1 Import stock prices of your choice

2 Convert prices to returns by quarterly

## # A tibble: 100 × 3
##    asset date       returns
##    <chr> <date>       <dbl>
##  1 TSLA  2012-03-30  0.282 
##  2 TSLA  2012-06-29 -0.174 
##  3 TSLA  2012-09-28 -0.0664
##  4 TSLA  2012-12-31  0.146 
##  5 TSLA  2013-03-28  0.112 
##  6 TSLA  2013-06-28  1.04  
##  7 TSLA  2013-09-30  0.588 
##  8 TSLA  2013-12-31 -0.251 
##  9 TSLA  2014-03-31  0.326 
## 10 TSLA  2014-06-30  0.141 
## # … with 90 more rows

3 Make plot

## $y
## [1] "Frequency"
## 
## $x
## [1] "Rate of Return"
## 
## $title
## [1] "Distribution of Quarterly Returns, 2012-2016"
## 
## $caption
## [1] "A typical monthly return is higher for GM than F, HMC, TSLA, and VWAGY."
## 
## attr(,"class")
## [1] "labels"

4 Interpret the plot

Previous returns are shown in the chart. The typical return you should expect in a typical period for Ford is just above 0. It is a bell shape so it is rather predictablee. GM is bimodel so it is almost the same to profit as it is to lose. HMC has a frequency of 1 for all its returns except one which has a freguency of 2 at just below 0, so it is not as predictable as F. TSLA has a typical return of under 0. But if you are risk loving, there was one quarter where the return was 100%. VWAGY is similar to HMC, where most of it's returns only happened once, except for two which happened for 4 quarters and was less than 0. I would recommend going with Ford if you want to play it safe.

5 Change the global chunck options

Hide the code, messages, and warnings