Business Analytics
3rd Edition
ISBN: 9780135231678
Author: Evans, James R. (james Robert)
Publisher: PEARSON EDUCATION (COLLEGE)
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Chapter 1, Problem 5.4CYU
Define optimization and the characteristics of optimization models.
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The class will include a data exercise where students will be introduced to publicly available data sources. Students will gain experience in manipulating data from the web and applying it to understanding the economic and demographic conditions of regions in the U.S. Regions and topics of focus will be determined (by the student with instructor approval) prior to April. What data exercise can I do to fulfill this requirement? Please explain.
Consider the ceocomp dataset of compensation information for the CEO’s of 100 U.S. companies. We wish to fit aregression model to assess the relationship between CEO compensation in thousands of dollars (includes salary andbonus, but not stock gains) and the following variates:AGE: The CEOs age, in yearsEDUCATN: The CEO’s education level (1 = no college degree; 2 = college/undergrad. degree; 3 = grad. degree)BACKGRD: Background type(1= banking/financial; 2 = sales/marketing; 3 = technical; 4 = legal; 5 = other)TENURE: Number of years employed by the firmEXPER: Number of years as the firm CEOSALES: Sales revenues, in millions of dollarsVAL: Market value of the CEO's stock, in natural logarithm unitsPCNTOWN: Percentage of firm's market value owned by the CEOPROF: Profits of the firm, before taxes, in millions of dollars1) Create a scatterplot matrix for this dataset. Briefly comment on the observed relationships between compensationand the other variates.Note that companies with negative…
6 (Model Selection, Estimation and Prediction of GARCH) Consider the daily returns rt
of General Electric Company stock (ticker: "GE") from "2021-01-01" to "2024-03-31",
comprising a total of 813 daily returns. Using the "fGarch" package of R, outputs of
fitting three GARCH models to the returns are given at the end of this question.
Model 1 ARCH (1) with standard normal innovations;
Model 2
Model 3
GARCH (1, 1) with Student-t innovations;
GARCH (2, 2) with Student-t innovations;
Based on the outputs, answer the following questions.
(a) What can be inferred from the Standardized Residual Tests conducted on Model 1?
(b) Which model do you recommend for prediction between Model 2 and Model 3?
Why?
(c) Write down the fitted model for the model that you recommended in Part (b).
(d) Using the model recommended in Part (b), predict the conditional volatility in the
next trading day, specifically trading day 814.
Chapter 1 Solutions
Business Analytics
Ch. 1 - Explain why analytics is important in todays...Ch. 1 - Define business analytics.Ch. 1 - State three examples of how business analytics is...Ch. 1 - What are the key benefits of using business...Ch. 1 - What challenges do organizations face in using...Ch. 1 - Prob. 2.1CYUCh. 1 - How do statistical methods enhance business...Ch. 1 - What is operations research/management science?Ch. 1 - How does modern business analytics integrate...Ch. 1 - What are the components of a decision support...
Ch. 1 - Define prescriptive analytics and provide two...Ch. 1 - Define prescriptive analytics and provide two...Ch. 1 - Define prescriptive analytics and provide two...Ch. 1 - State three examples of how data are used in...Ch. 1 - How are data obtained from the Web used in...Ch. 1 - Define big data and list the four characteristics...Ch. 1 - Explain the concepts of data reliability and...Ch. 1 - Define a model and state three common forms of a...Ch. 1 - Prob. 5.2CYUCh. 1 - Prob. 5.3CYUCh. 1 - Define optimization and the characteristics of...Ch. 1 - Explain the importance of assumptions in building...Ch. 1 - What is the difference between uncertainty and...Ch. 1 - List the major phases of problem solving and...Ch. 1 - What lessons did Hewlett-Packard learn about using...Ch. 1 - For each of the following scenarios, state whether...Ch. 1 - Suppose that a manufacturer can produce a part for...Ch. 1 - Use the model developed in Example 1.5 to predict...Ch. 1 - A bank developed a model for predicting the...Ch. 1 - Four key marketing decision options are price (P),...Ch. 1 - Total marketing effort is a term used to describe...Ch. 1 - A manufacturer of headphones is preparing to set...Ch. 1 - PERFORMANCE LAWN EQUIPMENT In each chapter of this...Ch. 1 - Develop a spreadsheet for computing the demand for...Ch. 1 - The Excel file Science and Engineering Jobs shows...Ch. 1 - A new graduate has taken a job with an annual...Ch. 1 - Example 1.2 in the chapter described a scenario...Ch. 1 - Return on investment (ROI) is profit divided by...Ch. 1 - In the Accounting Professionals database, use...Ch. 1 - Prob. 7PEACh. 1 - Prob. 8PEACh. 1 - The worksheet Base Data in the Excel file Credit...Ch. 1 - The Excel file Store and Regional Sales Database...Ch. 1 - Define range names for all the data and model...Ch. 1 - Define range names for all the entities in the...Ch. 1 - Define range names for all the entities in the...
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- 4 (MLE of ARCH) Suppose rt follows ARCH(2) with E(rt) = 0, rt = ut, ut = στει, σε where {+} is a sequence of independent and identically distributed (iid) standard normal random variables. With observations r₁,...,, write down the log-likelihood function for the model esti- mation.arrow_forward5 (Moments of GARCH) For the GARCH(2,2) model rt = 0.2+0.25u1+0.05u-2 +0.30% / -1 +0.20% -2, find cov(rt). 0.0035 ut, ut = στει,στ =arrow_forwardDefinition of null hypothesis from the textbook Definition of alternative hypothesis from the textbook Imagine this: you suspect your beloved Chicken McNugget is shrinking. Inflation is hitting everything else, so why not the humble nugget too, right? But your sibling thinks you’re just being dramatic—maybe you’re just extra hungry today. Determined to prove them wrong, you take matters (and nuggets) into your own hands. You march into McDonald’s, get two 20-piece boxes, and head home like a scientist on a mission. Now, before you start weighing each nugget like they’re precious gold nuggets, let’s talk hypotheses. The average weight of nuggets as mentioned on the box is 16 g each. Develop your null and alternative hypotheses separately. Next, you weigh each nugget with the precision of a jeweler and find they average out to 15.5 grams. You also conduct a statistical analysis, and the p-value turns out to be 0.01. Based on this information, answer the following questions. (Remember,…arrow_forward
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