solve the optimal weightage (including short-selling) for each stock in the portfolio in accordance to the covariance matrix. By multiplying the above matrix yields expected return on this passive portfolio as well as other statistical tools like variance and standard deviation. Hence‚ Sharpe ratio is computed and indicates the risk-adjusted return on the portfolio 2. STEPS FOR FRONTIER TO BE ADDED Result: The covariance matrix is as follows: VCV Matrix MMM T CAT UTX WFC PFE KO ORCL INTC MRK
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SUFFICIENT DIMENSION REDUCTION BASED ON NORMAL AND WISHART INVERSE MODELS A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY LILIANA FORZANI IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY R. DENNIS COOK‚ Advisor December‚ 2007 c Liliana Forzani 2007 UNIVERSITY OF MINNESOTA This is to certify that I have examined this copy of a doctoral thesis by Liliana Forzani and have found that it is complete
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(ISOM2500)[2012](f)midterm1~=0zvopee^_78631.pdf downloaded by mhwongag from http://petergao.net/ustpastpaper/down.php?course=ISOM2500&id=0 at 2013-12-16 02:44:12. Academic use within HKUST only. Business Statistics‚ ISOM2500 (L3‚ L4 & L5) Practice Quiz I 1. The following bar chart describes the results of a survey concerning the relevance of study to present job by school. Focus on the School of Business and Management. What are the mode and the median respectively? (a) Relevant‚ Neutral (b) Relevant
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be drawn from normally distributed populations. • These populations should have equal variances. • The measurement scales should be at least interval so that arithmetic operations can be used with them. Parametric tests place different emphasis on the importance of assumptions. Some tests are quite robust and hold up well despite violations. For others‚ a departure from linearity or equality of variance may threaten the validity of the results. Assessing the consequences of violating a statistical
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outperform the original portfolios and therefore it seems as though the optimisation do not improve the return of the portfolios. This might be due to the uncertainty of the expected returns used in this thesis. Keywords: Efficient frontier‚ mean-variance optimisation‚ portfolio optimisation‚ Sharpe ratio 1 Table of contents 1 INTRODUCTION 3 1.1 BACKGROUND ......................................................................................................................................
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# 0703 Firm Growth: A Survey by Alexander Coad The Papers on Economics and Evolution are edited by the Evolutionary Economics Group‚ MPI Jena. For editorial correspondence‚ please contact: evopapers@econ.mpg.de ISSN 1430-4716 © by the author Max Planck Institute of Economics Evolutionary Economics Group Kahlaische Str. 10 07745 Jena‚ Germany Fax: ++49-3641-686868 #0703 Firm Growth: A Survey∗ Alex Coad a b c† a Max Planck Institute of Economics‚ Jena‚ Germany b Centre
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|0 |1 |2 |3 |4 |5 |6 | |# of policies |21 |15 |5 |4 |2 |3 |2 | • Find the mean number of claims per day. • Find the sample variance and standard deviation. 4. A survey carried out for a supermarket classified customers according to whether their visits to the store are frequent or infrequent and
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08 ETHE AUSTRALIAN NATIONAL UNIVERSITY SCHOOL OF FINANCE AND APPLIED STATISTICS First Semester Examination 2010 QUANTITATIVE RESEARCH METHODS (STAT1008) Writing Period: 3 hours duration Study Period: 15 minutes duration Permitted Material: Non-programmable calculator‚ dictionary and 1 A4 page with notes on both sides Instructions to Candidates: • Attempt ALL questions. • Each question is of equal mark value. • Start your solution to each question on a new page. • To ensure full marks
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interpret the coefficient of correlation r=0.853=0.9236 (There is strong correlation between two variables as its near 1) d) the coefficient of determination r2=0.853(The magnitude of the coefficient of determination indicates the proportion of variance in one variable‚ explained from knowledge of the second variable) e) the standard error of estimate S.E=0.3133(The standard error is the estimated standard deviation of a statistic) f) Conduct a test of hypothesis to determine whether the
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Descriptive Statistics Mean Variance Standard Deviation Sample Covariance If it is greater than zero‚ upward sloping. This is scale dependent. Sample Correlation This is scale independent: between -1 and 1‚ close to 1 is upward‚ 0 is central‚ -1 is downward sloping. Finding the regression Regression formula with one regressor Slope Intercept Finding R2 TSS=ESS+SSR The Coefficient of Determination = R2 This gives the total fit of ‚ between 0 (chance) and
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