## # A tibble: 548 × 5
## # Groups: symbol [4]
## symbol date price change text
## <chr> <date> <dbl> <dbl> <glue>
## 1 GDPC1 1947-01-01 2034. NA 1947.1,
## Growth: NA
## 2 GDPC1 1947-04-01 2029. -0.00267 1947.2,
## Growth: -0.3%
## 3 GDPC1 1947-07-01 2025. -0.00207 1947.3,
## Growth: -0.2%
## 4 GDPC1 1947-10-01 2057. 0.0156 1947.4,
## Growth: 1.6%
## 5 GDPC1 1948-01-01 2087. 0.0150 1948.1,
## Growth: 1.5%
## 6 GDPC1 1948-04-01 2122. 0.0165 1948.2,
## Growth: 1.7%
## 7 GDPC1 1948-07-01 2134. 0.00573 1948.3,
## Growth: 0.6%
## 8 GDPC1 1948-10-01 2136. 0.00112 1948.4,
## Growth: 0.1%
## 9 GDPC1 1949-01-01 2107. -0.0138 1949.1,
## Growth: -1.4%
## 10 GDPC1 1949-04-01 2100. -0.00341 1949.2,
## Growth: -0.3%
## # … with 538 more rows
Anaylyze your client company’s data. Consider the following:
Timing Depth Duration
of down turn in sales
Timing: The sales decline began in 2008, you can see where the sales go below 0. This was the same time that the economy declined.
Depth: GDP declined 2.2% while the industry dropped about 12% in sales. You can see that the industry is extremely sensitive to the overall economy.
Duration: The recession lasted just over a year from February 2008 to March 2009. The industry dropped in January 2008 and recovered in around January 2009. You can see that the recession was slightly longer and the industry sale is slightly shorter.