Question

我正在探索在＆＃39; http://www.moneycontrol.com/stocks/histstock.php?ex=N&sc_id=MU01&mycomp=Maruti%20Suzuki＆＃39;可以直接用R填充，然后直接将结果导入R工作区

感谢任何人是否有任何指针。谢谢你的时间。

Answer 1

我不确定为什么你在近一个月内没有得到任何答复。也许你需要考虑你发布的特定链接以外的选项。

library(BatchGetSymbols)

first.date <- Sys.Date()-365
last.date <- Sys.Date()

df.SP500 <- GetSP500Stocks()
tickers <- df.SP500$tickers

l.out <- BatchGetSymbols(tickers = tickers,
                         first.date = first.date,
                         last.date = last.date)

print(l.out$df.control)
print(l.out$df.tickers)

另外，您知道，您可以使用quantmod获取各种历史股票数据。

以下是一些例子。

###############################################################################
# Load Systematic Investor Toolbox (SIT)
###############################################################################
con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))
    source(con)
close(con)

    #*****************************************************************
    # Load historical data
    #****************************************************************** 
    load.packages('quantmod')

    stock.folder = 'c:\\Stocks\\Data\\'
    tickers = spl('UUP,EMB,HYG')

    data <- new.env()


    # load historical data, select data load method
    data.load.method = 'basic'

    if(data.load.method == 'basic') {       
        # quantmod - getSymbols
        getSymbols(tickers, src = 'yahoo', from = '1970-01-01', env = data, auto.assign = T)
    }else if(data.load.method == 'basic.local') {
        # if you saved yahoo historical price files localy
        getSymbols.sit(tickers, src = 'yahoo', from = '1980-01-01', env = data, auto.assign = T, stock.folder = stock.folder)
    }else if(data.load.method == 'custom.local') {
        # custom format historical price files
        for(n in tickers) {
            data[[n]] = read.xts(paste(stock.folder, n, '.csv', sep=''), format='%m/%d/%Y')
        }   
    }else if(data.load.method == 'custom.one.file') {
        # read from one csv file, column headers are tickers
        filename = 'hex.csv'
        all.data = read.xts(paste(stock.folder, filename, sep=''), format='%m/%d/%Y')
        for(n in names(all.data)) {
            data[[n]] = all.data[,n]
            colnames(data[[n]]) = 'Close'
            data[[n]]$Adjusted = data[[n]]$Open = data[[n]]$High = data[[n]]$Low = data[[n]]$Close
        }
    }       


    # prepare data for back test
        for(i in ls(data)) data[[i]] = adjustOHLC(data[[i]], use.Adjusted=T)                            
    bt.prep(data, align='remove.na')


    #*****************************************************************
    # Code Strategies
    #******************************************************************
    prices = data$prices  
    n = ncol(prices)

    models = list()

    # find period ends
    period.ends = endpoints(prices, 'months')
        period.ends = period.ends[period.ends > 0]

    obj = portfolio.allocation.helper(data$prices, period.ends=period.ends, lookback.len = 250, 
        min.risk.fns = list(EW=equal.weight.portfolio,
                        RP=risk.parity.portfolio,
                        MV=min.var.portfolio,
                        MC=min.corr.portfolio)
    ) 

    models = create.strategies(obj, data)$models

    #*****************************************************************
    # Create Report
    #******************************************************************    

    strategy.performance.snapshoot(models, T)

https://systematicinvestor.wordpress.com/2013/06/01/loading-historical-stock-data/

https://chrisconlan.com/download-daily-data-every-sp-500-stock-r/

使用r填写在线表单并下载数据

1 个答案: