C20: Data set for testing marima package (Copenhagen Stocks)

In marima: Multivariate ARIMA and ARIMA-X Analysis

Description

Two years of prices for 18 shares from the Copenhagen Stock Exchange C20 index, covering the most valuable companies. Two shares have been removed (Maersk A = almost identical to Maersk B) and ISS which is incomplete for the period considered.

Usage

data(C20)

Format

A data frame (C20) with 1+18+18 columns and 517 rows (about two full years).

Dates

Format for date is 2016-04-01

CARL.fin

Closing price for stock 'Carlsberg' .

CHR..fin

Closing price for stock 'Christian Hansen' .

COLO.fin

Closing price for stock 'Coloplast' .

DANS.fin

Closing price for stock 'Danske Bank' .

DSV..fin

Closing price for stock 'DSV' .

GEN..fin

Closing price for stock 'Genmap' .

GN.2.fin

Closing price for stock 'GN St. Nord' .

FLS..fin

Closing price for stock 'FL Smidth' .

JYSK.fin

Closing price for stock 'Jyske Bank' .

MAER.fin

Closing price for stock 'Maersk B' .

NDA..fin

Closing price for stock 'Nordea Bank' .

NOVO.fin

Closing price for stock 'Novo' .

NZYM.fin

Closing price for stock 'Novozymes' .

PNDO.fin

Closing price for stock 'Pandora' .

TDC..fin

Closing price for stock 'TDC' .

TRYG.fin

Closing price for stock Pandora' .

VWS..fin

Closing price for stock 'Vestas Wind' .

WDH..fin

Closing price for stock 'Wiliam Demant' .

CARL.ave

Average price for stock 'Carlsberg' .

CHR..ave

Average price for stock 'Christian Hansen' .

COLO.ave

Average price for stock 'Coloplast' .

DANS.ave

Average price for stock 'Danske Bank' .

DSV..ave

Average price for stock 'DSV' .

GEN..ave

Average price for stock 'Genmap' .

GN.2.ave

Average price for stock 'GN St. Nord' .

FLS..ave

Average price for stock 'FL Smidth' .

JYSK.ave

Average price for stock 'Jyske Bank' .

MAER.ave

Average price for stock 'Maersk B' .

NDA..ave

Average price for stock 'Nordea Bank' .

NOVO.ave

Average price for stock 'Novo' .

NZYM.ave

Average price for stock 'Novozymes' .

PNDO.ave

Average price for stock Pandora' .

TDC..ave

Average price for stock 'TDC' .

TRYG.ave

Average price for stock 'Pandora' .

VWS..ave

Average price for stock 'Vestas Wind' .

WDH..ave

Average price for stock 'William Demant' .

Examples

# Example 1:

library(marima)
data(C20)

selects <- c(2,7,11)

cat("Multivariate model for ",colnames(C20)[selects]," \n")

Data <- data.frame(C20[,selects])
colnames(Data) <- colnames(C20)[selects]

log.Data <- log(Data)
kvar <- length(selects)
k    <- c(1:kvar)
difs <- rep(1,length(selects))

difference <- rbind(k , difs)

dlog.Data <- 100*t(define.dif(log.Data,difference)$y.dif)

cat("dlog.Data represents the percentage change from day
to day. \n")

mod <- define.model(kvar = kvar, ar=c(1:2),ma=c(1))

Model <- marima(dlog.Data,
   ar.pattern=mod$ar.pattern, ma.pattern=mod$ma.pattern,penalty=2)

short.form(Model$ar.estimates,leading=FALSE)
short.form(Model$ma.estimates,leading=FALSE)

# Example 2:
library(marima)
data(C20)

selects <- c(13)

cat("Univariate model for ",colnames(C20)[selects]," \n")

Data <- data.frame(C20[,selects])
colnames(Data) <- colnames(C20)[selects]

log.Data <- log(Data)
kvar <- length(selects)
k    <- c(1:kvar)
difs <- rep(1,length(selects))

difference <- rbind(k , difs)

dlog.Data <- 100*t(define.dif(log.Data,difference)$y.dif)

mod <- define.model(kvar = kvar, ar=c(1:2),ma=c(1))

Model <- marima(dlog.Data,
   ar.pattern=mod$ar.pattern, ma.pattern=mod$ma.pattern,penalty=2)

short.form(Model$ar.estimates,leading=FALSE)
short.form(Model$ma.estimates,leading=FALSE)

marima documentation built on May 2, 2019, 2:10 p.m.