## # 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’s company data. Consider the following:

Timing depth *duration

of downturns in sale.

Grappone

timing The sales may lead or coincide with the overall economy. depth The Grappone’s sale is hugely volatile relative to the overall economy.

Duration The downturn in sales is not as long as one in the overall economy based on looking at data from the Great Recession.