 October, 2014, Steklov Mathematical Institute, Moscow Conference Program Monday, 13 October 9:30 { 10:00 Opening (Valeriy Kozlov, Yuri Kabanov) 10:00 { 10:40 Jean Jacod: Limit theorems for stochastic processes: some advances during the past ten years 10:45 { 11:25 Yuri Kabanov: Absolute continuity of measures, the Girsanov theorem, and Hellinger processes 11:30 { 11:45 Coffee break 11:45 { 12:25 Martin Schweizer: A new approach for stochastic Fubini theorems 12:30 { 13:10 Alexander Zvonkin: Gaussian measures on the space of matrcies and map enumeration 13:15 { 14:30 Lunch 14:30 { 15:10 Vladimir Spokoiny: From lambda-convergence to Fisher and Wilks expansions 15:15 { 15:55 Alexander Bulinski: Generalizations of the multifactor dimensionality reduction method 16:00 { 16:40 Jordan Stoyanov: Transformations of random variables and processes and their moment determinacy 16:45 { 17:00 Coffee break 17:00 { 17:40 Anna Obizhaeva: Market microstructure invariance 17:45 { 18:25 Pavel Katyshev: Transmission of information over channels with feedback and fil- tration theory Tuesday, 14 October 10:00 { 10:40 Hans-Juergen Engelbert: Stochastic differential equations for sticky reflecting Brow- nian motion 10:45 { 11:25 Hans F¨ollmer: Another look at It^o'sformula 11:30 { 11:45 Coffee break 11:45 { 12:25 Marek Musiela: TBA 12:30 { 13:10 Goran Peskir: Optimal mean-variance portfolio selection 13:15 { 14:30 Lunch 14:30 { 15:10 Alexander Novikov: First passage time problems: martingale approach revised 15:15 { 15:55 Mikhail Urusov: A generalized Donsker's theorem and approximating SDEs with irregular coefficients 16:00 { 16:40 Alexander Gushchin: On the inequalities connecting Hellinger processes and some statistical distances 16:45 { 17:00 Coffee break 17:00 { 17:30 Igor Pavlov: Interpolation properties of martingale measures and Haar interpola- tions of (B; S)-markets 17:35 { 18:05 Vadim Malyshev, A. -
On Asymptotic Diversification Effects for Heavy-Tailed Risks
On Asymptotic Diversification Effects for Heavy-Tailed Risks Dissertation zur Erlangung des Doktorgrades der Fakult¨atf¨urMathematik und Physik der Albert-Ludwigs-Universit¨atFreiburg im Breisgau vorgelegt von Georg Mainik Februar 2010 Dekan: Prof. Dr. Kay K¨onigsmann Referenten: Prof. Dr. Ludger R¨uschendorf Prof. Dr. Paul Embrechts Datum der Promotion: 29. April 2010 Contents 1 Introduction1 1.1 Motivation.............................1 1.2 Overview of related theory....................2 1.3 Central results and structure of the thesis...........3 1.4 Acknowledgements........................7 2 Multivariate regular variation9 2.1 Basic notation and model assumptions.............9 2.2 Canonical forms of exponent and spectral measures...... 14 2.3 Dependence functions....................... 18 2.4 Copulas.............................. 20 2.5 Spectral densities of Gumbel copulas.............. 24 2.6 Spectral densities of elliptical distributions........... 27 3 Extreme risk index 35 3.1 Basic approach.......................... 35 3.2 Representations in terms of spectral measures......... 39 3.3 Portfolio optimization and diversification effects........ 42 3.4 Minimization of risk measures.................. 49 4 Estimation 55 4.1 Basic approach.......................... 55 4.2 Main results............................ 59 4.3 Empirical processes with functional index............ 63 4.4 Proofs of the main results.................... 76 4.5 Examples and comments..................... 78 5 Stochastic order relations 87 5.1 Introduction............................ 87 5.2 Ordering of extreme portfolio losses............... 90 5.3 Ordering of spectral measures.................. 94 i ii CONTENTS 5.4 Convex and supermodular orders................ 106 5.5 Examples............................. 111 6 Modelling and simulation 117 6.1 Objectives and design....................... 117 6.2 Estimation of the tail index................... 118 6.3 Models............................... 121 6.4 Simulation results........................ -
A Table of Contents
A TABLE OF CONTENTS LECTURE 1 ....................................................................................................................................................................... 5 1.1. Random variables. Probability distribution law .................................................................................................. 5 1.2. Cumulative distribution function .......................................................................................................................... 6 1.3. Distribution set ..................................................................................................................................................... 7 1.4. Probability density function ................................................................................................................................. 8 LECTURE 2 ..................................................................................................................................................................... 10 2.1. Numerical characteristics of the random variable ............................................................................................. 10 LECTURE 3 ..................................................................................................................................................................... 15 3.1. Uniform distribution .......................................................................................................................................... 15 3.2. Exponential distribution -
Bibliography of Nonparametric Statistics and Related Topics
Section 12,3 ft" not r-ftmiwtt NATIONAL BUREAU OF STANDARDS REPORT 1828 BIBLIOGRAPHY OF NONPARAMETRIC STATISTICS AND RELATED TOPICS by I* Richard Savage <NB§> U. S. DEPARTMENT OF COMMERCE NATIONAL BUREAU OF STANDARDS U. S. DEPARTMENT OF COMMERCE Charles Sawyer, Secretary NATIONAL BUREAU OF STANDARDS A . Y„ Astin, Acting Director THE NATIONAL BUREAU OF STANDARDS The scope of activities of the National Bureau of Standards is suggested in the following listing of the divisions and sections engaged in technical work. In general, each section is engaged in specialized research, development, and engineering in the field indicated by its title. A brief description of the activities, and of the resultant reports and publications, appears on the inside of the back cover of this report. 1. Electricity, Resistance Measurements. Inductance and Capacitance. Electrical Instruments. Magnetic Measurements. Electrochemistry. 2. Optics and Metrology. Photometry and Colorimetry. Optical Instruments. Photo- graphic Technology. Length. Gage. 3. Heat and Power. Temperature Measurements. Thermodynamics. Cryogenics. En- gines and Lubrication. Engine Fuels. 4. Atomic and Radiation Physics. Spectroscopy. Radiometry. Mass Spectrometry. Physical Electronics. Electron Physics. Atomic Physics. Neutron Measurements. Nuclear Physics. Radioactivity. X-Rays. Betatron. Nucleonic Instrumentation. Radiological Equipment. Atomic Energy Commission Instruments Branch. 5. Chemistry. Organic Coatings. Surface Chemistry. Organic Chemistry. Analytical Chemistry. Inorganic Chemistry. Electrodeposition. Gas Chemistry. Physical Chem- istry. Thermochemistry. Spectrochemistry. Pure Substances. 6. Mechanics. Sound. Mechanical Instruments. Aerodynamics. Engineering Me- chanics. Hydraulics. Mass. Capacity, Density, and Fluid Meters. 7. Organic and Fibrous Materials. Rubber. Textiles. Paper. Leather. Testing and Specifications. Organic Plastics. Dental Research. 8. Metallurgy. Thermal Metallurgy. Chemical Metallurgy. Mechanical Metallurgy. Corrosion. 9. -
A First Course in Order Statistics
A First Course in Order Statistics Books in the Classics in Applied Mathematics series are monographs and textbooks declared out of print by their original publishers, though they are of continued importance and interest to the mathematical community. SIAM publishes this series to ensure that the information presented in these texts is not lost to today’s students and researchers. Editor-in-Chief Robert E. O’Malley, Jr., University of Washington Editorial Board John Boyd, University of Michigan Leah Edelstein-Keshet, University of British Columbia William G. Faris, University of Arizona Nicholas J. Higham, University of Manchester Peter Hoff, University of Washington Mark Kot, University of Washington Hilary Ockendon, University of Oxford Peter Olver, University of Minnesota Philip Protter, Cornell University Gerhard Wanner, L’Université de Genève Classics in Applied Mathematics C. C. Lin and L. A. Segel, Mathematics Applied to Deterministic Problems in the Natural Sciences Johan G. F. Belinfante and Bernard Kolman, A Survey of Lie Groups and Lie Algebras with Applications and Computational Methods James M. Ortega, Numerical Analysis: A Second Course Anthony V. Fiacco and Garth P. McCormick, Nonlinear Programming: Sequential Unconstrained Minimization Techniques F. H. Clarke, Optimization and Nonsmooth Analysis George F. Carrier and Carl E. Pearson, Ordinary Differential Equations Leo Breiman, Probability R. Bellman and G. M. Wing, An Introduction to Invariant Imbedding Abraham Berman and Robert J. Plemmons, Nonnegative Matrices in the Mathematical Sciences Olvi L. Mangasarian, Nonlinear Programming *Carl Friedrich Gauss, Theory of the Combination of Observations Least Subject to Errors: Part One, Part Two, Supplement. Translated by G. W. Stewart Richard Bellman, Introduction to Matrix Analysis U. -
Curriculum Vitae
CURRICULUM VITAE ALEXANDER G. TARTAKOVSKY Department of Mathematics and Center for Applied Mathematical Sciences University of Southern California 3620 S. Vermont Avenue, KAP 108 Los Angeles, CA 90089-2532 Phone (213) 740-2450 Fax (213) 740-2424 Email: [email protected] DEGREES Ph.D. in Statistics and Information Theory. Department of Electrical Engineering and Cybernetics, Moscow Institute of Physics and Technology, Russia, 1981. M.S. in Electrical Engineering with specialization in Radar Systems, Detection Theory, and Telecommunications. Department of Electrical Engineering and Flight Systems, Moscow Aviation Institute, Russia, 1978. PROFESSIONAL EXPERIENCE 2002{present Professor (Adjunct) and Senior Research Scientist, Department of Mathematics, University of Southern California. 1997{present Associate Director, Project Director, Center for Applied Mathematical Sciences, University of Southern California. 2006{present Vice President, Argo Science Corp, Palos Verdes, CA. 1996{1997 Senior Manager and Principal Investigator, Filimage, Inc., Los Angeles, CA. 1994{1995 Visiting Research Professor, Department of Mathematics, Statistics Division, University of California, Los Angeles. June{August 1994 Visiting Faculty at the University of North Carolina, Chapel Hill, Department of Statistics, and at the University of Southern California, Center for Applied Mathematical Sciences. 1993{1994 Visiting Research Professor, Department of Electrical Engineering, Flight Systems Research Center, University of California, Los Angeles. 1991{1993 -
Variance Risk Premium Dynamics: the Role of Jumps∗
Variance Risk Premium Dynamics: The Role of Jumps¤ Viktor Todorovy February 6, 2009 Abstract Using high-frequency stock market data and (synthetic) variance swap rates, this paper identi¯es and investigates the temporal variation in the market vari- ance risk premium. The variance risk is manifest in two salient features of ¯nancial returns: stochastic volatility and jumps. The pricing of these two separate components is analyzed in a general semiparametric framework. The key empirical results imply that investors fears of future jumps are especially sensitive to recent jump activity and that their willingness to pay for protection against jumps increase signi¯cantly immediately after the occurrence of jumps. This in turn suggests that time-varying risk aversion, as previously documented in the literature, is primarily driven by large, or extreme, market moves. The dynamics of risk-neutral jump intensity extracted from deep out-of-the money put options con¯rms these ¯ndings. (JEL C51, C52, G12, G13) Keywords: Continuous-time stochastic volatility models, jump processes, method- of-moments estimation, realized multipower variation. JEL classi¯cation: C51, C52, G12, G13. ¤This paper is part of my PhD dissertation at the Department of Economics, Duke University. I would like to thank my advisors George Tauchen, Tim Bollerslev, Ron Gallant and Han Hong for many discussions and encouragement along the way. I would like also to thank the editor (Joel Hasbrouck) and anonymous referees for many helpful suggestions. I bene¯ted also from comments, -
Optimal Sequential Decisions in Hidden-State Models
UPPSALA DISSERTATIONS IN MATHEMATICS 101 Optimal Sequential Decisions in Hidden-State Models Juozas Vaicenavicius Department of Mathematics Uppsala University UPPSALA 2017 Dissertation presented at Uppsala University to be publicly examined in 80101, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, Friday, 9 June 2017 at 13:00 for the degree of Doctor of Philosophy. The examination will be conducted in English. Faculty examiner: Professor Huyên Pham (Université Paris Diderot (Paris 7)). Abstract Vaicenavicius, J. 2017. Optimal Sequential Decisions in Hidden-State Models. Uppsala Dissertations in Mathematics 101. 26 pp. Uppsala: Department of Mathematics, Uppsala University. ISBN 978-91-506-2641-4. This doctoral thesis consists of five research articles on the general topic of optimal decision making under uncertainty in a Bayesian framework. The papers are preceded by three introductory chapters. Papers I and II are dedicated to the problem of finding an optimal stopping strategy to liquidate an asset with unknown drift. In Paper I, the price is modelled by the classical Black-Scholes model with unknown drift. The first passage time of the posterior mean below a monotone boundary is shown to be optimal. The boundary is characterised as the unique solution to a nonlinear integral equation. Paper II solves the same optimal liquidation problem, but in a more general model with stochastic regime-switching volatility. An optimal liquidation strategy and various structural properties of the problem are determined. In Paper III, the problem of sequentially testing the sign of the drift of an arithmetic Brownian motion with the 0-1 loss function and a constant cost of observation per unit of time is studied from a Bayesian perspective. -
An Inverse Optimal Stopping Problem for Diffusion Processes August 8, 2017
AN INVERSE OPTIMAL STOPPING PROBLEM FOR DIFFUSION PROCESSES August 8, 2017 THOMAS KRUSE AND PHILIPP STRACK Abstract. Let X be a one-dimensional diffusion and let g : [0,T ] R R be a payoff × → function depending on time and the value of X. The paper analyzes the inverse optimal stopping problem of finding a time-dependent function π : [0,T ] R such that a given ⋆ → stopping time τ is a solution of the stopping problem supτ E [g(τ,Xτ )+ π(τ)] . Under regularity and monotonicity conditions, there exists a solution π if and only if τ ⋆ is ⋆ the first time when X exceeds a time-dependent barrier b, i.e. τ = inf t 0 Xt b(t) . { ≥ | ≥ } We prove uniqueness of the solution π and derive a closed form representation. The rep- resentation is based on an auxiliary process which is a version of the original diffusion X reflected at b towards the continuation region. The results lead to a new integral equation characterizing the stopping boundary b of the stopping problem supτ E [g(τ,Xτ )]. Keywords: Optimal Stopping, Reflected Stochastic Processes, Dynamic Mechanism De- sign, Dynamic Implementability, MSC 2010: 91B02, 91A60, 60G40, 62L15 Introduction Optimal stopping is omnipresent in applications of dynamic optimization in economics, statistics, and finance. Examples are the optimal exercise timing of options, when to stop searching, and the quickest detection problem. One method to solve optimal stopping prob- lems in a Markovian framework is to identify the stopping region. Optimal stopping times arXiv:1406.0209v3 [math.OC] 7 Aug 2017 are then given as first hitting times of the stopping region. -
Limit Theorems for Power Variations of Pure-Jump Processes with Application to Activity Estimation∗
Limit Theorems for Power Variations of Pure-Jump Processes with Application to Activity Estimation¤ Viktor Todorov y and George Tauchen z March 18, 2010 Abstract This paper derives the asymptotic behavior of realized power variation of pure-jump It^o semimartingales as the sampling frequency within a ¯xed interval increases to in¯nity. We prove convergence in probability and an associated central limit theorem for the realized power variation as a function of its power. We apply the limit theorems to propose an e±cient adaptive estimator for the activity of discretely-sampled It^osemimartingale over a ¯xed interval. Keywords: Activity index, Blumenthal-Getoor index, Central Limit Theorem, It^osemimartin- gale, high-frequency data, jumps, realized power variation. 1 Introduction Realized power variation of a discretely sampled process can be de¯ned as the sum of the absolute values of the increments of the process raised to a given power. The leading case is when the power is 2, which corresponds to the realized variance that is widely used in ¯nance. It is well known that under very weak conditions, see e.g. Jacod and Shiryaev (2003), the realized variance converges to the quadratic variation of the process as the sampling frequency increases. Other powers than 2 have also been used as a way to measure variation of the process over a given interval in time as well as for estimation in parametric or semiparametric settings. Recently, Ait-Sahalia and Jacod (2009b) have used the realized power variation as a way to test for presence of jumps on a given path and Jacod and Todorov (2009) have used it to test for common arrival of jumps in a multivariate context. -
2007 Annual Report
Princeton University Bendheim Center for Finance Annual Report 2007 26 Prospect Avenue Princeton, NJ 08540-5296 http://www.princeton.edu/~bcf Contents CONTENTS 2 DIRECTOR’S INTRODUCTION 3 FACULTY 8 VISITING FACULTY 35 VISITING FELLOWS 39 GRADUATING PH.D. STUDENTS 40 FINANCE SEMINARS 41 CIVITAS FOUNDATION FINANCE SEMINAR FALL 2006 41 CIVITAS FOUNDATION FINANCE SEMINAR SPRING 2007 42 FINANCE PH.D. STUDENT WORKSHOP 43 CONFERENCES 45 THE PRINCETON LECTURES IN FINANCE 45 SECOND CAMBRIDGE-PRINCETON CONFERENCE 46 CONFERENCE ON RISK MEASURES AND ROBUST CONTROL IN FINANCE 48 RETHINKING BUSINESS MANAGEMENT: AN EXAMINATION OF THE FOUNDATIONS OF BUSINESS EDUCATION 48 UNDERGRADUATE CERTIFICATE IN FINANCE 50 DEPARTMENTAL PRIZES, HONORS AND ATHLETIC AWARDS TO UCF ’07 STUDENTS 51 SENIOR THESES OF THE CLASS OF ’07 53 MINI-COURSE ON FINANCIAL MODELING, VALUATION AND ANALYSIS 58 USING EXCEL, VBA AND C++ 58 MASTER IN FINANCE 59 ADMISSION REQUIREMENTS 60 STATISTICS ON THE ADMISSION PROCESS 60 PROGRAM REQUIREMENTS 61 CORE COURSES 62 ELECTIVE COURSES 62 TRACKS 64 SOME COURSE DESCRIPTIONS 65 MASTER IN FINANCE PLACEMENT 69 MFIN MATH CAMP/BOOT CAMP 70 ADVISORY COUNCIL 73 CORPORATE AFFILIATES PROGRAM 75 2006-07 PARTNERS 75 BENEFITS 75 GIFT OPPORTUNITIES 77 ACKNOWLEDGEMENTS 2006-07 78 Director’s Introduction The mission of Princeton University’s Bendheim Center for Finance is twofold: First, to develop new courses and programs in finance that will afford exciting learning opportunities to Princeton students; and second, to establish a leading center for modern financial research. Under the aegis of the BCF, Princeton’s existing finance curriculum is being expanded and improved, and two new academic programs have been created: an Undergraduate Certificate in Finance in 1999 and a Master Program in Finance in 2001.