data set代做、代写R程序语言、LTCRet留学生代做、代写R代写

日期：2020-01-16 10:13

#Practical Assignment #1. This assignment is worth 150 points.

#Useful hints: Utilize book examples and make sure to download

#and library appropriate packages (FRAPO, zoo, fBasics, evir)

#Under each of the items provide the relevant R code

#1) Check you working directory

getwd()

#2) Set your working directory to RStudio folder

#   that you have created inside the ANLY 515 forlder"

#3) Download the 3 data set, and lable them

#   BTC, LTC, ETH. These data sets reperesnet daily prices

#   of three chryptocurrencies: Bitcoin, Litcoin, and Ethereum.

#   Set the first column in each data set to the date format

#   and the remaining columns in numerical format.

#4) Create three new datasets that are subsets of the original

#   datasets, to include dates only after "2015-08-31".

#   Name these datasets btcnew, ltcnew, ethnew,

#5) Create 4 variables: date (represents dates of observation) ,

#   BTCPrice (price of Bitcoin), LTCPrice (Price of Litcoin),

#   ETHPrice (Price of Ethereum)

#6) Check the format of these variable by using str() command

#7) Use date variable to create attribute "time" for

#   BTCPrice, LTCPrice, and ETHPrice by using attr() function

#8) Create three variables that represent daily returns on all three coins

#   by using returnseries()(part of FRAPO package) function.

#   Call these variables BTCRet, LTCRet, and ETHRet.

#9) Use date variable to create attribute "time" for

#   BTCRet, LTCRet, and ETHRet

#10) Create a character variable CoinDates which extracts the dates

#   from the BTCRet variable by using

#   as.character(format(as.POSIXct(attr()),"%Y-%m-%d")) function

#11) Create time seriese called BTCReturns by using BTCRet varible

#   and timeSeries() function

#12) Rename the column of BTCReturns to "BTCReturns" by using colnames()

#13) Devide the output window into 2 by 2 matrix by using par() function

#14) Generate a time series plot of Daily Returns of Bitcoin

#   (requires fBasics library)

#15) Generate a box plot of Returns of Bitcoin

#16)  Generate a acf and pacf of Bitcoin Returns.

#     Make sure to omit missing values

#17)  Generate a QQ plot of Bitcoin.

#     You may have to generate a variable that omits missing values.

#     use na.omit() function

#18) Generate acf and pcf of the absolute returns of Bitcoin returns

#19) Generate Volotility Clustering Plot of absolute daily returns

# of Bitcoin

#Part II

#20)  Create new data set called PriceCoins that includes prices

#     of all three coins by using cbind()

#21)  Check the names of the colums and the format of each of the variable

#22) by using the package zoo create an element of class "zoo"

# labled PriceCoinsZoo, and includes Prices of all three Coints:

# BTCPrice", "LTCPrice", and "ETHPrice"

#23) Plot a time series graph of prices of all three coins

#24) Create a variable that calculates daily returns

#   (first difference of natural logs) on different coins.

#   Call the variable ReturnCoins by using diff(log()) function

#25) Plot a time series graph of returns of all three coins

#26)  Plot cross covariance functions between returns and between

#     absolute returns of a) BTC and LTC, BTC and ETC, and ETC and LTC.

#     You should have 6 graphs.

#27) Generate plots of rolling correlations between

#    BTC&LTC, BTC&ETH, and ETH&LTC

# Part III

# 28-30) Export all graphs to a word document and briefly analyze

#     whether data on cryptocurrency returns resembles the

#     "stylized facts" of the financial data