☑A FILE HOME INSERT Paste Clipboard A1 Calibri BIU- Y x 1 2 A m B - PAGE LAYOUT 11 A Font fx C Б Using return distributions - Excel FORMULAS DATA % ? REVIEW VIEW Alignment Number Conditional Format as Cell Formatting Table Styles- Styles Cells Editing 4 D E F G H J Suppose the returns below are normally distributed. Based on these values, what is the approximate probability that your return will be less than -2.1 percent in a given year? What range of returns would you expect to see 95 percent of the time? What range would you expect to see 99 percent of the time? 4 5 6 Average return 7 Standard deviation 8 Return less than 9 10 11 6.30% 8.40% -2.10% Complete the following analysis. Do not hard code values in your calculations. You must use the built-in Excel function to answer this question. Probability less than -2.10% 12 13 14 15 Range 16 95 percent 17 99 percent 18 19 20 Lower return Upper return Sign In > 4

☑A FILE HOME INSERT Paste Clipboard A1 Calibri BIU- Y x 1 2 A m B - PAGE LAYOUT 11 A Font fx C Б Using return distributions - Excel FORMULAS DATA % ? REVIEW VIEW Alignment Number Conditional Format as Cell Formatting Table Styles- Styles Cells Editing 4 D E F G H J Suppose the returns below are normally distributed. Based on these values, what is the approximate probability that your return will be less than -2.1 percent in a given year? What range of returns would you expect to see 95 percent of the time? What range would you expect to see 99 percent of the time? 4 5 6 Average return 7 Standard deviation 8 Return less than 9 10 11 6.30% 8.40% -2.10% Complete the following analysis. Do not hard code values in your calculations. You must use the built-in Excel function to answer this question. Probability less than -2.10% 12 13 14 15 Range 16 95 percent 17 99 percent 18 19 20 Lower return Upper return Sign In > 4

Essentials of Business Analytics (MindTap Course List)

2nd Edition

ISBN:9781305627734

Author:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Publisher:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Chapter8: Time Series Analysis And_forecasting

Section: Chapter Questions

Problem 22P: Consider the following time series: a. Construct a time series plot. What type of pattern exists in...

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(Click on the icon here into a spreadsheet.) T in order to copy the contents of the data table below Investment X Y Z Expected return 17% 17% 17% Standard deviation 7% 8% 9%
Given the following probability distribution of returns: Probability Return 0.1 -15.0% 0.25 0.0% 0.3 8.5% 0.25 12.0% 0.1 32.0% what is the expected return?
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Use the following returns for X and Y. Returns Year X Y 1. 21.8% 26.4% 2. -16.8 -3.8 3. 9.8 28.4 4. 19.8 -14.6 5. 4.8. 32.4 a. Calculate the average returns for X and Y. (Do not round intermediate calculations and enter your answers as a percent rounded to 2 decimal places, e.g., 32.16.) b. Calculate the variances for X and Y. (Do not round intermediate calculations and round your answers to 6 decimal places, e.g., 32.161616.) c. Calculate the standard deviations for X and Y. (Do not round intermediate calculations and enter your answers as a percent rounded to 2 decimal places, e.g., 32.16.)
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calculate the following Sharpe Ratio (SP) Treynor Measure Jensen Measure M2 measure T2 measure Information Ratio (appraisal ratio) Fund Average return Standard Deviation Beta coefficient Unsystematic Risk A 0.240 0.220 0.800 0.017 B 0.200 0.170 0.900 0.450 C 0.290 0.380 1.200 0.074 D 0.260 0.290 1.100 0.026 E 0.180 0.400 0.900 0.121 F 0.320 0.460 1.100 0.153 G 0.250 0.190 0.700 0.120 Market 0.220 0.180 1.000 0.000 Risk free return 0.050 0.000
The expected value, standard deviation of returns, and coefficient o below.) \table[[Asset A],[Possible Outcomes,Probability,Returns (%)
Consider the following time series: a. Construct a time series plot. What type of pattern exists in the data? Is there an indication of a seasonal pattern? b. Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. c. Compute the quarterly forecasts for next year.
Prob. Return (%) B 0.1 40 G 0.2 30 O 0.3 15 L 0.2 2 S 0.2 -12 where B-Bloom,G-Good, O-Ok, L-Level and S- Slump Probability(p(x)) Return(x) (%) x*p(x) x2*p(x) B 0.1 40 0.1*40=4 0.1*402=160 G 0.2 30 0.2*30=6 0.2*302=180 O 0.3 15 0.3*15=4.5 0.3*152=67.5 L 0.2 2 0.2*2=0.4 0.2*22=0.8 S 0.2 -12 0.2*-12=-2.4 0.2*(-12)2=28.8 Expected return==E(x)=∑x*p(x)=4+6+4.5+0.4-2.4 =12.5% Variance of return=E(x2)-[E(x)]2 E(x2)=∑x2p(x)=160+180+67.5+0.8+28.8 = 437.1 Variance= 437.1-(12.5)2 = 280.85 sd of return= 280.85 = 16.76% The expected return on Granny's gold investment is 12.5% The sd of return on Granny's gold investment is 16.76% 1. In your own words, define the two components of total risk? Give examples of both risks.2. How is beta estimated or calculated?
find the trynors ratio for q and compare it to treynor ratio for m does this analysis indicate whether q is under priced, over priced or correctly priced Beta q= 1.25, rf= 2% rm=12% rq=13.5%
Calculate : M2 measure T2 measure Information Ratio (appraisal ratio) Fund Average return Standard Deviation Beta coefficient Unsystematic Risk A 0.240 0.220 0.800 0.017 B 0.200 0.170 0.900 0.450 C 0.290 0.380 1.200 0.074 D 0.260 0.290 1.100 0.026 E 0.180 0.400 0.900 0.121 F 0.320 0.460 1.100 0.153 G 0.250 0.190 0.700 0.120 Market 0.220 0.180 1.000 0.000 Risk free return 0.050 0.000
A linear regression model is Units = 4,004 – 0.659×Week. For week 46, what is the forecast for the number of units? Round your answer to the nearest whole number. units