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You need to assign each of the target variables to their own column and then train a model for each of your forecast horizons library(quantmod) symbol= getSymbols("AAPL",from="2010-03-01", auto.assign=F) close<-Cl(symbol) open<-Op(symbol) lc1<-lag(close) lc2<-lag(close,2) lc3<-lag(close,3) lo1<-lag(open) lo2<-lag(open,2) ...


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Recently I attended a presentation by the first author of the following paper who gave us quite a creative and illuminating (kind of meta-)use of random forests in Quant Finance: All that Glitters Is Not Gold: Comparing Backtest and Out-of-Sample Performance on a Large Cohort of Trading Algorithms (March 2016) by Thomas Wiecki, Andrew Campbell, Justin Lent, ...



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