Calculate the MAPE for each of the 3 forecast models used in the table.Which should be used for forecasting efforts, and why? A1 Month2 Jan3 Feb4Mar5Apr6 May7 Jun8 Jul9 Aug10 Sept11 Oct12 Nov13 Dec14 JanBCDEFSales ('000 Units) 5-month Moving Average Weighted moving average Exponential smoothing forecast Alpha16000 1-Alpha16,00019,0001600018,0001660015,0001688020,0001650418,00017203.222,00017362.5620,00018290.04819,00018632.038422,00018705.6307224,00019364.5045823,00020291.603661760018000186001900019800202002140018100163001830018300206002040019600209002290023200G0.20.8

Time series are used to forecast or predict the variable over the time. There are four types of…

Answered: Calculate the MAPE for each of the 3…

MATLAB: An Introduction with Applications

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Author:Amos Gilat

Publisher:Amos Gilat

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MARKET CAPITALIZATION is taken as a variable to be predicted, the rest are the predictors Create the following variables in the excel sheet: 1. Change Total Assets to ‘Log(Total Assets)-LogTA, 2. create a new variable called CR (CR= current assets/current liabilities), 3. Create a new variable called DR (DR= Total Debt/Total Asset), 4. Change Market Capitalization to Log(Market Capitalization)-LogMCAP Focus on LogMCAP, LogTA, CR, DR, EBIT, LogMCAP to be predicted, the rest are predictors for the purpose of completing the assignment. 1. Perform a descriptive analysis in R , using the variables given . 2. Design a structure to show the training data, testing data, and discuss the validation process using your dataset. 3. Perform a regression analysis, show the clearly and discuss on the predictive power using the forecast figures and coefficients. 4. You may include scatter plots to address the significance of the predictors, OR extend your analysis by using other statistical…
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O Equation: EQX02 Workfile: TEMP:Untitled\ View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable INTEREST Method Least Squares Date: 09/10/20 Time: 21:33 Sample (adjusted) 2010M03 2019M12 Included observations: 118 after adjustments Variable Coeficient Std Error 1-Statstic Prob. 0.3778 0.0000 INTEREST(-1) INTEREST(-2) UNEMP(-1) UNEMP(-2) -0.149421 1.366098 0.365452 0.006215 0017402 0.168770 0 087917 0.088887 0.074166 0.075188 -0.885355 15.53853 4111411 0.083802 0.0001 09334 0.8174 0.231441 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statstic Prob(F-statistic) 0.992907 Mean dependent var 0.992655 SD. dependent var 0.102165 Akaike info critenon 1.179453 Schwarz criterion 104.2976 Hannan Quinn criter. 3954.322 Durbin-Watson stat 0.000000 2.776102 1.192120 -1.683011 1.565609 -1.635342 1.877536 Consider the above ARDL model for INTEREST (interest) where UNEMP is the unemployment rate. What is the degrees of freemdom of…
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Calculate the MAPE for each of the 3 forecast models used in the table. Which should be used for forecasting efforts, and why?