R语言动量和马科维茨Markowitz投资组合(Portfolio)模型实现

#*****************************************************************
# 加载历史数据
#*****************************************************************


load.packages('quantmod')


# 加载保存的原始数据
#
load('raw.Rdata')






getSymbols.extra(N8.tickers, src = 'yahoo', from = '1970-01-01', env = data, raw.data =
for(i in data$symbolnames) data[[i]] = adjustOHLC(data[[i]]

#*****************************************************************
# 运行测试，每月数据
#*****************************************************************


plot(scale.one(data$prices))

prices = data$prices


plotransition(res[[1]]['2013::'])

#*****************************************************************
# 建立基准
#*****************************************************************
models = list()


commission = list(cps = 0.01, fixed = 10.0, percentage = 0.0)


data$weight[] = NA


model = brun(data, clean.signal=T,

#*****************************************************************
#  转换为模型结果
#*****************************************************************
CLA = list(weight = res[[1]], ret = res[[2]], equity = cumprod(1 + res[[2]]), type = "weight")


obj = list(weights = list(CLA = res[[1]]), period.ends

#*****************************************************************
#进行复制
#*****************************************************************
weight.limit = data.frame(last(pric
obj = portfoli(data$prices,
periodicity = 'months', lookback.len = 12, silent=T,
const.ub = weight.limit,urns,1) + colSums(last(hist.returns,3)) +
colSums(last(hist.returns,6)) + colSums(last(hist.returns,12))) / 22
ia
},
min.risk.fns = list(
)

#*****************************************************************
# 让我们使用Pierre的平均输入假设
#*****************************************************************
obj = portfolio(data$prices,
periodicity = 'months', lookback.len = 12, si
create.ia.fn =   create.(c(1,3,6,12), 0),
min.risk.fns = list(
TRISK.AVG = target.risk.portfolio(target.r
)

#*****************************************************************
#进行回测
#*****************************************************************


plotb(models, plotX = T, log = 'y', Left

layout(1)
barplot(sapply(models, turnover, data)