Measures of risk for individual financial asset i: Variance of returns: Standard deviation of returns: Covariance of returns assets i and j: Var (ri ) = σ i2 = Expected value of [ri − E (ri )]2 σ i = σ i2 Cov(ri ‚ rj ) = σ ij = Exp. value of [ri − E (ri )][rj − E (rj )] Correlation between returns i and j: Expected portfolio return (N assets): ρij = σ ij σ iσ j N i =1 N E (rp ) = ∑ wi ri (weights wi) Portfolio variance (N assets): 7. Beta of financial asset i: σ = ∑∑ wi
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Exam Questions Question 4 (Semester 2‚ 2005) 96633337 Juan (a) Expected Portfolio Return and Risk Expected Return Risk Covariance = (0.002)(0.06)(0.09)=0.0000108 (b) Minimum Variance (Pendix Ltd) The minimum variance for this portfolio is 0.693‚ indicating that risk is minimized when 69.3 percent of the portfolio is invested in Pendix’s shares. A rational investor would not allow Pendix’s shares to account for more than this proportion
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Colonial Broadcasting Company Executive Summary Colonial Broadcasting Co (CBC)‚ a major American television network‚ must determine which of the different factors plays a key role in optimizing the ratings of its movie. The following report contains statistical analysis on the different relationships between the factors influencing ratings. The Regression Model For a detailed description of the variables and the defined statistical terms used in this report‚ see [ Annex 1 ]. Based on the sample
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Beta Management Group is a small investment management company based in Boston‚ which was founded by Ms. Sarah Wolfe (The founder and CEO of the Beta Management Group) in 1988. Ms. Wolfe follows a market timing investment strategy based on two portfolios; the Vanguard index and money market instruments. The goals of Beta Management were to enhance returns but reduce risks for clients via market timing. Ms. Wolfe would keep the vast majority of Beta’s funds in no-load‚ low-expense index funds; and
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STAT 231 (Winter 2012 - 1121) Honours Statistics Prof. R. Metzger University of Waterloo A LTEXer: W. Kong Last Revision: April 3‚ 2012 Table of Contents 1 PPDAC 1.1 1.2 1.3 1.4 1.5 2 Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Analysis . . . . .
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59 34 49 27 33 18 35 20 a. Age Weeks Employed Mean 37.75 Mean 18.6875 Standard Error 2.974195 Standard Error 2.188452 Median 37.5 Median 18.5 Mode 25 Mode 21 Standard Deviation 11.89678 Standard Deviation 8.753809 Sample Variance 141.5333 Sample Variance 76.62917 Kurtosis -1.17143 Kurtosis -0.21626 Skewness 0.337402 Skewness 0.522601 Range 36 Range 30 Minimum 23 Minimum 6 Maximum 59 Maximum 36 Sum 604 Sum 299 Count 16 Count 16 Confidence Level(99.0%) 8.764138 Confidence Level(99
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Using the simple regression model to explain the relationship between 3-Month T-bill 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…………………………………………………
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EXERCISE 29 t-TEST FOR INDEPENDENT GROUPS I STATISTICAL TECHNIQUE IN REVIEW The t-test is a parametric analysis technique used to determine significant differences between the scores obtained from two groups. The t-test uses the standard deviation to estimate the standard error of the sampling distribution and examines the differences between the means of the two groups. Since the t-test is considered fairly easy to calculate‚ researchers often use it in determining differences between two groups
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Cognitive Experimental Research Report. The Effect of Word and Picture Stimuli on the Number of Items Recalled. Abstract Based on Standing’s (1973) examination of recognition memory and the recall of words and pictures which supported the picture superiority effect‚ this experiment measured the number of items recalled by participants that had either been given word
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X has a chi-square distribution with n degrees of freedom. Therefore E(Y) = E(X) = E(X) = n. Proposition 3. If X has a chi-square distribution with n degrees of freedom‚ then the variance of X is X2 = E((X - X)2) = 2n. If Y/ has a chi-square distribution with n degrees of freedom‚ then the variance of Y is Y2 = 2n2. Proof. Since X ~ (n/2‚2) it follows from Proposition 3 of section 2.2 that X2 = (n/2)(22) = 2n. One has Y/ = X where X has a chi-square distribution
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