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6. Describe the nature of omitted variable bias as it relates to time series. In what cases
does controlling for trend variables solve the omitted variable bias?
7. Event studies.
a. Describe the six steps to conduct a financial event study.
b. What is the relationship between the
use of financial event studies for causal inference?
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- This is a Business Forecasting Question. I know the 3 stages for the evolution of forecasting are 1. Times Series Model 2. Demand Planning Model 3. Predictive Analytics Models I have questions in my homeworks about these stages, but they don't call them what I was given. I have the answer choices: Judgemental, Big Data, Quantitative, and Time Series. Obviously Time Series is one, but what are the other 2 Called. I am not putting the specifics of the questions because that's not what I'm asking. I'm just hoping that someone can clarify these 3 stages for me. I realize that I listed 4 things which means that one is not a stage. I think Big Data isn't a stage, but please correct me if I'm wrong.5. Describe the process of “de-trending” in time series regression analysis. Why do weneed to “de-trend”? 6. Describe the nature of omitted variable bias as it relates to time series? In what casesdoes controlling for trend variables solve the omitted variable bias? 7. Event studies.a. Describe the six steps to conduct a financial event study.b. What is the relationship between the efficient capital market hypothesis and theuse of financial event studies for causal inference?1. How is the judgmental forecasting executed? 2. How is judgmental forecasting relevant in making decisions? 3. Differentiate Weighted Moving Average Forecast from Smoothing Forecast? 4. Relate cycles, seasonality and trends in time series forecasting. What is their relevance in such type of forecasting? 5. Illustrate one example/scenario when judgmental forecast is utilized.
- 4. Relate cycles, seasonality and trends in time series forecasting. What is their relevance in such type of forecasting? 5. Illustrate one example/scenario when judgmental forecast is utilized.Extensions Help | Arial 1 Last edit was seconds ago 11 1 + BIUA ¹2' 3 C 田 5 6 1. What are 2 examples of variables that can have a correlation to the demand/forecast of a product your company makes? 2. What does it mean when we say we use the BOM to do an MRP MacBook Pro U = = == explosion? 3. Explain what do we call "Strategic Stock". Give an example of when this could be triggered I 7 1214. A set of data with a correlation coefficient of -0.855 has a a. moderate negative linear correlation b. strong negative linear correlation c. weak negative linear correlation d. little or no linear correlation
- Which of the following approaches can help you mitigate the challenges of poor forecasts? a. Obtain and use the best, most recent information available b. Always use simple forecasting techniques c. Build flexible operations d. Minimize inventory Oe. All of the above Of. a and c'only g. b and d only5. Explain the major assumptions of the basic EOQ model.1.Why does a business cycle diagram serve as a forecasting model? 2.Name TWO coincident indicators used in forecasting.
- Suppose you regress the annual percentage stock price returns on Russell 2000 small cap index for on a the percentage annual returns for a market index. Use the following output from this linear regression to answer questions a. - f. a. What is the formula for the Russell 2000's characteristic line? b. You forecast a market return of 6% next year. According to the market model, what is next year's expected return for the Russell 2000 index? c. What is the correlation between the return on the Russell 2000 and the return on the market Index? d. How much of the variation in the Russell 2000's returns are explained by the model? e. Based on these regression results, the Russell 2000 index would be considered what kind of an investment, defensive, aggressive, or market neutral? f. Does this regression have much explanatory power? Why or why not?Which trend would you choose to forecast the 2013 value of Bob's beer can collection? Dollars Market Value of Bob's Beer Can Collection, 1989-2009 300 250 200 150 100 50 0 -50 -100 1989 1991 1993- 1995- ye-10.23x+229.84 R=0.7036 6002 2011- 2013- O Linear model is preferred. O. Neither model is appropriate. Either model works-they are equivalent. Exponential model is preferred. Dollars Market Value of Bob's Beer Can Collection, 1989-2009 300 250 200 150 100 50 0 1989 1991 1993- 1995- Y-241.72e-0083 R²=0.675 1997 1999- 2001 2003 2005 2007 6002 2011- 2013-4. Explain the difference between bias and precision in econometric analysis. As a seasoned econometrician, to which of these two attributes do you ascribe more importance?
