## # A tibble: 384 × 5
## # Groups:   symbol [2]
##    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 374 more rows

Analyze your client’s company data. Consider the following.

timing depth *duration

“Timing” -Auto sales reflect the timing when the economy is doing well vs. not. The trend shows that during the 2007 economic crash, car sales and automotive in general fell, but comes up overtime as the market comes back up as well.

“Depth” -The market is constantly changing, and Grappone’s sales reflect how well the economy is doing, because when people have more money in their pockets they tend to spend more and purchase more expensive things.

“Duration” -The duration throughout the chart shows that when the market goes down for 1-2 years/ partial quarters, the automotive numbers also drop, while when the market came back up from the 2007-2009 period, the automotive numbers gained massively.