www.thetestpreps.com CRITICAL CONCEPTS FOR THE 2014 CFA® Approximation formula for nominal required rate: ExAM Exprctrd return, variance of2-S1ock portfolio: THICAL AND PROFESSIONAL ANDARDS Professionalism Knowledge of the Law, Independence and Objectiviry Misrepresentation. Misconduct. Inregrity of Capiml Markers Material Nonpublic Information. Market Manipulation. Duties to Clients Loyalty. Prudence. and Care. Fair Dealing. Suitability, Performance Presentation. Preservation of Confidenrialiry
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October 2007 Lecture Notes Part 1 Statistics David Winter D.Winter@bris.ac.uk 1 Some Basic Concepts 2 Expectations, Moments and Descriptive Statistics 3 Bivariate Distributions 4 Estimation 5 The Normal and Related Distributions and Interval Estimation 6 Hypothesis Testing These notes provide a summary of the lectures. They are not a complete account of the unit material. You should also consult the reading as given in the unit outline and the lectures. 1 10 19 26 35 43
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APPENDICES A B C Quantitative Review References to CFA Questions Glossary A P P E N D I X A QUANTITATIVE REVIEW Students in management and investment courses typically come from a variety of backgrounds. Some, who have had strong quantitative training, may feel perfectly comfortable with formal mathematical presentation of material. Others, who have had less technical training, may easily be overwhelmed by mathematical formalism. Most students, however, will
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Research has shown that both fluorescence and photoprotection generate detectible leaf- and canopy-scale reflectance changes that are highly correlated with LUE at both the leaf and forest stand levels. Current research includes study of how these biophysical changes, with significant leaf- and forest-level reflectance correlations, can be used to quantify the degree of photosynthetic down-regulation in a spatially continuous mode. Future research directions could take the following forms. Development
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SUBJECT: BUSINESS STATISTICS COURSE CODE: MC-106 LESSON: 01 AUTHOR: SURINDER KUNDU VETTER: DR. B. S. BODLA AN INTRODUCTION TO BUSINESS STATISTICS OBJECTIVE: The aim of the present lesson is to enable the students to understand the meaning, definition, nature, importance and limitations of statistics. “A knowledge of statistics is like a knowledge of foreign language of algebra; it may prove of use at any time under any circumstance”……………………………………...Bowley. STRUCTURE: 1.1 1.2 1.3
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Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar © Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 1 Classification: Definition Given a collection of records (training set ) – Each record contains a set of attributes, one of the attributes is the class. Find a model for class attribute as a function of the values of other attributes. Goal: previously unseen
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Regression Analysis (Spring, 2000) By Wonjae Purposes: a. Explaining the relationship between Y and X variables with a model (Explain a variable Y in terms of Xs) b. Estimating and testing the intensity of their relationship c. Given a fixed x value, we can predict y value. (How does a change of in X affect Y, ceteris paribus?) (By constructing SRF, we can estimate PRF.) OLS (ordinary least squares) method: A method to choose the SRF in such a way that the sum of the residuals is as small
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Q U A N T I T A T I V E F I N A N C E V O L U M E 2 (2002) 45–60 INSTITUTE O F PHYSICS PUBLISHING RE S E A R C H PA P E R quant.iop.org Dynamics of implied volatility surfaces Rama Cont1,3 and Jos´ da Fonseca2 e Centre de Math´ matiques Appliqu´ es, Ecole Polytechnique, F-91128 e e Palaiseau, France 2 Ecole Superieure d’Ingenierie Leonard de Vinci, F-92916 Paris La D´ fense, e France E-mail: Rama.Cont@polytechnique.fr and jose.da fonseca@devinci.fr Received 20 September 2001 Published 4
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Massachusetts Institute of Technology 6.042J/18.062J, Fall ’02: Mathematics for Computer Science Professor Albert Meyer and Dr. Radhika Nagpal Course Notes 10 November 4 revised November 6, 2002, 572 minutes Introduction to Probability 1 Probability Probability will be the topic for the rest of the term. Probability is one of the most important subjects in Mathematics and Computer Science. Most upper level Computer Science courses require probability in some form, especially in analysis
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