In mdavis29/stockFunctions: Tools for xts Stock Tickers

The following is a guide to stockTools

Load the symbol list and get the historical data, load to enviroment e

data("sp500Symbols")
## build new data
e<-new.env()
failList <- getHistoricalStocks(sp500Symbols, e)
stockDataEnv<-e
save(stockDataEnv, file = 'stockDataEnv.rda')

Build a Data Frame From Stock Ticker Data

Load pre downloaded data from and enviroment, saved as an rda file set the dependent and class variables. This uses the buildStockdatasetfromEnv function to take all stocks in the enviroment, and turn them into a data data frame suitable for modeling

load('stockDataEnv.rda')
rd<-na.buildStockDataSetFromEnv(stockDataEnv)
## get Varible Names
classCol<- "tradeFlag" 
predVars<-colnames(rd)[!colnames(rd) %in% c( "time","tradeInd","stockName",classCol)]
dim(rd)

Load a pre trained cluster model for the data and use cluster prediction as features for the rd data frame

load('clusterFit.rda') ## loads as cluster fit
rd.clean<-na.omit(rd)
km.df<-predictKmeans(clusterFit, rd.clean)

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mdavis29/stockFunctions documentation built on May 22, 2019, 3:22 p.m.