Week 6 Discussion

#Libraries

library(quantmod)

## Warning: package 'quantmod' was built under R version 4.0.3

## Loading required package: xts

## Warning: package 'xts' was built under R version 4.0.3

## Loading required package: zoo

## Warning: package 'zoo' was built under R version 4.0.3

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

## Loading required package: TTR

## Warning: package 'TTR' was built under R version 4.0.3

## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo

## Version 0.4-0 included new data defaults. See ?getSymbols.

library(fpp2)

## Warning: package 'fpp2' was built under R version 4.0.3

## -- Attaching packages --------------------------------------------------------------------------------- fpp2 2.4 --

## v ggplot2   3.3.2     v fma       2.4  
## v forecast  8.13      v expsmooth 2.3

## Warning: package 'forecast' was built under R version 4.0.3

## Warning: package 'fma' was built under R version 4.0.3

## Warning: package 'expsmooth' was built under R version 4.0.3

## 

library(vars)

## Warning: package 'vars' was built under R version 4.0.3

## Loading required package: MASS

## 
## Attaching package: 'MASS'

## The following objects are masked from 'package:fma':
## 
##     cement, housing, petrol

## Loading required package: strucchange

## Warning: package 'strucchange' was built under R version 4.0.3

## Loading required package: sandwich

## Warning: package 'sandwich' was built under R version 4.0.3

## Loading required package: urca

## Warning: package 'urca' was built under R version 4.0.3

## Loading required package: lmtest

## Warning: package 'lmtest' was built under R version 4.0.3

#Download data #Using JP Morgan and Bank Of America, as they should be relatively correlated. They are in the same industry and subject to roughly similar regulatory changes

tickers=c("BAC","JPM")

getSymbols(tickers,return.class="ts",from="2015-01-01",to="2020-11-01",auto.assign = TRUE, periodicity="monthly")

## 'getSymbols' currently uses auto.assign=TRUE by default, but will
## use auto.assign=FALSE in 0.5-0. You will still be able to use
## 'loadSymbols' to automatically load data. getOption("getSymbols.env")
## and getOption("getSymbols.auto.assign") will still be checked for
## alternate defaults.
## 
## This message is shown once per session and may be disabled by setting 
## options("getSymbols.warning4.0"=FALSE). See ?getSymbols for details.

## [1] "BAC" "JPM"

#Plot time series

#Bank variables

BAC_ts=BAC[,6]
JPM_ts=JPM[,6]

autoplot(BAC_ts)+
  autolayer(JPM_ts)

#Data isnt stationary so we should take differences

#differences
BAC_ts.diff = diff(BAC_ts)
JPM_ts.diff = diff(JPM_ts)

#these look reasonably correlated
autoplot(BAC_ts.diff)

autoplot(JPM_ts.diff)

plot(BAC_ts, JPM_ts)

#Check Autocorrelations #Autocorrelations look good to me, we are set to run VAR model

ggAcf(BAC_ts.diff)

ggPacf(BAC_ts.diff)

ggAcf(JPM_ts.diff)

ggPacf(JPM_ts.diff)

#Selecting a model

combined.data=cbind(BAC=BAC_ts.diff,JPM=JPM_ts.diff)


VARselect(combined.data[,1:2], lag.max=8,
  type="const")[["selection"]]

## AIC(n)  HQ(n)  SC(n) FPE(n) 
##      1      1      1      1

var1 <- VAR(combined.data, p=1, type="const")
serial.test(var1, lags.pt=8, type="PT.asymptotic")

## 
##  Portmanteau Test (asymptotic)
## 
## data:  Residuals of VAR object var1
## Chi-squared = 21.862, df = 28, p-value = 0.7876

fcst.1 = forecast(var1)
autoplot(fcst.1)