Investment Science Chapter 3 Dr. James A. Tzitzouris 3.1 Use A= 1− rP 1 (1+r)n with r = 7/12 = 0.58%‚ P = $25‚ 000‚ and n = 7 × 12 = 84‚ to obtain A = $377.32. 3.2 Observe that since the net present value of X is P ‚ the cash flow stream arrived at by cycling X is equivalent to one obtained by receiving payment of P every n + 1 periods (since k = 0‚ . . . ‚ n). Let d = 1/(1 + r). Then ∞ P∞ = P k=0 (dn+1 )k . Solving explicitly for the geometric series‚ we have that P∞ = Denoting
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The Potential of Bamboo(Bambusa vulgaris) Shoot as Pancit Bautista National High School Bautista‚ Pangasinan Werner J G Junio Proponent Mrs. Febren Velasquez Research Adviser i TABLE OF CONTENTS Page Project Title. . . . . . . . . . . . . . . . . . . i Table of Contents. . . . . . . . . . . . . . . . . ii CHAPTER 1. THE PROBLEM: RATIONALE AND BACKGROUND Background of the Study. . . . . . . . . . . . . . 1 Conceptual Framework. . . . . . . . . . . . . . .
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increases 3 points‚ the median will become __. a. 21 b. 21.5 c. 24 d. Cannot be determined without additional information. e. none of these 3. If you are told a population has a mean of 25 and a variance of 0‚ what must you conclude? a. Someone has made a mistake. b. There is only one element in the population. c. There are no elements in the population. d. All the elements in the population are 25. e
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Covariance = 1/5 (-0.1-0.035)(0.21-0.04) + (0.2-0.035)(0.3-0.12) + (0.05-0.035)(0.07-0.12) + (-0.05-0.035)(-0.03-0.12) + (0.02-0.035)(-0.08-.012) + (0.09-0.035)(0.25-.012) = 0.00794 Variance of A = 1/5 (-0.1-0.035)2 + (0.2-0.08)2 + (0105 – 0.035)2 + (-0.05-0.035)2 + (0.02-0.035)2 + (0.09-0.035)2 = 0.01123 Variance of B = 1/5 (0.21-0.12)2 + (0.3-0.12)2 + (0.07-0.12)2 + (-0.03-0.12)2 (-0.08-0.12)2 + (0.25-0.12)2 = 0.02448 C. Correlation = 0.00794/(0.01123) (0.02448) = 0.479 12-4. Suppose all
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and an expected return of 3.5%‚ what kind of asset is it? Is it really risk-free? 5.Take the HMC management’s views of expected returns‚ standard deviation‚ and covariance of real returns as correct. Also‚ assume that cash is riskless (i.e. zero variance and covariance). If the board allows HMC to invest in only one asset class‚ which asset classes would you advise HMC to discard right away? Why? 6.If the board allows HMC to invest in assumed riskless cash and one other asset class‚ which asset
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Executive Summary: Par‚ Inc has developed a new coating designed to resist cuts and provide a more durable ball. One concern for Par‚ Inc was the effect of the new coating on driving distances. Par would like the new cut-resistant ball to offer driving distances comparable to those of the current-model golf ball. To compare the driving distances for the two balls‚ 40 balls of both new and current models were subjected to distance test. The testing was performed with a mechanical hitting machine
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Data Analysis‚ Interpretation‚ and Conclusion‚ Part IV Domingo Melchor‚ Ed Mendoza‚ Allen LaHeist‚ Noel Alba University of Phoenix MU11MBA07 QNT/561 Dr. Jyotirmay Deb‚ Ph.D. Workshop/Week 4 July 21‚ 2012 Abstract Part IV of the business research proposal paper is the analysis and interpretation of the data collected in Part III. This installment of the paper illustrates the hypothesis testing technique of analyzing data. It answers the questions raised in Part I about low attendance
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CASE STUDY : Beta Management Company The Context Beta Management Group is a small investment management company based in Boston. It was founded in 1988 by Ms. Sarah Wolfe (The founder and CEO of the Beta Management Group). 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. Majority of Beta’s
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regression parameters obtained by the method of least squares. (c) An estimator being a random variable‚ its variance‚ like the variance of any random variable‚ measures the spread of the estimated values around the mean value of the estimator. (d) The (positive) square root value of the variance of an estimator. (e) Equal variance. (f) Unequal variance. (g) Correlation between successive values of a random variable. (h) In the regression context‚ TSS
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2Yt−2 + 0.1Yt−3 + (c) (3 marks) Yt = 0.7Yt−1 + 0.2t + t t 6. (12 marks total) Suppose that Yt follows the model Yt = 1 + 2t + 0.5ut + 0.2ut−1 + 0.1ut−2 ‚ where ut is a serially uncorrelated random variable with mean 0 and variance σu2 . (a) (3 marks) Compute the mean and variance of Yt . (b) (3 marks) Compute the first and second autocorrelations of Yt . (c) (3 marks) Show that ρj = 0 for j > 2. (d) (3 marks) Is this time series process stationary? 2 EC3304 7. (30 marks total) In the United States
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