data("cgs2022")
dca = ConnectednessApproach(cgs2022, 
                            nlag=1,
                            nfore=10,
                            window.size=250,
                            corrected=TRUE,
                            model="TVP-VAR",
                            connectedness="Time",
                            VAR_config=list(TVPVAR=list(kappa1=0.99, kappa2=0.99, prior="BayesPrior")))
## 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.
kable(dca$TABLE)
X2YCHF X5YCHF X10YCHF X2YDKK X5YDKK X10YDKK X2YEUR X5YEUR X10YEUR X2YGBP X5YGBP X10YGBP X2YNOK X5YNOK X10YNOK X2YSEK X5YSEK X10YSEK FROM
X2YCHF 16.15 11.66 8.31 4.92 5.83 4.90 5.88 6.03 5.11 3.71 4.30 4.18 1.95 2.72 2.75 3.36 4.29 3.95 83.85
X5YCHF 9.65 13.09 10.82 4.14 6.03 5.65 5.13 6.37 6.00 3.35 4.41 4.63 1.93 3.14 3.38 3.05 4.58 4.65 86.91
X10YCHF 7.16 11.36 13.81 3.73 6.06 6.35 4.55 6.36 6.72 3.07 4.53 5.13 1.82 3.20 3.71 2.80 4.59 5.05 86.19
X2YDKK 4.67 4.68 4.08 15.97 9.87 7.57 9.55 7.88 5.68 3.29 3.76 3.74 1.81 2.69 2.88 3.61 4.48 3.78 84.03
X5YDKK 4.13 5.22 5.09 7.21 11.10 8.95 7.02 9.01 7.95 3.34 4.58 5.00 1.75 3.10 3.51 3.30 4.91 4.84 88.90
X10YDKK 3.58 5.05 5.46 5.78 9.29 11.53 5.35 8.40 9.47 3.24 4.92 5.82 1.71 3.18 3.90 2.95 4.90 5.47 88.47
X2YEUR 4.86 5.17 4.45 8.33 8.31 6.06 13.62 10.04 7.09 3.91 4.36 4.29 1.85 2.71 2.84 3.61 4.54 3.96 86.38
X5YEUR 4.10 5.29 5.10 5.74 8.68 7.82 8.13 10.80 9.27 3.57 4.91 5.41 1.74 3.04 3.45 3.27 4.88 4.82 89.20
X10YEUR 3.61 5.21 5.60 4.42 7.98 9.16 6.08 9.68 11.28 3.48 5.41 6.44 1.72 3.19 3.81 2.81 4.74 5.37 88.72
X2YGBP 3.95 4.38 3.91 3.89 5.03 4.76 5.06 5.54 5.21 17.51 13.29 9.53 1.77 2.63 2.67 2.95 4.10 3.80 82.49
X5YGBP 3.68 4.61 4.57 3.62 5.54 5.80 4.56 6.18 6.54 10.46 13.73 11.64 1.64 2.87 3.17 2.75 4.26 4.39 86.27
X10YGBP 3.52 4.76 5.04 3.49 5.92 6.68 4.38 6.65 7.64 7.39 11.48 13.52 1.57 2.93 3.42 2.61 4.25 4.77 86.48
X2YNOK 2.81 3.32 3.05 2.88 3.53 3.25 3.27 3.68 3.43 2.35 2.72 2.66 23.37 16.06 10.42 4.09 4.67 4.44 76.63
X5YNOK 2.86 3.92 3.88 3.21 4.57 4.63 3.52 4.74 4.75 2.56 3.49 3.67 11.75 17.04 11.22 3.72 5.11 5.36 82.96
X10YNOK 2.90 4.20 4.46 3.34 5.22 5.68 3.67 5.34 5.73 2.56 3.84 4.28 7.16 10.74 15.70 3.64 5.46 6.09 84.30
X2YSEK 3.88 4.18 3.73 4.35 5.13 4.36 4.94 5.31 4.41 3.07 3.61 3.52 3.32 4.08 3.94 17.20 11.95 9.01 82.80
X5YSEK 3.63 4.68 4.58 4.12 5.85 5.64 4.65 6.06 5.67 3.17 4.17 4.28 2.80 4.22 4.51 8.85 12.76 10.38 87.24
X10YSEK 3.35 4.80 5.07 3.49 5.79 6.43 4.08 6.04 6.55 2.96 4.34 4.87 2.65 4.42 5.04 6.78 10.46 12.91 87.09
TO 72.33 92.49 87.20 76.67 108.62 103.68 89.81 113.31 107.22 65.48 88.11 89.09 48.95 74.92 74.62 64.16 92.17 90.12 1538.93
Inc.Own 88.48 105.58 101.01 92.64 119.72 115.20 103.43 124.11 118.49 82.98 101.84 102.61 72.32 91.95 90.32 81.37 104.93 103.02 cTCI/TCI
NET -11.52 5.58 1.01 -7.36 19.72 15.20 3.43 24.11 18.49 -17.02 1.84 2.61 -27.68 -8.05 -9.68 -18.63 4.93 3.02 90.53/85.50
NPT 5.00 13.00 9.00 6.00 16.00 14.00 12.00 17.00 15.00 2.00 7.00 11.00 0.00 3.00 4.00 1.00 10.00 8.00 
PlotTCI(dca, ylim=c(70,100))

PlotNET(dca, ylim=c(-50,50))

cc_nok = ConditionalConnectedness(dca, group=c(13,14,15))
## Conditional connectedness measures are implemented according to:
##  Chatziantoniou, I., Gabauer, D., & Stenfors, A. (2021). Independent Policy, Dependent Outcomes: A Game of Cross-Country Dominoes across European Yield Curves (No. 2021-06). University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
PlotTCI(cc_nok, ylim=c(35,100))

PlotNET(cc_nok, ylim=c(-15,15))

cc_2y = ConditionalConnectedness(dca, group=seq(1,18,3))
## Conditional connectedness measures are implemented according to:
##  Chatziantoniou, I., Gabauer, D., & Stenfors, A. (2021). Independent Policy, Dependent Outcomes: A Game of Cross-Country Dominoes across European Yield Curves (No. 2021-06). University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
kable(cc_2y$TABLE)
X2YCHF X2YDKK X2YEUR X2YGBP X2YNOK X2YSEK FROM
X2YCHF 44.80 13.73 16.35 10.36 5.48 9.29 55.20
X2YDKK 12.20 40.10 24.75 8.68 4.78 9.50 59.90
X2YEUR 13.45 23.06 37.51 10.79 5.12 10.08 62.49
X2YGBP 11.30 10.99 14.19 49.99 5.12 8.40 50.01
X2YNOK 7.43 7.69 8.71 6.24 58.98 10.94 41.02
X2YSEK 10.54 11.84 13.42 8.39 9.02 46.79 53.21
TO 54.93 67.32 77.42 44.46 29.52 48.21 321.85
Inc.Own 99.73 107.41 114.92 94.45 88.50 94.99 cTCI/TCI
NET -0.27 7.41 14.92 -5.55 -11.50 -5.01 64.37/53.64
NPT 3.00 4.00 5.00 1.00 0.00 2.00 
PlotTCI(cc_2y, ylim=c(20,100))

PlotNET(cc_2y, ylim=c(-30,30))

ca_currency = AggregatedConnectedness(dca, groups=list("CHF"=c(1,2,3), "DKK"=c(4,5,6), "EUR"=c(7,8,9), "GBP"=c(10,11,12), "NOK"=c(13,14,15), "SEK"=c(16,17,18)))
## Aggregated connectedness measures are introduced accoring to:
##  Chatziantoniou, I., Gabauer, D., & Stenfor, A. (2021). Independent Policy, Dependent Outcomes: A Game of Cross-Country Dominoes across European Yield Curves (No. 2021-06). University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
kable(ca_currency$TABLE)
CHF DKK EUR GBP NOK SEK FROM
CHF 34.01 15.87 17.38 12.43 8.21 12.10 65.99
DKK 13.98 29.09 23.44 12.56 8.18 12.75 70.91
EUR 14.47 22.16 28.66 13.93 8.11 12.67 71.34
GBP 12.80 14.91 17.25 36.18 7.56 11.30 63.82
NOK 10.47 12.10 12.71 9.37 41.15 14.19 58.85
SEK 12.63 15.05 15.90 11.33 11.66 33.43 66.57
TO 64.35 80.09 86.68 59.63 43.71 63.01 397.48
Inc.Own 98.36 109.19 115.34 95.81 84.86 96.44 cTCI/TCI
NET -1.64 9.19 15.34 -4.19 -15.14 -3.56 79.50/66.25
NPT 3.00 4.00 5.00 2.00 0.00 1.00 
PlotTCI(ca_currency, ylim=c(50,100))

PlotNET(ca_currency, ylim=c(-35,35))

ca_maturity = AggregatedConnectedness(dca, groups=list("2Y"=seq(1,18,3), "5Y"=seq(2,18,3), "10Y"=seq(3,18,3)))
## Aggregated connectedness measures are introduced accoring to:
##  Chatziantoniou, I., Gabauer, D., & Stenfor, A. (2021). Independent Policy, Dependent Outcomes: A Game of Cross-Country Dominoes across European Yield Curves (No. 2021-06). University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
print(ca_maturity$TABLE)
##         2Y       5Y       10Y      FROM         
## 2Y      "36.96"  "34.42"  "28.62"  "63.04"      
## 5Y      "27.01"  "37.82"  "35.17"  "62.18"      
## 10Y     "22.90"  "35.78"  "41.32"  "58.68"      
## TO      " 49.91" " 70.20" " 63.79" "183.90"     
## Inc.Own " 86.87" "108.02" "105.11" "cTCI/TCI"   
## NET     "-13.13" "  8.02" "  5.11" "91.95/61.30"
## NPT     "0.00"   "2.00"   "1.00"   ""
PlotTCI(ca_maturity, ylim=c(80,100))

PlotNET(ca_maturity, ylim=c(-25,25))