Disclosure Risk Measurement with Entropy in Sample Based Frequency Tables
|
|
|
- Morgan Lucas
- 5 years ago
- Views:
Transcription
1 Disclosure Risk Measurement with Entropy in Sample Based Frequency Tables L. Antal N. Shlomo M. Elliot University of Manchester New Techniques and Technologies for Statistics 10 March 2015 L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
2 Outline 1 Idea and Notation 2 Disclosure Risk Measures 3 Results L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
3 Outline Idea and Notation 1 Idea and Notation 2 Disclosure Risk Measures 3 Results L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
4 Idea and Notation Idea and Notation We would like to measure the disclosure risk of a population based frequency table Information theoretical expressions (e.g. entropy) can reflect the properties of attribute disclosure Notation Population based frequency table: F = (F 1, F 2,..., F K ) Population size: N = K i=1 F i Sample based frequency table: f = (f 1, f 2,..., f K ) Sample size: n = K i=1 f i L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
5 Outline Disclosure Risk Measures 1 Idea and Notation 2 Disclosure Risk Measures 3 Results L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
6 Disclosure Risk Measures Properties of a desired disclosure risk measure Properties: If only one cell is populated in the table, then the disclosure risk should be high. Uniformly distributed frequencies imply low risk. The smaller the cells, the higher the disclosure risk. The more number of zeroes, the higher the disclosure risk. The disclosure risk bounded by 0 and 1. L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
7 Disclosure Risk Measures The Disclosure Risk Measure We developed the disclosure risk measure for population based frequency tables first Now we extend it for sample based frequency tables The disclosure risk measure for population based frequency tables: R 1 (F, w) = w 1 D ( K + w 2 1 H(X) ) w 3 log K 1 N log 1 e N where D is the set of zeroes in F and w = (w 1, w 2, w 3 ) is a vector of weights L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
8 Disclosure Risk Measures Disclosure Risk Measure for Sample Based Tables The disclosure risk of a sample based table should be lower than that of the original population based table R 2 (F, f, w) = w 1 ( w 2 1 H(X) log K ( ) D E D D E + K ) H(X Y ) w 3 H(X) 1 N log 1 e N where E is the set of zeroes in the sample based table and H(X Y ) is the conditional entropy of the original table with respect to the sample based table. L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
9 Outline Results 1 Idea and Notation 2 Disclosure Risk Measures 3 Results L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
10 Results Results Data: 2001 UK census tables 10 selected output areas N = 2449 Weights: w = (0.1, 0.8, 0.1) Initial population based table: output area (10 output areas) religion 1,000 sample based tables, 1,000 estimated population based frequency tables for each sample based table L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
11 Results Results Estimation of population based frequency tables: Drawing samples from a population based table Applying a log-linear model to the sample based tables to estimate population parameters Drawing N n individuals from a multinomial distribution Adding the individuals to the sample based table L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
12 Results Results R 1 (F, w) R 2 (F, f, w) From true population frequencies From estimated population frequencies From true population frequencies From estimated population frequencies Sampling fraction Table: Table: output area (10 output areas) religion. 1,000 samples, 1,000 estimated population based table for each sample. L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
13 Summary Summary A disclosure risk measure has been extended to sample based tables. The disclosure risk measure is based on information theory. Initial results show good estimates for a two-dimensional table. The model needs to be explored for higher dimensional tables. L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
14 Thank you for your attention! L. Antal, N. Shlomo, M. Elliot Disclosure Risk Measurement NTTS / 14
ELEMENTS OF MONTE CARLO SIMULATION
APPENDIX B ELEMENTS OF MONTE CARLO SIMULATION B. GENERAL CONCEPT The basic idea of Monte Carlo simulation is to create a series of experimental samples using a random number sequence. According to the
Optimal Control of Batch Service Queues with Finite Service Capacity and General Holding Costs
Queueing Colloquium, CWI, Amsterdam, February 24, 1999 Optimal Control of Batch Service Queues with Finite Service Capacity and General Holding Costs Samuli Aalto EURANDOM Eindhoven 24-2-99 cwi.ppt 1 Background
Math 1090 Final Exam Fall 2012
Math 1090 Final Exam Fall 2012 Name Instructor: Student ID Number: Instructions: Show all work, as partial credit will be given where appropriate. If no work is shown, there may be no credit given. All
Large-Scale SVM Optimization: Taking a Machine Learning Perspective
Large-Scale SVM Optimization: Taking a Machine Learning Perspective Shai Shalev-Shwartz Toyota Technological Institute at Chicago Joint work with Nati Srebro Talk at NEC Labs, Princeton, August, 2008 Shai
A First Course in Probability
A First Course in Probability Seventh Edition Sheldon Ross University of Southern California PEARSON Prentice Hall Upper Saddle River, New Jersey 07458 Preface 1 Combinatorial Analysis 1 1.1 Introduction
Strategies for Improving the Efficiency of Monte-Carlo Methods
Strategies for Improving the Efficiency of Monte-Carlo Methods Paul J. Atzberger General comments or corrections should be sent to: paulatz@cims.nyu.edu Introduction The Monte-Carlo method is a useful
Lecture 5. 1 Online Learning. 1.1 Learning Setup (Perspective of Universe) CSCI699: Topics in Learning & Game Theory
CSCI699: Topics in Learning & Game Theory Lecturer: Shaddin Dughmi Lecture 5 Scribes: Umang Gupta & Anastasia Voloshinov In this lecture, we will give a brief introduction to online learning and then go
Maximum Likelihood Estimation
Maximum Likelihood Estimation The likelihood and log-likelihood functions are the basis for deriving estimators for parameters, given data. While the shapes of these two functions are different, they have
Factor endowments and trade I
Part A: Part B: Part C: Two trading economies The Vienna Institute for International Economic Studies - wiiw April 29, 2015 Basic assumptions 1 2 factors which are used in both sectors 1 Fully mobile across
Contract Theory in Continuous- Time Models
Jaksa Cvitanic Jianfeng Zhang Contract Theory in Continuous- Time Models fyj Springer Table of Contents Part I Introduction 1 Principal-Agent Problem 3 1.1 Problem Formulation 3 1.2 Further Reading 6 References
How To Prevent Another Financial Crisis On Wall Street
How To Prevent Another Financial Crisis On Wall Street Helin Gao helingao@stanford.edu Qianying Lin qlin1@stanford.edu Kaidi Yan kaidi@stanford.edu Abstract Riskiness of a particular loan can be estimated
Probability Distributions: Discrete
Probability Distributions: Discrete Introduction to Data Science Algorithms Jordan Boyd-Graber and Michael Paul SEPTEMBER 27, 2016 Introduction to Data Science Algorithms Boyd-Graber and Paul Probability
Chapter 2 Uncertainty Analysis and Sampling Techniques
Chapter 2 Uncertainty Analysis and Sampling Techniques The probabilistic or stochastic modeling (Fig. 2.) iterative loop in the stochastic optimization procedure (Fig..4 in Chap. ) involves:. Specifying
Asset Pricing in Production Economies
Urban J. Jermann 1998 Presented By: Farhang Farazmand October 16, 2007 Motivation Can we try to explain the asset pricing puzzles and the macroeconomic business cycles, in one framework. Motivation: Equity
Strategies and Nash Equilibrium. A Whirlwind Tour of Game Theory
Strategies and Nash Equilibrium A Whirlwind Tour of Game Theory (Mostly from Fudenberg & Tirole) Players choose actions, receive rewards based on their own actions and those of the other players. Example,
Keywords Akiake Information criterion, Automobile, Bonus-Malus, Exponential family, Linear regression, Residuals, Scaled deviance. I.
Application of the Generalized Linear Models in Actuarial Framework BY MURWAN H. M. A. SIDDIG School of Mathematics, Faculty of Engineering Physical Science, The University of Manchester, Oxford Road,
An Introduction to Dynamic Macroeconomic Models. Part One: Basic Models And Solution Methods
The ABCs of RBCs An Introduction to Dynamic Macroeconomic Models George McCandless Preface Introduction Part One: Basic Models And Solution Methods 1. The Basic Solow Model The Basic Model Technological
An introduction to Machine learning methods and forecasting of time series in financial markets
An introduction to Machine learning methods and forecasting of time series in financial markets Mark Wong markwong@kth.se December 10, 2016 Abstract The goal of this paper is to give the reader an introduction
Econ 3790: Business and Economics Statistics. Instructor: Yogesh Uppal
Econ 3790: Business and Economics Statistics Instructor: Yogesh Uppal Email: yuppal@ysu.edu Chapter 12 Goodness of Fit Test: A Multinomial Population Test of Independence Hypothesis (Goodness of Fit) Test
Chapter 6. Transformation of Variables
6.1 Chapter 6. Transformation of Variables 1. Need for transformation 2. Power transformations: Transformation to achieve linearity Transformation to stabilize variance Logarithmic transformation MACT
Computer Vision Group Prof. Daniel Cremers. 7. Sequential Data
Group Prof. Daniel Cremers 7. Sequential Data Bayes Filter (Rep.) We can describe the overall process using a Dynamic Bayes Network: This incorporates the following Markov assumptions: (measurement) (state)!2
Amath 546/Econ 589 Introduction to Credit Risk Models
Amath 546/Econ 589 Introduction to Credit Risk Models Eric Zivot May 31, 2012. Reading QRM chapter 8, sections 1-4. How Credit Risk is Different from Market Risk Market risk can typically be measured directly
Hedonic Regressions: A Review of Some Unresolved Issues
Hedonic Regressions: A Review of Some Unresolved Issues Erwin Diewert University of British Columbia, Vancouver, Canada The author is indebted to Ernst Berndt and Alice Nakamura for helpful comments. 1.
Chapter 15: Jump Processes and Incomplete Markets. 1 Jumps as One Explanation of Incomplete Markets
Chapter 5: Jump Processes and Incomplete Markets Jumps as One Explanation of Incomplete Markets It is easy to argue that Brownian motion paths cannot model actual stock price movements properly in reality,
Transportation Theory and Applications
Fall 2017 - MTAT.08.043 Transportation Theory and Applications Lecture III: Trip Generation Modelling A. Hadachi Definitions Trip or Journey: is a one-way movement from origin to destination. Home-based
Prentice Hall Connected Mathematics, Grade 7 Unit 2004 Correlated to: Maine Learning Results for Mathematics (Grades 5-8)
: Maine Learning Results for Mathematics (Grades 5-8) A. NUMBERS AND NUMBER SENSE Students will understand and demonstrate a sense of what numbers mean and how they are used. Students will be able to:
ECON 200 EXERCISES. (b) Appeal to any propositions you wish to confirm that the production set is convex.
ECON 00 EXERCISES 3. ROBINSON CRUSOE ECONOMY 3.1 Production set and profit maximization. A firm has a production set Y { y 18 y y 0, y 0, y 0}. 1 1 (a) What is the production function of the firm? HINT:
Economic factors and solvency
Economic factors and solvency Harri Nyrhinen, University of Helsinki ASTIN Colloquium Helsinki 2009 Insurance solvency One of the main concerns in actuarial practice and theory. The companies should have
An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity
An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity Coralia Cartis, Nick Gould and Philippe Toint Department of Mathematics,
Inflation and Unemployment
Inflation and Unemployment Prof. Lutz Hendricks Econ520 March 21, 2017 1 / 35 Objectives In this section you will learn: 1. how and when lax monetary policy reduces unemployment 2. how to derive and interpret
Chapter 9. Idea of Probability. Randomness and Probability. Basic Practice of Statistics - 3rd Edition. Chapter 9 1. Introducing Probability
Chapter 9 Introducing Probability BPS - 3rd Ed. Chapter 9 1 Idea of Probability Probability is the science of chance behavior Chance behavior is unpredictable in the short run but has a regular and predictable
Single Price Mechanisms for Revenue Maximization in Unlimited Supply Combinatorial Auctions
Single Price Mechanisms for Revenue Maximization in Unlimited Supply Combinatorial Auctions Maria-Florina Balcan Avrim Blum Yishay Mansour February 2007 CMU-CS-07-111 School of Computer Science Carnegie
Some aspects of using calibration in polish surveys
Some aspects of using calibration in polish surveys Marcin Szymkowiak Statistical Office in Poznań University of Economics in Poznań in NCPH 2011 in business statistics simulation study Outline Outline
Log-linear Modeling Under Generalized Inverse Sampling Scheme
Log-linear Modeling Under Generalized Inverse Sampling Scheme Soumi Lahiri (1) and Sunil Dhar (2) (1) Department of Mathematical Sciences New Jersey Institute of Technology University Heights, Newark,
CSCI 1951-G Optimization Methods in Finance Part 00: Course Logistics Introduction to Finance Optimization Problems
CSCI 1951-G Optimization Methods in Finance Part 00: Course Logistics Introduction to Finance Optimization Problems January 26, 2018 1 / 24 Basic information All information is available in the syllabus
Numerical schemes for SDEs
Lecture 5 Numerical schemes for SDEs Lecture Notes by Jan Palczewski Computational Finance p. 1 A Stochastic Differential Equation (SDE) is an object of the following type dx t = a(t,x t )dt + b(t,x t
Economic Growth: Malthus and Solow Copyright 2014 Pearson Education, Inc.
Chapter 7 Economic Growth: Malthus and Solow Copyright Chapter 7 Topics Economic growth facts Malthusian model of economic growth Solow growth model Growth accounting 1-2 U.S. Per Capita Real Income Growth
Chapter 7: Estimation Sections
1 / 40 Chapter 7: Estimation Sections 7.1 Statistical Inference Bayesian Methods: Chapter 7 7.2 Prior and Posterior Distributions 7.3 Conjugate Prior Distributions 7.4 Bayes Estimators Frequentist Methods:
Single Price Mechanisms for Revenue Maximization in Unlimited Supply Combinatorial Auctions
Single Price Mechanisms for Revenue Maximization in Unlimited Supply Combinatorial Auctions Maria-Florina Balcan Avrim Blum Yishay Mansour December 7, 2006 Abstract In this note we generalize a result
Applied Stochastic Processes and Control for Jump-Diffusions
Applied Stochastic Processes and Control for Jump-Diffusions Modeling, Analysis, and Computation Floyd B. Hanson University of Illinois at Chicago Chicago, Illinois siam.. Society for Industrial and Applied
Revenue Management Under the Markov Chain Choice Model
Revenue Management Under the Markov Chain Choice Model Jacob B. Feldman School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853, USA jbf232@cornell.edu Huseyin
Lecture 17: More on Markov Decision Processes. Reinforcement learning
Lecture 17: More on Markov Decision Processes. Reinforcement learning Learning a model: maximum likelihood Learning a value function directly Monte Carlo Temporal-difference (TD) learning COMP-424, Lecture
Rewriting Codes for Flash Memories Based Upon Lattices, and an Example Using the E8 Lattice
Rewriting Codes for Flash Memories Based Upon Lattices, and an Example Using the E Lattice Brian M. Kurkoski kurkoski@ice.uec.ac.jp University of Electro-Communications Tokyo, Japan Workshop on Application
ON SOME ASPECTS OF PORTFOLIO MANAGEMENT. Mengrong Kang A THESIS
ON SOME ASPECTS OF PORTFOLIO MANAGEMENT By Mengrong Kang A THESIS Submitted to Michigan State University in partial fulfillment of the requirement for the degree of Statistics-Master of Science 2013 ABSTRACT
Generating Power Laws
Summary of Unit Six Generating Power Laws Introduction to Fractals and Scaling David P. Feldman http://www.complexityexplorer.org Rich-get-Richer Models Procedure for growing a network. At each step, make
Premia 14 HESTON MODEL CALIBRATION USING VARIANCE SWAPS PRICES
Premia 14 HESTON MODEL CALIBRATION USING VARIANCE SWAPS PRICES VADIM ZHERDER Premia Team INRIA E-mail: vzherder@mailru 1 Heston model Let the asset price process S t follows the Heston stochastic volatility
Macroeconometric Modeling: 2018
Macroeconometric Modeling: 2018 Contents Ray C. Fair 2018 1 Macroeconomic Methodology 4 1.1 The Cowles Commission Approach................. 4 1.2 Macroeconomic Methodology.................... 5 1.3 The
Course information FN3142 Quantitative finance
Course information 015 16 FN314 Quantitative finance This course is aimed at students interested in obtaining a thorough grounding in market finance and related empirical methods. Prerequisite If taken
Universal Portfolios
CS28B/Stat24B (Spring 2008) Statistical Learning Theory Lecture: 27 Universal Portfolios Lecturer: Peter Bartlett Scribes: Boriska Toth and Oriol Vinyals Portfolio optimization setting Suppose we have
Models of Multinomial Qualitative Response
Models of Multinomial Qualitative Response Multinomial Logit Models October 22, 2015 Dependent Variable as a Multinomial Outcome Suppose we observe an economic choice that is a binary signal from amongst
Outline. 1. Capture/recapture models 2. Inter-rater agreement, Kappa
Outline 1. Capture/recapture models 2. Inter-rater agreement, Kappa Capture/recapture Consider estimating the size of a population where a complete census is impossible Example: estimating the number of
Back- and Side Testing of Price Simulation Models
Back- and Side Testing of Price Simulation Models Universität Duisburg Essen - Seminarreihe Energy & Finance 23. Juni 2010 Henrik Specht, Vattenfall Europe AG The starting point Question: How do I know
Paul Ormerod Volterra Partners LLP, London and Centre for the Study of Decision-Making Uncertainty, UCL
Paul Ormerod Volterra Partners LLP, London and Centre for the Study of Decision-Making Uncertainty, UCL 4 5 The rational autonomous agent The fundamental tool of neoclassical economics is an objective
9.1 Principal Component Analysis for Portfolios
Chapter 9 Alpha Trading By the name of the strategies, an alpha trading strategy is to select and trade portfolios so the alpha is maximized. Two important mathematical objects are factor analysis and
1 The Solow Growth Model
1 The Solow Growth Model The Solow growth model is constructed around 3 building blocks: 1. The aggregate production function: = ( ()) which it is assumed to satisfy a series of technical conditions: (a)
Probability Distributions: Discrete
Probability Distributions: Discrete INFO-2301: Quantitative Reasoning 2 Michael Paul and Jordan Boyd-Graber FEBRUARY 19, 2017 INFO-2301: Quantitative Reasoning 2 Paul and Boyd-Graber Probability Distributions:
Approximate methods for dynamic portfolio allocation under transaction costs
Western University Scholarship@Western Electronic Thesis and Dissertation Repository November 2012 Approximate methods for dynamic portfolio allocation under transaction costs Nabeel Butt The University
Constructing Markov models for barrier options
Constructing Markov models for barrier options Gerard Brunick joint work with Steven Shreve Department of Mathematics University of Texas at Austin Nov. 14 th, 2009 3 rd Western Conference on Mathematical
Financial Analysis The Price of Risk. Skema Business School. Portfolio Management 1.
Financial Analysis The Price of Risk bertrand.groslambert@skema.edu Skema Business School Portfolio Management Course Outline Introduction (lecture ) Presentation of portfolio management Chap.2,3,5 Introduction
High Frequency Trading Strategy Based on Prex Trees
High Frequency Trading Strategy Based on Prex Trees Yijia Zhou, 05592862, Financial Mathematics, Stanford University December 11, 2010 1 Introduction 1.1 Goal I am an M.S. Finanical Mathematics student
Modified ratio estimators of population mean using linear combination of co-efficient of skewness and quartile deviation
CSIRO PUBLISHING The South Pacific Journal of Natural and Applied Sciences, 31, 39-44, 2013 www.publish.csiro.au/journals/spjnas 10.1071/SP13003 Modified ratio estimators of population mean using linear
ECON 450 Development Economics
ECON 450 Development Economics Classic Theories of Economic Growth and Development The Empirics of the Solow Growth Model University of Illinois at Urbana-Champaign Summer 2017 Introduction This lecture
An Approximation Algorithm for Capacity Allocation over a Single Flight Leg with Fare-Locking
An Approximation Algorithm for Capacity Allocation over a Single Flight Leg with Fare-Locking Mika Sumida School of Operations Research and Information Engineering, Cornell University, Ithaca, New York
Taxes and the Global Allocation of Capital
Taxes and the Global Allocation of Capital David Backus, Espen Henriksen, and Kjetil Storesletten Carnegie-Rochester April 20, 2007 This version: April 19, 2007 Backus, Henriksen, and Storesletten () Capital
The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay. Solutions to Final Exam
The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay Solutions to Final Exam Problem A: (40 points) Answer briefly the following questions. 1. Consider
Bonus-malus systems 6.1 INTRODUCTION
6 Bonus-malus systems 6.1 INTRODUCTION This chapter deals with the theory behind bonus-malus methods for automobile insurance. This is an important branch of non-life insurance, in many countries even
Policy modeling: Definition, classification and evaluation
Available online at www.sciencedirect.com Journal of Policy Modeling 33 (2011) 523 536 Policy modeling: Definition, classification and evaluation Mario Arturo Ruiz Estrada Faculty of Economics and Administration
Financial Mathematics III Theory summary
Financial Mathematics III Theory summary Table of Contents Lecture 1... 7 1. State the objective of modern portfolio theory... 7 2. Define the return of an asset... 7 3. How is expected return defined?...
Department of Economics The Ohio State University Final Exam Answers Econ 8712
Department of Economics The Ohio State University Final Exam Answers Econ 8712 Prof. Peck Fall 2015 1. (5 points) The following economy has two consumers, two firms, and two goods. Good 2 is leisure/labor.
Predicting the Success of a Retirement Plan Based on Early Performance of Investments
Predicting the Success of a Retirement Plan Based on Early Performance of Investments CS229 Autumn 2010 Final Project Darrell Cain, AJ Minich Abstract Using historical data on the stock market, it is possible
Vladimirs Jansons, Vitalijs Jurenoks, Konstantins Didenko (Riga) MODELLING OF SOCIAL-ECONOMIC SYSTEMS USING OF MULTIDIMENSIONAL STATISTICAL METHODS
Vladimirs Jansons, Vitalijs Jurenoks, Konstantins Didenko (Riga) MODELLING OF SOCIAL-ECONOMIC SYSTEMS USING OF MULTIDIMENSIONAL STATISTICAL METHODS Introduction. The basic idea of simulation modelling
Monetary Policy Shock Analysis Using Structural Vector Autoregression
Monetary Policy Shock Analysis Using Structural Vector Autoregression (Digital Signal Processing Project Report) Rushil Agarwal (72018) Ishaan Arora (72350) Abstract A wide variety of theoretical and empirical
Calculation of Risk Adjusted Loss Reserves based on Cost of Capital
Calculation of Risk Adjusted Loss Reserves based on Cost of Capital Vincent Lous Posthuma Partners, The Hague Astin, Mexico City - October, 2012 Outline Introduction Outline Introduction Risk Adjusted
Decision theoretic estimation of the ratio of variances in a bivariate normal distribution 1
Decision theoretic estimation of the ratio of variances in a bivariate normal distribution 1 George Iliopoulos Department of Mathematics University of Patras 26500 Rio, Patras, Greece Abstract In this
Macroeconomic Cycle and Economic Policy
Macroeconomic Cycle and Economic Policy Lecture 1 Nicola Viegi University of Pretoria 2016 Introduction Macroeconomics as the study of uctuations in economic aggregate Questions: What do economic uctuations
A New Hybrid Estimation Method for the Generalized Pareto Distribution
A New Hybrid Estimation Method for the Generalized Pareto Distribution Chunlin Wang Department of Mathematics and Statistics University of Calgary May 18, 2011 A New Hybrid Estimation Method for the GPD
Econ 300: Quantitative Methods in Economics. 11th Class 10/19/09
Econ 300: Quantitative Methods in Economics 11th Class 10/19/09 Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write. --H.G. Wells discuss test [do
A note on the nested Logit model
Erik Biørn Version of September 17 2008 ECON5115 - ECONOMETRICS: MICROECONOMETRICS AND DISCRETE CHOICE AUTUMN 2008 A note on the nested Logit model In this note we present the basic idea of the nested
SPC Binomial Q-Charts for Short or long Runs
SPC Binomial Q-Charts for Short or long Runs CHARLES P. QUESENBERRY North Carolina State University, Raleigh, North Carolina 27695-8203 Approximately normalized control charts, called Q-Charts, are proposed
The Collective Model of Household : Theory and Calibration of an Equilibrium Model
The Collective Model of Household : Theory and Calibration of an Equilibrium Model Eleonora Matteazzi, Martina Menon, and Federico Perali University of Verona University of Verona University of Verona
Available online at (Elixir International Journal) Statistics. Elixir Statistics 44 (2012)
7411 A class of almost unbiased modified ratio estimators population mean with known population parameters J.Subramani and G.Kumarapandiyan Department of Statistics, Ramanujan School of Mathematical Sciences
A utility maximization proof of Strassen s theorem
Introduction CMAP, Ecole Polytechnique Paris Advances in Financial Mathematics, Paris January, 2014 Outline Introduction Notations Strassen s theorem 1 Introduction Notations Strassen s theorem 2 General
Sublinear Time Algorithms Oct 19, Lecture 1
0368.416701 Sublinear Time Algorithms Oct 19, 2009 Lecturer: Ronitt Rubinfeld Lecture 1 Scribe: Daniel Shahaf 1 Sublinear-time algorithms: motivation Twenty years ago, there was practically no investigation
List of tables List of boxes List of screenshots Preface to the third edition Acknowledgements
Table of List of figures List of tables List of boxes List of screenshots Preface to the third edition Acknowledgements page xii xv xvii xix xxi xxv 1 Introduction 1 1.1 What is econometrics? 2 1.2 Is
Optimal stopping problems for a Brownian motion with a disorder on a finite interval
Optimal stopping problems for a Brownian motion with a disorder on a finite interval A. N. Shiryaev M. V. Zhitlukhin arxiv:1212.379v1 [math.st] 15 Dec 212 December 18, 212 Abstract We consider optimal
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization
for Strongly Convex Stochastic Optimization Microsoft Research New England NIPS 2011 Optimization Workshop Stochastic Convex Optimization Setting Goal: Optimize convex function F ( ) over convex domain
Unconventional Monetary Policy
Dr Martin Weale External MPC Member, University of Nottingham 8 th March 2016 Outline: Four Types of Unconventional Policy 1. Asset purchases (quantitative easing) 2. Forward guidance 3. Monetary finance
f x f x f x f x x 5 3 y-intercept: y-intercept: y-intercept: y-intercept: y-intercept of a linear function written in function notation
Questions/ Main Ideas: Algebra Notes TOPIC: Function Translations and y-intercepts Name: Period: Date: What is the y-intercept of a graph? The four s given below are written in notation. For each one,
A COMBINATION OF SURPLUS AND EXCESS REINSURANCE OF A FIRE PORTFOLIO. GUNNAR BENKTANDER AND JAN OHLIN University of Stockholm
A COBINATION OF SURPLUS AND EXCESS REINSURANCE OF A FIRE PORTFOLIO GUNNAR BENKTANDER AND JAN OHLIN University of Stockholm Reinsurance forms can roughly be classified into proportional and non-proportional.
Implemented by the education Commission of the SAV as per 1 January 2013
SAV SYLLABUS 2013 This Syllabus is identical with the CORE SYLLABUS FOR ACTUARIAL TRAINING IN EUROPE, issued by the Groupe Consultatif Actuariel Europeen and underpins the mutual recognition agreement
The Yield Envelope: Price Ranges for Fixed Income Products
The Yield Envelope: Price Ranges for Fixed Income Products by David Epstein (LINK:www.maths.ox.ac.uk/users/epstein) Mathematical Institute (LINK:www.maths.ox.ac.uk) Oxford Paul Wilmott (LINK:www.oxfordfinancial.co.uk/pw)
Review consumer theory and the theory of the firm in Varian. Review questions. Answering these questions will hone your optimization skills.
Econ 6808 Introduction to Quantitative Analysis August 26, 1999 review questions -set 1. I. Constrained Max and Min Review consumer theory and the theory of the firm in Varian. Review questions. Answering
Generating synthetic populations using IPF and Monte Carlo techniques Some new results
Research Collection Conference Paper Generating synthetic populations using IPF and Monte Carlo techniques Some new results Author(s): Frick, M.A. Publication Date: 2004 Permanent Link: https://doi.org/10.3929/ethz-a-004753115
Multi-armed bandit problems
Multi-armed bandit problems Stochastic Decision Theory (2WB12) Arnoud den Boer 13 March 2013 Set-up 13 and 14 March: Lectures. 20 and 21 March: Paper presentations (Four groups, 45 min per group). Before
Mixed Logit or Random Parameter Logit Model
Mixed Logit or Random Parameter Logit Model Mixed Logit Model Very flexible model that can approximate any random utility model. This model when compared to standard logit model overcomes the Taste variation
Module 10:Application of stochastic processes in areas like finance Lecture 36:Black-Scholes Model. Stochastic Differential Equation.
Stochastic Differential Equation Consider. Moreover partition the interval into and define, where. Now by Rieman Integral we know that, where. Moreover. Using the fundamentals mentioned above we can easily
Bias in Reduced-Form Estimates of Pass-through
Bias in Reduced-Form Estimates of Pass-through Alexander MacKay University of Chicago Marc Remer Department of Justice Nathan H. Miller Georgetown University Gloria Sheu Department of Justice February
Introductory Econometrics for Finance
Introductory Econometrics for Finance SECOND EDITION Chris Brooks The ICMA Centre, University of Reading CAMBRIDGE UNIVERSITY PRESS List of figures List of tables List of boxes List of screenshots Preface
The extent to which they accumulate productive assets.
Technology Transfer Our analysis of the neoclassical growth model illustrated that growth theory predicts significant differences in per capita income across countries due to : The extent to which they
Lecture Notes: November 29, 2012 TIME AND UNCERTAINTY: FUTURES MARKETS
Lecture Notes: November 29, 2012 TIME AND UNCERTAINTY: FUTURES MARKETS Gerard says: theory's in the math. The rest is interpretation. (See Debreu quote in textbook, p. 204) make the markets for goods over