Backtesting MA in R

Backtesting MA in R.r

# Step 1: Load libraries and data
library(quantmod)
library(PerformanceAnalytics)
## 
##Attaching package: 'PerformanceAnalytics'
##The following object is masked from 'package:graphics':
##legend
getSymbols('NFCI', src = 'FRED', , from = '2000-01-01')
##[1] "NFCI"
NFCI <- na.omit(lag(NFCI)) # we can only act on the signal after release, i.e. the next day
getSymbols("^GSPC", from = '2000-01-01')
##[1] "^GSPC"
data <- na.omit(merge(NFCI, GSPC)) # merge before (!) calculating returns)
data$GSPC <- na.omit(ROC(Cl(GSPC))) # calculate returns of closing prices
#Step 2: Create your indicator
data$sig <- ifelse(data$NFCI < 1, 1, 0)
data$sig <- na.locf(data$sig)
#Step 3: Use indicator to create equity curve
perf <- na.omit(merge(data$sig * data$GSPC, data$GSPC))
colnames(perf) <- c("Stress-based strategy", "SP500")
#Step 4: Evaluate strategy performance
table.DownsideRisk(perf)
table.Stats(perf)
##Stress-based strategy SP500
charts.PerformanceSummary(perf)
chart.RelativePerformance(perf[ , 1], perf[ , 2])
chart.RiskReturnScatter(perf)