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 RBBN  2018-03-29 -0.417 
##  2 RBBN  2018-06-29  0.334 
##  3 RBBN  2018-09-28 -0.0416
##  4 RBBN  2018-12-31 -0.349 
##  5 RBBN  2019-03-29  0.0662
##  6 RBBN  2019-06-28 -0.0518
##  7 RBBN  2019-09-30  0.178 
##  8 RBBN  2019-12-31 -0.633 
##  9 RBBN  2020-03-31 -0.0228
## 10 RBBN  2020-06-30  0.260 
## # … with 90 more rows

3 Make plot

4 Interpret the plot

When comparing the quarterly returns for the given assets, (COST, DIS, PFE, RBBN, TSLA), it can be seen that these stock returns are somewhat volitile. In a span of only five years, the sample illustartes the nature of these stocks and how an investor can expect their investments to perform under normal conditions. As seen with COST, DIS, and PFE, there is a high concentration of plots at or around zero, indicating that these assets should normally be expected to produce a return from -0.1% to 0.2% during any given quarter. While these stocks may be more risk-adverse, they will likely generate low rates of return in the long-run. That being said, COST appears to have more plots above 0, which could be an indication that the stock will continue to positively perform each quarter. On the other hand, RBBN and TSLA show a much a wider distribution of plots. These two stocks are different because they are more volitile in nature. RBBN and TSLA may be able to capture higher returns during some periods, but during others they will fall victim to much lower returns as well. An investor would need to be mindful when making an investment that has a wide distribution of returns, because there would be an inhertently higher probability of either losses or gains.

5 Change the global chunck options

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