# Do we need to lag values for backtesting?

I am using R moving average crossover backtest script from eickonomics. But I have a question about this section.

#Calculate the moving averages and lag them one day to prevent lookback bias
PreviousSMA_50 <- lag(SMA(Cl(data[['SPY']]),50))
PreviousSMA_200 <- lag(SMA(Cl(data[['SPY']]),200))
.
.
data$weight[] = ifelse(as.integer(PreviousSMA_50>PreviousSMA_200)==1,1,0) #If price of SPY is above the SMA then buy  Why does the author need to lag the SMA values? Why can't he simply use unlagged values? PreviousSMA_50 <- SMA(Cl(data[['SPY']]),50) PreviousSMA_200 <- SMA(Cl(data[['SPY']]),200) . . data$weight[] = ifelse(as.integer(PreviousSMA_50>PreviousSMA_200)==1,1,0)


Why would we use previous SMA value instead of current SMA value? How does it cause lookahead bias?

If we need other indicators do we have to lag those values as well?

rsi<-RSI(Cl(data[['SPY']]),50)
roc<-ROC(Cl(data[['SPY']]),50)


• so is this logic wrong PreviousSMA_50 <- SMA(Cl(data[['SPY']]),50)..... data\$weight[] = ifelse(as.integer(Cl(data[['SPY']])>PreviousSMA_50)==1,1,0) I have used this in my backtest so this backtest result are wrong? – Eka Sep 3 '16 at 12:38