4. Assume that a risk-free money market account is added to the market described in Q3.The continuously compounded rate of return on the money market account is log (1.1).(i) For each given μ, use Lagrange multipliers to determine the proportions (as afunction of μ) of wealth invested in the three assets available for the minimumvariance portfolio with expected return μ.(ii) Determine the market portfolio in this market and calculate its Sharp ratio.

(i) Minimum Variance Portfolio with Given Expected Return MuTo determine the proportions of wealth…

Answered: 4. Assume that a risk-free money market…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter6: Exponential And Logarithmic Functions

Section6.8: Fitting Exponential Models To Data

Problem 5SE: What does the y -intercept on the graph of a logistic equation correspond to for a population...

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What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?
Suppose an investment account is opened with aninitial deposit of 10,500 earning 6.25 interest,compounded continuously. How much will theaccount be warm after 25 years?
Suppose you have inherited K100,000 from your father-in-law that can be invested in a combination of only two stock portfolios, with the maximum investment allowed in either portfolio set at K75,000 . The first portfolio has an average rate of return of 10%, whereas the second has 20%. In terms of risk factors associated with these portfolios, the first has a risk rating of 4 (on a scale 0 to 10), and the second has 9. Since you wish to maximize your return, you will not accept an average rate of return below 12% or risk factor above 6. Formulate the linear programming model for the problem. How much should you invest in each portfolio? Solve the problem by simplex method.
A standard "money demand" function used by macroeconomists has the form In(m) = fo + B,In(GDP) + 62R, Where m is the quantity of (real) money, GDP is the value of (real) gross domestic product, and R is the value of the nominal interest rate measured in percent per year. Supposed that B, = 2.28 and B2 = - 0.09. What is the expected change in m if GDP increases by 1%? The value of m is expected to increase by approximately 2 %. (Round your response to the nearest integer) What is the expected change in m if the interest rate increases from 1% to 6%? The value of m is expected to decrease by approximately 45 %. (Round your response to the nearest integer)
We want to understand the relationship between sales growth rates (s) and project FCF growth rates (g). This is useful to think about, because in our spreadsheet models we often need an estimate of g but when we look for analyst forecasts, they often just apply to s. We consider a hypothetical firm in which there are Sales, COGS, Depreciation, Taxes, ONWC, and CAPEX occurring each year. You know that sales growth is constant and equals s. You further know that in any given year, COGS/Sales-c, the tax rate is p, the ratio of ONWC to Sales is n, and CAPEX-Depreciation, and Depreciation/Sales-d. s, c, p, n, and d are constants (i.e., fixed parameters that don't change over time). Perform an algebraic series of calculations. Start with FCF = (Sales - COGS - DA - Taxes - etc). Simplify the expression until it is in the form Sales. *((1-c-d)(1-p)-s/(1+s)*n).
Suppose that G is a function of a stock price, S and time. Suppose that σs and og are the volatilities of S and G. Show that when the expected return of S increases by Aos, the growth rate of G increases by AoG, where A is a constant.
A company that supplies gasoline to a city has recorded the weeklyusage (tons/week) for the past 3 years. The file BA2854GasolineRecord.xlsxcontains this record.(a) Propose a method for predicting the demand for gasoline. Use thatmethod to forecast demand for next year (weeks 157 to 208).(b) Improve your prediction in part (a) by including a statement about demand variability. (Hint: Look at or the range of the data.) week demand (tons) 1 1174.5 2 1316.2 3 1197 4 1127.3 5 1193.1 6 1260.7 7 1378.2 8 1273.7 9 1366.4 10 1113 11 1177.7 12 1056 13 1291.2 14 1269.1 15 1289.6 16 1181 17 1249 18 1212 19 1286.2 20 1204.8 21 1266.2 22 1332.4 23 1236.3 24 1266.1 25 1415.3 26 1100.1 27 1208.1 28 1505.1 29 1282.7 30 1190.5 31 1152.8 32 1089.7 33 1404.7 34 1308.6 35 1255.4 36 1106.7 37 1484.6 38 1317.4 39 1294.7 40 1154 41 1449.9 42 1174.9 43 1466.9 44 1282.4 45 1228 46 1174 47 1196.2 48 1443.8 49…
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The following table gives the millions of metric tons of carbon dioxide emissions in a certain country for selected years from 2010 and projected to 2032. 2012 2014 2016 2018 2020 CO2 Emissions 338.5 364.5 397.1 423.8 452.1 498.4 Year 2010 Year 2022 2024 2026 2028 2030 CO2 Emissions 557.2 592.9 628.7 662.1 707.1 (a) Create a linear function that models these data, with x as the number of years past 2010 and y as the millions of metric tons of carbon dioxide emissions. (Round all numerical values to two decimal places.) y(x) = 2032 741.7 (b) Find the model's estimate for the 2024 data point. (Round your answer to two decimal places.) million metric tons Interpret the slope of the linear model. For each year since ---Select--- (c) Find the slope of the linear model. (Round your answer to two decimal places.) , carbon dioxide emissions in the U.S. are expected to change by million metric tons.
Metropolitan Hospital has estimated its average monthly bed needs, N, as: N=460+9X�=460+9� where X = time period (months); (January 2002 = 0) Assume that no new hospital additions are expected in the area in the foreseeable future. The following monthly seasonal adjustment factors have been estimated, using data from the past five years: Forecast Metropolitan's bed demand for January, April, July, November, and December 2007. Month Adjustment Factor (%) Forecast January +5 April -15 July +4 November -5 December -25 Suppose the following actual and forecast values for June bed demands have been recorded. Year Forecast Actual 2007 1,045 1,139 2006 937 974 2005 829 895 2004 721 743 2003 613 656 2002 505 515 What seasonal adjustment factor would you recommend be used in making future June forecasts? 2.1% 5.5% 1.3%
Suppose that the index model for two Canadian stocks HD and ML is estimated with the following results: RHD =-0.03+2.10RM+eHD R-squared =0.7 RML =0.06+1.60RM+eML R-squared =0.6 σM =0.15 where M is S&P/TSX Comp Index and RX is the excess return of stock X. For portfolio P with investment proportion of 0.4 in HD and 0.6 in ML, calculate the systematic risk, non-systematic risk, and total risk of P.
A piece of equipment is being insured against early failure. The time from purchase until failure of the equipment is exponentially distributed with mean 10 years. The insurance will pay an amount x if the equipment fails during the first year, and it will pay 0.5x if failure occurs during the second or third year. If failure occurs after the first three years, no payment will be made. Calculate x such that the expected payment made under this insurance is 1000.

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