Witht the given stock, conduct the Bollinger Bands analysis by answering the questions below.
Hint: Take stock, pipe it to tidyquant::tq_mutate to calculate 20-day moving averages, pipe it to tidyquant::tq_mutate to calculate 20-day running standard deviation, pipe it to rename() to rename value to SD, and assign the result to stock. To calculate the running standard deviation, use runSD in place of SMA. You can see all the available functions in tidyquant::tq_mutate using tq_mutate_fun_options().
Hint: Take stock, pipe it to mutate(sd2up = SMA + 2 * SD, sd2down = SMA - 2 * SD), and assign the result to stock.
Hint: Take stock, pipe it to dplyr::select to keep date, close, SMA, sd2up, and sd2down, and assign the result to stock_selected.
Hint: Take stock_selected, pipe it to gather(key = type, value = price, close:sd2down), and assign the result to stock_long.
Hint: Take stock_selected and pipe it to ggplot(). Map date to the x-axis, price to the y-axis, and type to color in the line chart.
## Warning: Removed 57 row(s) containing missing values (geom_path).
Hint: A correct answer must show the per-share profit each scenario, the difference between the buying price and the selling price.
Scenario 2 would yield a much larger profit. Scenario one would yield 29% while scenario 2 would yield 55%. This is due to the higher selling price with the upper band being 2.5 sd. With this higher selling price you still have the same buying price.
Hint: Use message
, echo
and results
in the chunk options. Refer to the RMarkdown Reference Guide.