Singular Value Decomposition (SVD)
|
|
|
- tejaspathi lv
- 5 years ago
- Views:
Transcription
1 Singular Value Decomposition (SVD)
2 Matrix Transpose
3 Matrix Multiplication
4 Matrix Inverse If, A B = I,identity matrix Then, B= A -1 Identity matrix:
5 X= UΣV T U and V are Orthonormal matrices rxr diagonal matrix with r non-zero diagonal elements
6 X U = x x V T OPTIONAL R Code > M=matrix(c(1,0,0,0,0,0,0,4,0,3,0,0,0,0,0,0,2,0,0,0),nrow=4,ncol=5) > X=svd(M) > X$u > X$d > X$v > X$u%*%diag(X$d)%*%t(X$v)
7 Applications of SVD in image processing closest rank-k approximation for a matrix X X k = k u i= 1 Each term in the summation expression above is called principal image i Σ i v T i
8 Original matrix (X) Original size *5=20 bytes X U = x x k=1 0 x 4 x = Compressed size *1+1+1*5=10 bytes V T
9 k=2 0 0 x 4 0 x = Compressed size *2+2+2*5=20 bytes k= x 4 0 0x = Compressed size *3+3+3*5=30 bytes k= = Compressed size *4+4+4*5=40 bytes x x
10 The image compression example in Original size = 384*384 bytes = 147,456 bytes k=1: 384*1+1+1*384=769 bytes k=10: 384* *384=7,690 bytes k=20: 384* *384=15,380 bytes k=50: 384* *384=38,450 bytes k=100: 384* *384=76,900 bytes k=200: 384* *384=153,800 bytes
A way to improve incremental 2-norm condition estimation
A way to improve incremental 2-norm condition estimation Jurjen Duintjer Tebbens Institute of Computer Science Academy of Sciences of the Czech Republic duintjertebbens@cs.cas.cz Miroslav Tůma Institute
Image analysis of malign melanoma: Waveles and svd
Image analysis of malign melanoma: Waveles and svd Dan Dolonius University of Gothenburg gusdolod@student.gu.se April 28, 2015 Dan Dolonius (Applied Mathematics) Image analysis of malign melanoma April
Geometry of orthogonally invariant matrix varieties
Geometry of orthogonally invariant matrix varieties Dmitriy Drusvyatskiy Mathematics, University of Washington Joint work with H.-L. Lee (UW), G. Ottaviano (Florence), and R.R. Thomas (UW) UC Davis Algebra
A general approach to calculating VaR without volatilities and correlations
page 19 A general approach to calculating VaR without volatilities and correlations Peter Benson * Peter Zangari Morgan Guaranty rust Company Risk Management Research (1-212) 648-8641 zangari_peter@jpmorgan.com
Partial Lanczos SVD methods for R
Partial Lanczos SVD methods for R Bryan Lewis 1, adapted from the work of Jim Baglama 2 and Lothar Reichel 3 1 REvolution Computing 2 University of Rhode Island 3 Kent State University UseR 2009 Outline
IDENTIFYING BROAD AND NARROW FINANCIAL RISK FACTORS VIA CONVEX OPTIMIZATION: PART I
1 IDENTIFYING BROAD AND NARROW FINANCIAL RISK FACTORS VIA CONVEX OPTIMIZATION: PART I Lisa Goldberg lrg@berkeley.edu MMDS Workshop. June 22, 2016. joint with Alex Shkolnik and Jeff Bohn. Identifying Broad
Exercise List: Proving convergence of the (Stochastic) Gradient Descent Method for the Least Squares Problem.
Exercise List: Proving convergence of the (Stochastic) Gradient Descent Method for the Least Squares Problem. Robert M. Gower. October 3, 07 Introduction This is an exercise in proving the convergence
The Azéma-Yor Embedding in Non-Singular Diffusions
The Azéma-Yor Embedding in Non-Singular Diffusions J.L. Pedersen and G. Peskir Let (X t ) t 0 be a non-singular (not necessarily recurrent) diffusion on R starting at zero, and let ν be a probability measure
8. International Financial Allocation
8. International Financial Allocation An Example and Definitions... 1 Expected eturn, Variance, and Standard Deviation.... S&P 500 Example... The S&P 500 and Treasury bill Portfolio... 8.S. 10-Year Note
Solving the Stochastic Steady-State Diffusion Problem Using Multigrid
Solving the Stochastic Steady-State Diffusion Problem Using Multigrid Tengfei Su Applied Mathematics and Scientific Computing Program Advisor: Howard Elman Department of Computer Science May 5, 2016 Tengfei
Submitting Secondary Claims with COB Data Elements - Facilities
Overview Submitting Secondary Claims with COB Data Elements - Facilities This supplement to the billing section of the AmeriHealth Caritas Pennsylvania Claims Filing Instruction Manual provides specific
Design of a Financial Application Driven Multivariate Gaussian Random Number Generator for an FPGA
Design of a Financial Application Driven Multivariate Gaussian Random Number Generator for an FPGA Chalermpol Saiprasert, Christos-Savvas Bouganis and George A. Constantinides Department of Electrical
BOUNDS FOR THE LEAST SQUARES RESIDUAL USING SCALED TOTAL LEAST SQUARES
BOUNDS FOR THE LEAST SQUARES RESIDUAL USING SCALED TOTAL LEAST SQUARES Christopher C. Paige School of Computer Science, McGill University Montreal, Quebec, Canada, H3A 2A7 paige@cs.mcgill.ca Zdeněk Strakoš
Perturbation Bounds for Determinants and Characteristic Polynomials
Perturbation Bounds for Determinants and Characteristic Polynomials Ilse Ipsen North Carolina State University, Raleigh, USA Joint work with: Rizwana Rehman Characteristic Polynomials n n complex matrix
Option Valuation (Lattice)
Page 1 Option Valuation (Lattice) Richard de Neufville Professor of Systems Engineering and of Civil and Environmental Engineering MIT Massachusetts Institute of Technology Option Valuation (Lattice) Slide
Day 10: Additional Scaling Issues
Day 10: Additional Scaling Issues Kenneth Benoit Essex Summer School 2011 July 22, 2011 Problems to solve I: Conditional (non-)independence Words occur in order In occur words order. Occur order words
CHAPTER XV -- RESIGNATION AND REINSTATEMENT. Section General Provisions Classified Employee Early Retirement Incentive (Board Policy)
CHAPTER XV -- RESIGNATION AND REINSTATEMENT Rule 15.1 RESIGNATION AND RETIREMENT Section 15.1.1 General Provisions 15.1.2 Classified Employee Early Retirement Incentive (Board Policy) Rule 15.2 REINSTATEMENT
Hedging under Model Uncertainty
Hedging under Model Uncertainty Efficient Computation of the Hedging Error using the POD 6th World Congress of the Bachelier Finance Society June, 24th 2010 M. Monoyios, T. Schröter, Oxford University
INFORMATION ABOUT EMBASSY OF INDIA, BEIJING, REQUIRED UNDER SECTION 4(1)(B) OF THE RTI ACT, 2005
INFORMATION ABOUT EMBASSY OF INDIA, BEIJING, REQUIRED UNDER SECTION 4()(B) OF THE RTI ACT, 2005 (i) the particulars of its organization, functions and duties; Embassy is headed by Ambassador of India and
2018 CERTIFIED TOTALS JRC - Jr College
Property Count: 105,320 ARB Approved Totals 12/5/2018 3:59:10PM Land Homesite: 925,101,628 Non Homesite: 1,291,819,599 Ag Market: 2,868,865,199 Timber Market: 0 Total Land (+) 5,085,786,426 Improvement
Facility Instruction Manual:
Facility Instruction Manual: Submitting Secondary Claims with COB Data Elements Overview This supplement to the billing section of the Passport Health Plan (PHP) Provider Manual provides specific coding
Convex-Cardinality Problems Part II
l 1 -norm Methods for Convex-Cardinality Problems Part II total variation iterated weighted l 1 heuristic matrix rank constraints Prof. S. Boyd, EE364b, Stanford University Total variation reconstruction
TRΛNSPΛRΣNCY ΛNΛLYTICS
TRΛNSPΛRΣNCY ΛNΛLYTICS RISK-AI, LLC PRESENTATION INTRODUCTION I. Transparency Analytics is a state-of-the-art risk management analysis and research platform for Investment Advisors, Funds of Funds, Family
Lecture 8 : The dual lattice and reducing SVP to MVP
CSE 206A: Lattice Algorithms and Applications Spring 2007 Lecture 8 : The dual lattice and reducing SVP to MVP Lecturer: Daniele Micciancio Scribe: Scott Yilek 1 Overview In the last lecture we explored
2016 CERTIFIED TOTALS JRC - Jr College
Property Count: 106,117 ARB Approved Totals 1/20/2017 12:28:00PM Land Homesite: 684,819,553 Non Homesite: 1,128,556,336 Ag Market: 2,119,949,178 Timber Market: 0 Total Land (+) 3,933,325,067 Improvement
2018 CERTIFIED TOTALS GRA - Grayson County
Property Count: 105,325 ARB Approved Totals 12/5/2018 3:56:37PM Land Homesite: 925,101,628 Non Homesite: 1,291,819,599 Ag Market: 2,868,865,199 Timber Market: 0 Total Land (+) 5,085,786,426 Improvement
What Can a Life-Cycle Model Tell Us About Household Responses to the Financial Crisis?
What Can a Life-Cycle Model Tell Us About Household Responses to the Financial Crisis? Sule Alan 1 Thomas Crossley 1 Hamish Low 1 1 University of Cambridge and Institute for Fiscal Studies March 2010 Data:
Life Insurer Financial Profile
Life Insurer Financial Profile Company New York Life Ins Massachusetts Transamerica Life John Hancock Life & Mutual of Omaha Genworth Life Ins MedAmerica Ins Co Co Mutual Life Ins Ins Co Health Ins Ins
Tree methods for Pricing Exotic Options
Tree methods for Pricing Exotic Options Antonino Zanette University of Udine antonino.zanette@uniud.it 1 Path-dependent options Black-Scholes model Barrier option. ds t S t = rdt + σdb t, S 0 = s 0, Asian
CALHOUN COUNTY APPRAISAL DISTRICT ANNUAL REPORT Jesse W. Hubbell, Chief Appraiser
CALHOUN COUNTY APPRAISAL DISTRICT ANNUAL REPORT 2015 Jesse W. Hubbell, Chief Appraiser Calhoun County Appraisal District 426 W. Main St. Port Lavaca TX 77979 361-552-4560 361-552-4787 October 2015 CALHOUN
Aligning Forces. for Quality. Achieve. organization. About our. California
cost payment/incentives care across settings Anthem Blue Cross Value Based Purchasing Design (Reference Based Pricing) Ivan J Kamil MD Jeff.kamil@ @wellpoint. com Anthem Blue Cross Woodland Hills, California
Modeling Portfolios that Contain Risky Assets Risk and Reward II: Markowitz Portfolios
Modeling Portfolios that Contain Risky Assets Risk and Reward II: Markowitz Portfolios C. David Levermore University of Maryland, College Park Math 420: Mathematical Modeling February 4, 2013 version c
WEB-BASED BUDGET USER-GUIDE
WEB-BASED BUDGET USER-GUIDE Please enter your network username and password to access your account. USERNAME: PASSWORD: For all new users, please provide your network username for the initial setup and
4.6 GENEVA INTRODUCTION BOOKING JOURNAL AND MANUAL TRANSACTIONS (NOT FOR DISTRIBUTION FOR INTERNAL USE ONLY)
4.6 GENEVA INTRODUCTION BOOKING JOURNAL AND MANUAL TRANSACTIONS (NOT FOR DISTRIBUTION FOR INTERNAL USE ONLY) Table of Contents BOOKING JOURAL AND MANUAL TRANSACTIONS... 3 INVESTMENT RELATED JOURNALS...
End-to-End Congestion Control for the Internet: Delays and Stability
End-to-End Congestion Control for the Internet: Delays and Stability Ramesh Johari and David Tan Statistical Laboratory, University of Cambridge March 16, 2000 Abstract Under the assumption that queueing
Interval Methods and Condition Numbers of Linear Algebraic Systems. Интервальные методы и числа обусловленности линейных алгебраических систем
Interval Computations No 4, 1994 Interval Methods and Condition Numbers of Linear Algebraic Systems Søren Christiansen The sensitivity of linear systems is often expressed in terms of condition numbers,
arxiv: v1 [q-fin.mf] 8 Sep 2017
![arxiv: v1 [q-fin.mf] 8 Sep 2017](/thumbs/72/67412039.jpg "arxiv: v1 [q-fin.mf] 8 Sep 2017")
Winning Investment Strategies Based on Financial Crisis Indicators Antoine Kornprobst Université Paris 1 Panthéon-Sorbonne, Labex ReFi arxiv:1709.02701v1 [q-fin.mf] 8 Sep 2017 September 7th 2017 Abstract
Revenue from the Saints, the Showoffs, and the Predators: Comparisons of Auctions with Price-Preference Values Supplemental Information
Revenue from the Saints, the Showoffs, and the Predators: Comparisons of Auctions with Price-Preference Values Supplemental Information Timothy C. Salmon Florida State University R. Mark Isaac Florida
MORITA EQUIVALENCE OF SEMIGROUPS REVISITED: FIRM SEMIGROUPS
MORITA EQUIVALENCE OF SEMIGROUPS REVISITED: FIRM SEMIGROUPS László Márki Rényi Institute, Budapest joint work with Valdis Laan and Ülo Reimaa Berlin, 10 October 2017 Monoids Two monoids S and T are Morita
Modelling, Estimation and Hedging of Longevity Risk
IA BE Summer School 2016, K. Antonio, UvA 1 / 50 Modelling, Estimation and Hedging of Longevity Risk Katrien Antonio KU Leuven and University of Amsterdam IA BE Summer School 2016, Leuven Module II: Fitting
CALCULATING RETURNS TO DEGREE USING ADMINISTRATIVE DATA TOM SCHENK JR., IOWA DEPARTMENT OF EDUCATION KIYOKAZU MATSUYAMA, IOWA WORKFORCE DEVELOPMENT
CALCULATING RETURNS TO DEGREE USING ADMINISTRATIVE DATA TOM SCHENK JR., IOWA DEPARTMENT OF EDUCATION KIYOKAZU MATSUYAMA, IOWA WORKFORCE DEVELOPMENT MOTIVATING QUESTIONS What are Iowa community colleges
The New Issues Puzzle
The New Issues Puzzle Professor B. Espen Eckbo Advanced Corporate Finance, 2009 Contents 1 IPO Sample and Issuer Characteristics 1 1.1 Annual Sample Distribution................... 1 1.2 IPO Firms are
Bayesian Linear Model: Gory Details
Bayesian Linear Model: Gory Details Pubh7440 Notes By Sudipto Banerjee Let y y i ] n i be an n vector of independent observations on a dependent variable (or response) from n experimental units. Associated
Robust Principal Component Analysis? John Wright
Robust Principal Component Analysis? John Wright Microsoft Research Modern Massive Data Sets, Stanford, June 18, 2010 ROBUST PRINCIPAL COMPONENT ANALYSIS? Joint work with Emmanuel Candès, Xiaodong Li and
No, because np = 100(0.02) = 2. The value of np must be greater than or equal to 5 to use the normal approximation.
1) If n 100 and p 0.02 in a binomial experiment, does this satisfy the rule for a normal approximation? Why or why not? No, because np 100(0.02) 2. The value of np must be greater than or equal to 5 to
Nominal exchange rate
Nominal exchange rate The nominal exchange rate between two currencies is the price of one currency in terms of the other. The nominal exchange rate (or, for short, exchange rate) will be denoted by the
The R.L. Brown Advisory Group, LLC Business Continuity Plan (BCP)
The R.L. Brown Advisory Group, LLC Business Continuity Plan (BCP) I. Emergency Contact Persons Our firm s emergency contact person is: Robert L. Brown, President, 925-425-9610, bob@rlbrownadvisors.com
FE670 Algorithmic Trading Strategies. Stevens Institute of Technology
FE670 Algorithmic Trading Strategies Lecture 4. Cross-Sectional Models and Trading Strategies Steve Yang Stevens Institute of Technology 09/26/2013 Outline 1 Cross-Sectional Methods for Evaluation of Factor
Arbitrage Enforced Valuation of Financial Options. Outline
Arbitrage Enforced Valuation of Financial Options Richard de Neufville Professor of Engineering Systems and of Civil and Environmental Engineering MIT Arbitrage Enforced Valuation Slide 1 of 40 Outline
Show that the column rank and the row rank of A are both equal to 3.
hapter Vectors and matrices.. Exercises. Let A 2 5 4 3 2 4 2 2 3 5 4 2 4 3 Show that the column rank and the row rank of A are both equal to 3. 2. Let x and y be column vectors of size n, andleti be the
Why Surplus Consumption in the Habit Model May be Less Pe. May be Less Persistent than You Think
Why Surplus Consumption in the Habit Model May be Less Persistent than You Think October 19th, 2009 Introduction: Habit Preferences Habit preferences: can generate a higher equity premium for a given curvature
Optimal Portfolios and Random Matrices
Optimal Portfolios and Random Matrices Javier Acosta Nai Li Andres Soto Shen Wang Ziran Yang University of Minnesota, Twin Cities Mentor: Chris Bemis, Whitebox Advisors January 17, 2015 Javier Acosta Nai
Vega Maps: Predicting Premium Change from Movements of the Whole Volatility Surface
Vega Maps: Predicting Premium Change from Movements of the Whole Volatility Surface Ignacio Hoyos Senior Quantitative Analyst Equity Model Validation Group Risk Methodology Santander Alberto Elices Head
A Non-Normal Principal Components Model for Security Returns
A Non-Normal Principal Components Model for Security Returns Sander Gerber Babak Javid Harry Markowitz Paul Sargen David Starer February 21, 219 Abstract We introduce a principal components model for securities
FACILITY LEGAL NAME and / or OWNERSHIP CHANGE Instructions for Form S3
FACILITY LEGAL NAME and / or OWNERSHIP CHANGE Instructions for Form S3 Per MCAPCO Regulation 1.5212 Applications, an application for ownership transfer of a permit may be made by letter to MCAQ if no alteration
Number of countries Average Median
GLOBAL financial DEVELOPMENT REPORT 05/06 appendix A 57 MAP A. DEPTH FINANCIAL INSTITUTIONS To approximate financial institutions depth, this map uses domestic private credit to the real sector by deposit
Ornstein-Uhlenbeck Theory
Beatrice Byukusenge Department of Technomathematics Lappeenranta University of technology January 31, 2012 Definition of a stochastic process Let (Ω,F,P) be a probability space. A stochastic process is
Melbourne Institute Working Paper Series Working Paper No. 22/07
Melbourne Institute Working Paper Series Working Paper No. 22/07 Permanent Structural Change in the US Short-Term and Long-Term Interest Rates Chew Lian Chua and Chin Nam Low Permanent Structural Change
Attilio Meucci. Managing Diversification
Attilio Meucci Managing Diversification A. MEUCCI - Managing Diversification COMMON MEASURES OF DIVERSIFICATION DIVERSIFICATION DISTRIBUTION MEAN-DIVERSIFICATION FRONTIER CONDITIONAL ANALYSIS REFERENCES
The Usefulness of Bayesian Optimal Designs for Discrete Choice Experiments
The Usefulness of Bayesian Optimal Designs for Discrete Choice Experiments Roselinde Kessels Joint work with Bradley Jones, Peter Goos and Martina Vandebroek Outline 1. Motivating example from healthcare
MASM006 UNIVERSITY OF EXETER SCHOOL OF ENGINEERING, COMPUTER SCIENCE AND MATHEMATICS MATHEMATICAL SCIENCES FINANCIAL MATHEMATICS.
MASM006 UNIVERSITY OF EXETER SCHOOL OF ENGINEERING, COMPUTER SCIENCE AND MATHEMATICS MATHEMATICAL SCIENCES FINANCIAL MATHEMATICS May/June 2006 Time allowed: 2 HOURS. Examiner: Dr N.P. Byott This is a CLOSED
Option Pricing Using Monte Carlo Methods. A Directed Research Project. Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE
Option Pricing Using Monte Carlo Methods A Directed Research Project Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE in partial fulfillment of the requirements for the Professional Degree
Maintaining prior distributions across evolving eigenspaces An application to portfolio construction
Maintaining prior distributions across evolving eigenspaces An application to portfolio construction Kevin R. Keane and Jason J. Corso Department of Computer Science and Engineering University at Buffalo,
Trend Analysis of Indian Stock Market Using Dynamic Mode Decomposition
Trend Analysis of Indian Stock Market Using Dynamic Mode Decomposition Deepthi Praveenlal Kuttichira,1 Gopalakrishnan E.A 2 Vijay Krishna Menon 3 K.P Soman 4 Center Of Computational Engineering and Networking,
Methodology Document of NIFTY50 Value 20 Index March 2017
Methodology Document of NIFTY50 Value 20 Index March 2017 Contact Email: iisl@nse.co.in Tel: +91-22-26598386 Address: Exchange Plaza, Bandra Kurla Complex, Bandra (East), Mumbai - 400 051(India). Contents
Modeling multiple runoff tables
Modeling multiple runoff tables Vincent Lous www.posthuma-partners.nl Motivation Why creating a "model" for all lines of business is important Motivation Why creating a "model" for all lines of business
MA131 Lecture 8.2. The normal distribution curve can be considered as a probability distribution curve for normally distributed variables.
Normal distribution curve as probability distribution curve The normal distribution curve can be considered as a probability distribution curve for normally distributed variables. The area under the normal
Layout Strategy. Dr. Keong Leong Management Department UNLV
Layout Strategy Dr. Keong Leong Management Department UNLV Key Learning Outcome When you complete this class you should be able to: Explain the strategic importance of layout decisions Develop a good layout
ECE 586GT: Problem Set 1: Problems and Solutions Analysis of static games
University of Illinois Fall 2018 ECE 586GT: Problem Set 1: Problems and Solutions Analysis of static games Due: Tuesday, Sept. 11, at beginning of class Reading: Course notes, Sections 1.1-1.4 1. [A random
AMENDED EXHIBIT A STANDARDS FOR COMPLIANCE
AMENDED EXHIBIT A STANDARDS FOR COMPLIANCE 1. PROOF OF COVERAGE REPORTING REQUIREMENTS AIG must achieve and maintain a performance standard of 90 percent or better timeliness in filing guaranty contracts
Coale & Kisker approach
Coale & Kisker approach Often actuaries need to extrapolate mortality at old ages. Many authors impose q120 =1but the latter constraint is not compatible with forces of mortality; here, we impose µ110
Jianfei Shen. School of Economics, The University of New South Wales, Sydney 2052, Australia
. Zero-sum games Jianfei Shen School of Economics, he University of New South Wales, Sydney, Australia emember that in a zerosum game, u.s ; s / C u.s ; s / D, s ; s. Exercise. Step efer Matrix A, we know
Table of. contents. Key. Explanation to. Revenue from
Memorandum: Societal impact calculatio on when setting-up complete infrastructure of defibrillators, includingg the FirstAED system for emergency call out of first responderss via smartphones based on
Discrete probability distributions
Discrete probability distributions Probability distributions Discrete random variables Expected values (mean) Variance Linear functions - mean & standard deviation Standard deviation 1 Probability distributions
Speculative Betas. Harrison Hong and David Sraer Princeton University. September 30, 2012
Speculative Betas Harrison Hong and David Sraer Princeton University September 30, 2012 Introduction Model 1 factor static Shorting OLG Exenstion Calibration High Risk, Low Return Puzzle Cumulative Returns
Financial Engineering
Financial Engineering Boris Skorodumov Junior Seminar September 8, 2010 Biography Academics B.S Moscow Engineering Physics Institute, Moscow, Russia, 2002 Focus : Applied Mathematical Physics Ph.D Nuclear
Some Bounds for the Singular Values of Matrices
Applied Mathematical Sciences, Vol., 007, no. 49, 443-449 Some Bounds for the Singular Values of Matrices Ramazan Turkmen and Haci Civciv Department of Mathematics, Faculty of Art and Science Selcuk University,
Lecture 16. Options and option pricing. Lecture 16 1 / 22
Lecture 16 Options and option pricing Lecture 16 1 / 22 Introduction One of the most, perhaps the most, important family of derivatives are the options. Lecture 16 2 / 22 Introduction One of the most,
AUTOMATION, algorithmic trading, and globalization
A Study of Russell 3000 Dimensionality Using non-linear Dimensionality Reduction Techniques Nitish Bahadur, Kelum Gajamannage, and Randy Paffenroth 1 Abstract Financial markets are high-dimensional, complex,
Chapter 4: Asymptotic Properties of MLE (Part 3)
Chapter 4: Asymptotic Properties of MLE (Part 3) Daniel O. Scharfstein 09/30/13 1 / 1 Breakdown of Assumptions Non-Existence of the MLE Multiple Solutions to Maximization Problem Multiple Solutions to
Methodology Document of LIX 15 Index October 2015
Methodology Document of LIX 15 Index October 2015 Contact Email: iisl@nse.co.in Tel: +91-22-26598386 Address: Exchange Plaza, Bandra Kurla Complex, Bandra (East), Mumbai - 400 051(India). Contents Introduction:...
AIM Note for Investing Companies
AIM Note for Investing Companies July 2016 AIM NOTE FOR INVESTING COMPANIES Contents 1 Introduction 3 2 Investing companies 3 3 Appropriateness for AIM 3 3.1 Appropriateness of certain entities 3 3.2 Directors
WORKSHOP : FINANCIAL STATEMENT PRESENTATION
The Actuarial Society of Hong Kong WORKSHOP : FINANCIAL STATEMENT PRESENTATION 2017 Insurance IFRS Seminar Steve Cheung Session 17 Agenda 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.1 2.2 2.3 Product features
The skew-rank of oriented graphs
The skew-rank of oriented graphs Xueliang Li a, Guihai Yu a,b, a Center for Combinatorics and LPMC-TJKLC arxiv:14047230v1 [mathco] 29 Apr 2014 Nankai University, Tianjin 300071, China b Department of Mathematics
Coordination of Benefits (COB) Professional
Coordination of Benefits (COB) Professional Submitting COB claims electronically saves providers time and eliminates the need for paper claims with copies of the other payer s explanation of benefits (EOB)
All About Risk... A Senior Project submitted to The Division of Science, Mathematics, and Computing of Bard College. by Dexin Zhou
All About Risk... A Senior Project submitted to The Division of Science, Mathematics, and Computing of Bard College by Dexin Zhou Annandale-on-Hudson, New York April, 2009 Dedication Dedicated to all my
Chapter 8: CAPM. 1. Single Index Model. 2. Adding a Riskless Asset. 3. The Capital Market Line 4. CAPM. 5. The One-Fund Theorem
Chapter 8: CAPM 1. Single Index Model 2. Adding a Riskless Asset 3. The Capital Market Line 4. CAPM 5. The One-Fund Theorem 6. The Characteristic Line 7. The Pricing Model Single Index Model 1 1. Covariance
2D penalized spline (continuous-by-continuous interaction)
2D penalized spline (continuous-by-continuous interaction) Two examples (RWC, Section 13.1): Number of scallops caught off Long Island Counts are made at specific coordinates. Incidence of AIDS in Italian
Reactive Synthesis Without Regret
Reactive Synthesis Without Regret (Non, rien de rien... ) Paul Hunter, Guillermo A. Pérez, Jean-François Raskin CONCUR 15 @ Madrid September, 215 Outline 1 Regret 2 Playing against a positional adversary
E&G, Ch. 8: Multi-Index Models & Grouping Techniques I. Multi-Index Models.
1 E&G, Ch. 8: Multi-Index Models & Grouping Techniques I. Multi-Index Models. A. The General Multi-Index Model: R i = a i + b i1 I 1 + b i2 I 2 + + b il I L + c i Explanation: 1. Let I 1 = R m ; I 2 =
Accelerated Stochastic Gradient Descent Praneeth Netrapalli MSR India
Accelerated Stochastic Gradient Descent Praneeth Netrapalli MSR India Presented at OSL workshop, Les Houches, France. Joint work with Prateek Jain, Sham M. Kakade, Rahul Kidambi and Aaron Sidford Linear
Computational Methods for Option Pricing. A Directed Research Project. Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE
Computational Methods for Option Pricing A Directed Research Project Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE in partial fulfillment of the requirements for the Professional Degree
Regression Review and Robust Regression. Slides prepared by Elizabeth Newton (MIT)
Regression Review and Robust Regression Slides prepared by Elizabeth Newton (MIT) S-Plus Oil City Data Frame Monthly Excess Returns of Oil City Petroleum, Inc. Stocks and the Market SUMMARY: The oilcity
Valuation of derivative assets Lecture 6
Valuation of derivative assets Lecture 6 Magnus Wiktorsson September 14, 2017 Magnus Wiktorsson L6 September 14, 2017 1 / 13 Feynman-Kac representation This is the link between a class of Partial Differential
Examples of a Release Conditions Matrix
Related Guide: 9. Conditions Matrix Examples of a Conditions Matrix Members of a jurisdiction s PSA implementation team can draw from this resource as they develop their own Conditions Matrix. A blank
SOLUTIONS 913,
Illinois State University, Mathematics 483, Fall 2014 Test No. 3, Tuesday, December 2, 2014 SOLUTIONS 1. Spring 2013 Casualty Actuarial Society Course 9 Examination, Problem No. 7 Given the following information
Understanding Deep Learning Requires Rethinking Generalization
Understanding Deep Learning Requires Rethinking Generalization ChiyuanZhang 1 Samy Bengio 3 Moritz Hardt 3 Benjamin Recht 2 Oriol Vinyals 4 1 Massachusetts Institute of Technology 2 University of California,
Tax Reform. Individuals: The new tax bill: the good, the not so good, the bad, and the ugly. Strand Boyce O Shaughnessy, CPAs, Inc.
Volume 11, Issue 1 January 2018 Strand Boyce O Shaughnessy, CPAs, Inc. Tax Reform The new tax bill: the good, the not so good, the bad, and the ugly. To say that December was an interesting month in the
Fitting Least squares
3 Fttg lest sqres Fttg Lest sqres esd, /3/7 tos rgros e-ml: rgros@csd.oc.gr Now: pool of other techqes If we kow whch pots belog to the le, how do we fd the optml le prmeters? Lest sqres, Wht f there re
GOLD & SILVER MINING SECTORS
PC WONG DISCLAIMER The views by the author are his alone. All opinions expressed by the author are subject to change. The viewer is not to assume the performance of any company shares will equal its past