## # A tibble: 548 Ă— 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 rowsAnalyze Comptus data. Consider the following: timing depth *duration
of downturn in sales.
Timing Despite being rather independent of the economy Huge economic downturns and upturns do affect their growth dramatically. They can fall way down very quickly in a very large downturn and then skyrocket back up the next time a huge positive surge hits the economy.
Depth Comptus seems to be rather independent of the economy. Probably because it’s less of individual sales and more sales to big businesses. Companies always need manufactured industrial esq goods. Note that only in a very large economic downturn and upturns does the economy really effect their growth.
Duration When affected by the substantial economic changes I mentioned earlier the downturn or upturn in sales tends to last as long as the upturn or downturn in the economy with which it started.