## # 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
Analyze your client company’s data. Consider the following:
of downturns in sale.
timing The sales may lead or coincides with the overall economy.
depth The Bank of New Hampshire sale is hugely volatile relative to the overall economy.
duration The downturn in sales spikes tremendously throughout various different quarters throughout the many years.