Matrantuongquan

library(ConnectednessApproach)

## Warning: package 'ConnectednessApproach' was built under R version 4.3.3

## Warning in .recacheSubclasses(def@className, def, env): undefined subclass
## "ndiMatrix" of class "replValueSp"; definition not updated

## 
## Please cite as:

##  Gabauer, David (2022). ConnectednessApproach.

##  R package version 1.0.0. https://CRAN.R-project.org/package=ConnectednessApproach

library(readxl)
library(zoo)

## 
## Attaching package: 'zoo'

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

data <-  read_excel("C:/Users/Admin/Downloads/Book2.xlsx")
 
date=data$Date

df=data[,-1]
zoodata <- zoo(df,order.by = date)
nrow(zoodata)

## [1] 327

dyc <- ConnectednessApproach(zoodata, nlag=1, nfore=10, window.size=200, model="QVAR", connectedness="Time")

## Estimating model

## Computing connectedness measures

## The QVAR connectedness approach is implemented according to:
##  Chatziantoniou, I., Gabauer, D., & Stenfors, A. (2021). Interest rate swaps and the transmission mechanism of monetary policy: A quantile connectedness approach. Economics Letters, 204, 109891.

dyc$TABLE

##         OIL      VND/USD  XAUUSD   VNI      BIDV     FROM         
## OIL     "78.94"  " 4.88"  " 4.25"  " 9.60"  " 2.33"  "21.06"      
## VND/USD " 1.50"  "90.22"  " 0.12"  " 7.37"  " 0.79"  " 9.78"      
## XAUUSD  " 1.34"  " 0.56"  "83.22"  " 5.60"  " 9.28"  "16.78"      
## VNI     " 3.06"  " 7.23"  " 5.48"  "69.16"  "15.07"  "30.84"      
## BIDV    " 3.23"  " 2.68"  " 4.62"  "18.05"  "71.42"  "28.58"      
## TO      "  9.13" " 15.35" " 14.47" " 40.62" " 27.47" "107.04"     
## Inc.Own " 88.07" "105.57" " 97.69" "109.78" " 98.89" "cTCI/TCI"   
## NET     "-11.93" "  5.57" " -2.31" "  9.78" " -1.11" "26.76/21.41"
## NPT     "1.00"   "3.00"   "1.00"   "4.00"   "1.00"   ""

myzoo = na.omit(zoodata)
dyc <- ConnectednessApproach(myzoo, nlag=1, nfore=10, window.size=200, model="TVP-VAR", connectedness="Time")

## Estimating model

## Computing connectedness measures

## The TVP-VAR connectedness approach is implemented according to:
##  Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84.

ConnectednessApproach::PlotNetwork(dyc)

ConnectednessApproach::PlotFROM(dyc)

ConnectednessApproach::PlotTO(dyc)

ConnectednessApproach::PlotTCI(dyc)