With the given stock, conduct the Bollinger Bands analysis by answering the questions below.

Q1 Calculate 20-day moving averages and 20-day running standard deviation. Save the result under stock and print it.

Q2 Calculate the Bollinger Bands. Save the result under stock and print it.

Hint: Take stock, pipe it to mutate(sd2up = SMA + 2 * SD, sd2down = SMA - 2 * SD), and assign the result to stock.

Q3 Select variables to build the Bollinger Bands. Save the result under stock_selected and print it.

Hint: Take stock, pipe it to dplyr::select to keep date, close, SMA, sd2up, and sd2down, and assign the result to stock_selected.

Q4 Transform data to long form from wide form for graphing.Save the result under stock_long and print it.

Hint: Take stock_selected, pipe it to gather(key = type, value = price, close:sd2down), and assign the result to stock_long.

Q5 Visualize data.

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).

Q6 If you had invested $1 million on the day of the first buying point and sold all the shares on the following selling point, how much would you have won or lost?

2020-02-27 158.18 2020-06-08 188.36

On February 27, 2020, I would have bought 6321 shares with $1 million, at the price of $158.18 per share. I would have made over $190 000 by selling the shares on June 8, 2020 at a price of $188.36 per share.

Q7 An analyst may tinker with the width of the Bollinger Bands depending the volatility of the stock. Which of the following scenarios would have yield the largest profit? Elaborate your answer.

Hint: A correct answer must show the per-share profit each scenario, the difference between the buying price and the selling price.

  1. the upper band being 2 sd up from the average and the lower band 2 sd below (standard)

Buying price: 2020-02-27 at 158.18; Selling price: 2020-06-08 at 188.36; –Per share profit: 30.18

  1. the upper band being 2.5 sd up from the average and the lower band 2 sd below

Buying price: 2020-02-27 at 158.18; Selling price: 2020-06-10 at 196.84; –Per share profit: 38.66

The second scenario will yield more profit, where the Bollinger Band is wider. If the upper Bollinger Band is 2.5 instead of 2, R is finding a higher buying price when filtering for a day when the closing goes higher than the high band, at 2.5 standard deviations. The closing price will be lower at 2 standard deviations because the range is lower.

Q8 Hide the messages, the code, and its results on the webpage.

Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.

Q9 Display the title and your name correctly at the top of the webpage.

Q10 Use the correct slug.