combinations (Essential Investment‚2003).Optimal market portfolio is regarded by Doeswijk‚ Lam and Swinkels (2012) as the best choose or benchmark choose of portfolio for any ordinary investor because it includes all assets’ value among the market.Minimum variance portfolio (MVP) focuses on the goal of reaching the lowest risk through determining appropriate weight of each asset. “MVPs illustrated returns similar to their benchmark capitalization weighted indices but with 25-30% lower standard deviation.”(Haugen
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possible outcome. (3)Standard Deviation of Return: Risk refers to the dispersion of a variable. It is commonly measured by the variance or the standard deviation. The variance of a probability distribution is the sum of the squares of the deviations of actual returns from the expected return‚ weighted by the associated probabilities. 2 = ∑ p(i)*{*R(i)-E(R)]} 2 where‚ 2 =variance‚ R®=return for the ith possible outcome‚ p(i)=probability
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York‚ and 20 were residents of North Carolina. From the data collected we could know that the higher test scores indicate higher levels of depression. The descriptive statistics of the data collected are as following: GROUPS SIZE SUM MEAN SAMPLE VARIANCE FLORIDA 20 88.50 4.42 3.81 NEW YORK 20 131.53 6.58 3.95 NORTH CAROLINA 20 137.09 6.85 2.31 For the second part of this study‚ we considered the relationship between geographic location and depression for individuals 65 years of age or older
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The 10 stocks are being selected for portfolio 1 among the 15 stocks due to having the highest market capitalization. It is a measurement derive from share price times the number of shares outstanding. In addition‚ it could be represent the public opinion of a company’s net worth. Undoubtedly‚ these 10 stocks are chosen because of having the highest company’s value‚ highest expectation from the public and both highest economic and monetary conditions. Although sometime market cap might be an economic
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Think Stats: Probability and Statistics for Programmers Version 1.6.0 Think Stats Probability and Statistics for Programmers Version 1.6.0 Allen B. Downey Green Tea Press Needham‚ Massachusetts Copyright © 2011 Allen B. Downey. Green Tea Press 9 Washburn Ave Needham MA 02492 Permission is granted to copy‚ distribute‚ and/or modify this document under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported License‚ which is available at http://creativecommons
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rate and Dow Jones Index Index 1. Introduction………………………………………………3 2. Modeling the relationship between the 3-Month T-bill rates and Dow Jones Index (First Model)……………………3 3. Hypothesis and Testing…………………………………...4 4. Empirical Analysis………………………………………...5 5. Further Comparison………………………………………5 6. Conclusion…………………………………………………7 7. Appendix……………………………………………………8 8. Reference…………………………………………………..10 1. Introduction The 3-month T-bill rates and Dow Jones index are
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Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test Andrew W. Lo A. Craig MacKinlay University of Pennsylvania In this article we test the random walk hypothesis for weekly stock market returns by comparing variance estimators derived from data sampled at different frequencies. The random walk model is strongly rejected for the entire sample period (19621985) and for all subperiod for a variety of aggregate returns indexes and size-sorted portofolios. Although
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Error 0.022666 Median 0.0607 Median 0.0511 Median 0.0108 Mode -0.5085 Mode -0.8652 Mode -0.3641 Standard Deviation 0.305747 Standard Deviation 0.489717 Standard Deviation 0.22552 Sample Variance 0.093481 Sample Variance 0.239822 Sample Variance 0.050859
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Mean and Variance of the Binomial Distribution The probability distribution of the Bernoulli trial with random variable X is given by Table 1 X=x P(X=x) 0 1-p 1 p The expectation and variance can be calculated as follow E X 01 p 1 p p Mean and Variance of the Binomial Distribution The expectation and variance can be calculated as follow Var X 0 1 p 1 p p 2 2 p p2 p1 p pq 2 Mean and Variance of the Binomial
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Unit 2: Business Resources Amy Doherty D3: Benefits & Drawbacks of Variances Variances can be defined as “A measurement of the spread between numbers in a data set. The variance measures how far each number in the set is from the mean.”1 A variance can be adverse or favourable. An adverse variance is when the actual financial figures for a business are worse than forecasted and a favourable variance is when the actual figures are better than budgeted. A budget is an documented summary
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