Portfolio backtester

require(quantmod)


############ Part 1 #############
######### Create framework for getting data #########

### Get number of securities user wants to backtest
number.of.securities <- as.numeric(readline('Enter number of securities to backtest: '))

### Get years to backtest
backtest.period <- as.numeric(readline('Enter years to backtest: '))

####### Get symbols for n number of securities

#create matrix for quotes
symbol.matrix <- matrix(ncol = number.of.securities)
symbol.weight.matrix <- matrix(ncol = number.of.securities)

#get symbols
for (i in 1:number.of.securities){
  symbol.matrix[i] <- readline('Enter symbol: ')
  symbol.weight.matrix[i] <- as.numeric(readline('Enter weight: '))
}


#use symbol.matrix to get data
#create empty variable for storing data
data.matrix <- NULL

# loop through symbol matrix and get data using getSymbols
for (i in 1:number.of.securities){
  v <- na.omit(ROC(Cl(getSymbols(symbol.matrix[i], from = Sys.Date() - (365*backtest.period), auto.assign = FALSE))))
  data.matrix <- cbind(data.matrix, v)
}


########## Part 2 ############
####### Backtest data ###########


starting.amount <- 10000

###Create starting amount for each equity

starting.equity.matrix <- matrix(ncol = number.of.securities)

for (i in 1:number.of.securities){
  starting.equity.matrix[,i] <- symbol.weight.matrix[,i] * starting.amount
}

# Calc cumsum of each security to find equity curve

equity.curve.matrix <- matrix(ncol = number.of.securities, nrow = length(data.matrix[,1]))

for (i in 1:number.of.securities){
  equity.curve.matrix[,i] <- exp(cumsum(data.matrix[,i]))
}

##### Now we have the equity curves, we can apply the starting amounts for each equity to each curve and find the gain/loss through time

equity.performance.matrix <- matrix(ncol = number.of.securities, nrow = length(data.matrix[,1]))

for (i in 1:number.of.securities){
  equity.performance.matrix[,i] <- equity.curve.matrix[,i] * starting.equity.matrix[,i]
}


### Now we need to combine the equity performance columns
total.performance <- as.matrix(rowSums(equity.performance.matrix))

# Putting the dates back on the matrix
dates <- data.matrix[,0]
total.performance <- merge(dates, total.performance)

plot(total.performance, type = 'l')