production target for Danshui is 200,000 units but three months’ study reflects that Danshui may not meet this target in 12 months and would also overrun the cost barrier thus landing in an unprofitable situation. Plant controller, Jianye Ma presented her analysis for August production to the plant manager, Wentao Chen. According to this report, the main difficult the plant is facing is being able to hire enough people to get the production to the 200000 units per month budgeted, despite having increased wages
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In multiple linear regression analysis, R2 is a measure of the ________. A) homoskedasticity of the predictors B) misclassification rate C) percentage of the variance of the dependent variable that is explained by the set of independent (predictor) variables D) precision of the resulting model when applied to the validation data 2. Categorical variables can be used in a multiple linear regression model _________. A) by partitioning of the dataset B) when no multicollinearity among
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keeping financial records and the procedures to maintain these statements. Besides we discussed about the accounting and pricing processes to understand them to operate budgetary activities properly. Then we solve mathematical problems related to the variance over the costing method and a problem related to capital investment decision. Finally we recommend some step which should be taken to the development of the firm in long run. Task 1: 1.1 Purposes for keeping financial record: To maintain
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MODULE 2, ASSIGNMENT 4 October 22, 2013 Topic: Standard Costing, Variance Analysis and Budgets Overview The main topics for Assignment 4 are standard costing, variance analysis, and budget creation. Accountants of all management levels often have to analyze variance reports in order to help in the decision-making process. Through the differentiation of costs into fixed and variable classifications, managers are better able to construct break-even charts and other decision-making and control
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FINANCE PORTFOLIO ANALYSIS FINAL WORK DESCRIPTIVE ANALYSIS AND APPLICATION OF THE PORTFOLIO THEORY Abstract The main objective of the work is to construct, through application of the Portfolio theory, an efficient frontier which represents a set of portfolios with optimum risk-return ratio for ten companies from Mexican IPC. The sample used in this work is composed of the most representative companies in this index. A descriptive analysis of the behavior of the stocks included
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|Res/342 | |Applying Analysis of Variance | |[Anova test simulation] | |Rochelle Kuebler | |[September 23, 2011]
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Chapter 14 Factor analysis 14.1 INTRODUCTION Factor analysis is a method for investigating whether a number of variables of interest Y1 , Y2 , : : :, Yl, are linearly related to a smaller number of unobservable factors F1, F2, : : :, Fk . The fact that the factors are not observable disquali¯es regression and other methods previously examined. We shall see, however, that under certain conditions the hypothesized factor model has certain implications, and these implications in turn can be
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among Brazilian states by applying the Bayesian Dynamic Factor Model described in (OTROK; WHITEMAN, 1998) and (KOSE; OTROK; WHITEMAN, 2003) to Gini indexes over the 1976-2014 period. Our results indicate that the common factor accounts for 48 percent of the Gini index co-movements; the richest states are more exposed. We found that macroeconomic stability is negatively correlated to the common factor, meaning that stability is inequality-decreasing. The deciles analysis suggests that inequality is
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of a new tenant in the event of non-renewal. Other factors include variability in monthly operating costs and future interest rates i.e., impact on cap rate. It is important that each factor be assessed individually at a tenant level, rather than applying averages which may mask key drivers. In the “base” case, where the assumed probabilities of lease renewal and new tenant are taken and fair market rental rates are assumed, the present value of Uptown Plaza is $23,844,000. This assumes a 9% cap
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performed in Excel. There are three objectives of the exercise: 1. To estimate 3 first ACF values and run significance test for them; 2. To calculate the variance ratio for q=2, test RW1 hypothesis by applying test statistics and show the level of significance for that statistics; 3. To estimate a GARCH (1,1) model with the mean and variance equations defined. Part 1 The first task of the exercise is the estimation of the first three values of the sample autocorrelation function (ACF), which
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