# required packages --------------------------------------------------
require(fImport)
require(ClustVarLV)
# --------------------------------------------------------------------
# some risky assets via ETFs
tix <- c('IWM', 'IWB', 'EFA', 'VWO', 'TLT',
'EDV', 'EMB', 'AGG', 'JNK', 'LTPZ',
'GSG', 'AMZ', 'GLD', 'VNQ', 'MNA',
'MCRO', 'QAI', 'CSLS', 'HDG', 'WDTI')
assetNames <- c('US.Large.Cap', 'US.Small.Cap', 'EAFE',
'EM.Mkts.Equity', 'US.Gov.Bonds', 'Intl.Gov.Bonds',
'EM.Mkts.Bonds', 'US.Agg.Bonds', 'US.HY.Bonds', 'US.TIPS',
'Commodities', 'MLP', 'Gold', 'REITs',
'Merger.Arb', 'Global.Macro', 'Multi-Strat',
'Equity.Long.Short', 'Hedge.Replicator', 'CTA')
# get data from yahoo finance, open-high-low-close format
ohlc <- yahooSeries(tix, from = '1900-01-01', freq = 'monthly')
# get prices from every 6th column
prices <- ohlc[, seq(6, 6*length(tix), 6)]
colnames(prices) <- assetNames
# cut to common time period and caluclate returns
ret <- returns(prices, method = 'discrete')
clv.res <- CLV(ret, method = "local", sX = FALSE, nmax = 8)
opar <- par()
par(mar = c(7.5,4.1,4.1,2.1))
plot(clv.res, type = 'dendrogram')
par(mar = opar$mar)
plot(clv.res, type = 'delta')
summary(clv.res, 4)
## $number
## clusters
## 1 2 3 4
## 12 4 3 1
##
## $groups
## $groups[[1]]
## cor in group cor next group
## Hedge.Replicator 0.94 0.33
## US.Small.Cap 0.93 0.35
## EAFE 0.93 0.37
## EM.Mkts.Equity 0.90 0.46
## US.HY.Bonds 0.88 0.54
## Global.Macro 0.88 0.47
## US.Large.Cap 0.87 0.30
## Multi-Strat 0.87 0.40
## REITs 0.77 0.13
## EM.Mkts.Bonds 0.75 0.41
## Equity.Long.Short 0.68 0.32
## Merger.Arb 0.57 0.36
##
## $groups[[2]]
## cor in group cor next group
## US.Gov.Bonds 0.98 -0.03
## Intl.Gov.Bonds 0.97 -0.04
## US.Agg.Bonds 0.83 0.21
## US.TIPS 0.80 0.26
##
## $groups[[3]]
## cor in group cor next group
## Commodities 0.84 0.46
## Gold 0.81 0.27
## CTA 0.24 -0.06
##
## $groups[[4]]
## cor in group cor next group
## MLP 1 0.25
##
##
## $set_aside
## NULL
##
## $cormatrix
## Comp1 Comp2 Comp3 Comp4
## Comp1 1.00 -0.21 0.39 0.25
## Comp2 -0.21 1.00 -0.19 -0.04
## Comp3 0.39 -0.19 1.00 -0.18
## Comp4 0.25 -0.04 -0.18 1.00
plot_var(clv.res, K = 4)
