R Assignment

setwd(“C:/Users/Tam/Documents”)

Installation of Necessary Packages

install.packages(“DataExplorer”) library(DataExplorer) install.packages(“tidyverse”) library(tidyverse) install.packages(“dplyr”) library(dplyr) install.packages(“ggplot2”) library(ggplot2) install.packages(“tseries”) library(tseries) install.packages(“moments”) library(moments) install.packages(“forecast”) library(forecast) install.packages(“quantmod”) library(quantmod)

Import Data

library(readr) Data <- read.csv2(“~/Raw Data.csv”, row.names=1) View(Data)

Summary Statistics

summary(Data)

Creating Data Explorer HTML Output

?create_report ?output_format

create_report(Data, output_format = html_document(toc = TRUE, toc_depth = 6, theme = “yeti”, output_file = “report.html”, output_dir = getwd(), y = NULL, config = configure_report(), report_title = “R Assignment Report - Tamara Govender (992077)”))

output_format(knitr_options(opts_knit = NULL, opts_chunk = NULL, knit_hooks = NULL, opts_hooks = NULL, opts_template = NULL), pandoc, keep_md = FALSE, clean_supporting = TRUE, df_print = NULL, pre_knit = NULL, post_knit = NULL, pre_processor = NULL, intermediates_generator = NULL, post_processor = NULL, on_exit = NULL, base_format = NULL)

Initial Return Plots

ggplot(data = Data, aes(x=Data\(CASH_RATIO,y = Data\)TOBIN_Q_RATIO))+ geom_jitter()+ labs(x=“Liquidity”,y=“Firm Market Value”,title = “MRF JSE EQUITY: 2000-2019”, caption=“The Relationship Between Liquidity (Proxied by the Cash Ratio) and Firm Market Value”)

ggplot(data = Data, aes(x=Data\(TURNOVER,y = Data\)TOBIN_Q_RATIO))+ geom_jitter()+ labs(x=“Liquidity”,y=“Firm Market Value”,title = “MRF JSE EQUITY: 2000-2019”, caption=“The Relationship Between Liquidity (Proxied by Turnover) and Firm Market Value”)

Stationarity Testing

adf.test(Data\(CASH_RATIO) pp.test(Data\)CASH_RATIO) kpss.test(Data$CASH_RATIO)

adf.test(Data\(TOBIN_Q_RATIO) pp.test(Data\)TOBIN_Q_RATIO) kpss.test(Data$TOBIN_Q_RATIO)

adf.test(Data\(TURNOVER) pp.test(Data\)TURNOVER) kpss.test(Data$TURNOVER)

Normality Testing

skewness(Data\(CASH_RATIO) kurtosis(Data\)CASH_RATIO) jarque.bera.test(Data$CASH_RATIO)

skewness(Data\(TOBIN_Q_RATIO) kurtosis(Data\)TOBIN_Q_RATIO) jarque.bera.test(Data$TOBIN_Q_RATIO)

skewness(Data\(TURNOVER) kurtosis(Data\)TURNOVER) jarque.bera.test(Data$TURNOVER)

GARCH Testing

garch(Data\(CASH_RATIO) garch(Data\)TOBIN_Q_RATIO) garch(Data$TURNOVER)

ARMA Testing

arma(Data\(CASH_RATIO) arma(Data\)TOBIN_Q_RATIO) arma(Data$TURNOVER)

Correlation Testing

cor.test(Data\(CASH_RATIO, Data\)TOBIN_Q_RATIO, method = “pearson”) cor.test(Data\(CASH_RATIO, Data\)TOBIN_Q_RATIO, method = “spearman”) cor.test(Data\(CASH_RATIO, Data\)TOBIN_Q_RATIO, method = “kendall”)

cor.test(Data\(TURNOVER, Data\)TOBIN_Q_RATIO, method = “pearson”) cor.test(Data\(TURNOVER, Data\)TOBIN_Q_RATIO, method = “spearman”) cor.test(Data\(TURNOVER, Data\)TOBIN_Q_RATIO, method = “kendall”)

ACF and PACF Plots

acf(Data\(CASH_RATIO,plot=TRUE,main="ACF: MRF JSE EQUITY") pacf(Data\)CASH_RATIO,plot=TRUE,main=“PACF: MRF JSE EQUITY”)

acf(Data\(TURNOVER,plot=TRUE,main="ACF: MRF JSE EQUITY") pacf(Data\)TURNOVER,plot=TRUE,main=“PACF: MRF JSE EQUITY”)

acf(Data\(TOBIN_Q_RATIO,plot=TRUE,main="ACF: MRF JSE EQUITY") pacf(Data\)TOBIN_Q_RATIO,plot=TRUE,main=“PACF: MRF JSE EQUITY”)

Unit Root Circles

fitCR <- auto.arima(Data$CASH_RATIO) MyARIMATestCR <- summary(fitCR) plot(fitCR)

fitTQ <- auto.arima(Data$TOBIN_Q_RATIO) MyARIMATestTQ <- summary(fitTQ) plot(fitTQ)

fitT <- auto.arima(Data$TURNOVER) MyARIMAT <- summary(fitT) plot(fitT)

Test

startdate = as.Date(2000-01-31) enddate = as.Date(2018-12-31) getSymbols(“JSE.JO”)

chartSeries(JSE.JO)

getSymbols(“^IXIC”) chartSeries(IXIC)

getSymbols(“ZAR=X”)

summary(JSE.JO,IXIC,ZAR=X)