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14 сентября 2019
Seasonality, visualization, and logistic regression (Programming language R)
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Instructions
Next we will construct some needed measures. For this assignment, we will work using first differences, i.e., \(revenue_t - revenue_{t-1}\). We will need to construct the first difference between the current quarter and the next, as well as
the four differences prior. We will also compare revenue by quarter, and thus calculating the lag of revenue will be useful. Thus, we will construct the following six measures:
revtq_lag = last quarter revenue
diff_lead = next quarter revenue - current quarter revenue
diff1 = current quarter revenue - last quarter revenue
diff2 = last quarter revenue - 2 quarters ago revenue
diff3 = 2 quarters ago revenue - 3 quarters ago revenue
diff4 = 3 quarters ago revenue - 4 quarters ago revenue
Also useful will be actual year and quarter for the data, as most retailers do not have calendar aligned fiscal years in Singapore. This has been coded for you.
Then, plot out current revenue vs last quarter revenue such that we can easily distinguish colors by quarter. What insights do we see from the graph? How does this compare with what we saw about US retail firms in session 4?
Exercise 2
Construct the 6 measures specified above.55 You should use mutate() and group_by() for these measures. To identify specific companies, you can use either gvkey or their names.
# Set eval=TRUE after writing your code
# Place your code for Exercise 2 in this code block
# Construct the five measures listed in the instructions, storing them in the
# specified names. Make sure to add these into df.
# Other useful measures: actual year and quarter -- these are done for you
df$year
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Автор24
Автор24
20 дней
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15 сентября 2019
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Seasonality, visualization, and logistic regression (Programming language R).jpg
2019-09-18 14:49
Последний отзыв студента о бирже Автор24
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В сроки автор уложился, работу зачли. Правда пояснительную записку оформил я сам. Не дорого и хорошо - можно смело рекомендовать автора
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