Retrieve the following data by revising the given code below.

Q1. Netflix for the period of 2014-01-01 - 2017-12-31 from Yahoo

# Load packages
library(quantmod)

data <- getSymbols("NFLX",from ="2014-01-01",to="2017-12-31", src = "yahoo", auto.assign = FALSE)

head(data)
##            NFLX.Open NFLX.High NFLX.Low NFLX.Close NFLX.Volume
## 2014-01-02  52.40143  52.51143 51.54286   51.83143    12325600
## 2014-01-03  52.00000  52.49572 51.84286   51.87143    10817100
## 2014-01-06  51.89000  52.04429 50.47572   51.36714    15501500
## 2014-01-07  49.68428  49.69857 48.15286   48.50000    36167600
## 2014-01-08  48.10429  49.42571 48.07429   48.71286    20001100
## 2014-01-09  48.82429  49.14000 47.85714   48.15000    17007200
##            NFLX.Adjusted
## 2014-01-02      51.83143
## 2014-01-03      51.87143
## 2014-01-06      51.36714
## 2014-01-07      48.50000
## 2014-01-08      48.71286
## 2014-01-09      48.15000
plot(data)

Q2. US unemployment rate (monthly seasonally adjusted) from FRED

data <- getSymbols("UNRATE", src = "FRED", auto.assign = FALSE)

head(data)
##            UNRATE
## 1948-01-01    3.4
## 1948-02-01    3.8
## 1948-03-01    4.0
## 1948-04-01    3.9
## 1948-05-01    3.5
## 1948-06-01    3.6
plot(data)

Q3. Foreign exchange rate, Korean won per US dollar from Oanda.com (Hint: Oanda.com only reports data for the past 180 days)

data <- getSymbols("KRW/USD", src = "oanda", auto.assign = FALSE)

head(data)
##             KRW.USD
## 2018-04-06 0.000936
## 2018-04-07 0.000934
## 2018-04-08 0.000934
## 2018-04-09 0.000936
## 2018-04-10 0.000938
## 2018-04-11 0.000938
plot(data)

Q4. You are interested in studying stock price changes (without dividend payments) of three tech giants - Microsoft, Apple, and Amazon for the period of 2014-01-01 - 2017-12-31. Load three stocks; extract the Close column from each of the three stocks; and merge them into one object.

# Create a new environment
data_env <- new.env()
getSymbols(c("MSFT", "AAPL","AMZN"),from= "2014-01-01",to="2017-12-31", env = data_env, auto.assign = TRUE)
## [1] "MSFT" "AAPL" "AMZN"
adjusted_list <- lapply(data_env, Cl)
adjusted <- do.call(merge, adjusted_list)

head(adjusted)
##            AAPL.Close AMZN.Close MSFT.Close
## 2014-01-02   79.01857     397.97      37.16
## 2014-01-03   77.28286     396.44      36.91
## 2014-01-06   77.70428     393.63      36.13
## 2014-01-07   77.14857     398.03      36.41
## 2014-01-08   77.63715     401.92      35.76
## 2014-01-09   76.64571     401.01      35.53
plot(adjusted)