1 Import stock prices of your choice

I chose AAPL, GOOG, and NFLX.

## # A tibble: 558 × 8
##    symbol date        open  high   low close   volume adjusted
##    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
##  1 AAPL   2026-01-02  272.  278.  269   271. 37838100     270.
##  2 AAPL   2026-01-05  271.  272.  266.  267. 45647200     267.
##  3 AAPL   2026-01-06  267   268.  262.  262. 52352100     262.
##  4 AAPL   2026-01-07  263.  264.  260.  260. 48309800     260.
##  5 AAPL   2026-01-08  257.  259.  256.  259. 50419300     258.
##  6 AAPL   2026-01-09  259.  260.  256.  259. 39997000     259.
##  7 AAPL   2026-01-12  259.  261.  257.  260. 45263800     260.
##  8 AAPL   2026-01-13  259.  262.  258.  261. 45730800     260.
##  9 AAPL   2026-01-14  259.  262.  257.  260. 40019400     259.
## 10 AAPL   2026-01-15  261.  261.  257.  258. 39388600     258.
## # ℹ 548 more rows

2 Convert prices to returns by quarterly

## # A tibble: 9 × 3
##   asset date       returns
##   <chr> <date>       <dbl>
## 1 AAPL  2026-03-31 -0.0647
## 2 AAPL  2026-06-30  0.132 
## 3 AAPL  2026-09-29  0.130 
## 4 GOOG  2026-03-31 -0.0939
## 5 GOOG  2026-06-30  0.209 
## 6 GOOG  2026-09-29 -0.0457
## 7 NFLX  2026-03-31  0.0552
## 8 NFLX  2026-06-30 -0.298 
## 9 NFLX  2026-09-29 -0.0155

3 Make plot

4 Interpret the plot

AAPL Low end of distributions = ~-20% Upper end of distributions = ~20% Typical Return = ~13%

GOOG Low end of distributions = ~-25% Upper end of distributions = ~20% Typical Return = ~-6%

NFLX Low end of distributions = ~-30% Upper end of distributions = ~20% Typical Return = ~3%

5 Change the global chunk options

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