# Calculating Stock Returns and Portfolio Returns in R

To calculate the returns of AAPL & GOOG over the time period, you can use the Return.calculate function.

stockReturns <- Return.calculate(adjustedPrices)
## 2017-01-03            NA            NA
## 2017-01-04  -0.001119178  0.0009667604
## 2017-01-05   0.005085153  0.0090481583
## 2017-01-06   0.011148442  0.0152766979
## 2017-01-09   0.009159465  0.0006202319
## 2017-01-10   0.001008411 -0.0023058897


This will then calculate the daily returns of AAPL and GOOG over the time period. The first day, as there is nothing to divide it by, will be NA. It generally makes sense to use this code instead to diverge from that problem.

stockReturns <- Return.calculate(adjustedPrices)[-1]
## 2017-01-04  -0.001119178  0.0009667604
## 2017-01-05   0.005085153  0.0090481583
## 2017-01-06   0.011148442  0.0152766979
## 2017-01-09   0.009159465  0.0006202319
## 2017-01-10   0.001008411 -0.0023058897
## 2017-01-11   0.005373393  0.0038767816


If one wants to calculate the returns of a portfolio, one can use the Return.portfolio function with the returns of the stocks as one argument and the weights of the stocks as another. For this example, it will be an equal weight between AAPL and GOOG.

portReturns <- Return.portfolio(stockReturns, c(0.5, 0.5))
##            portfolio.returns
## 2017-01-04     -7.620906e-05
## 2017-01-05      7.068722e-03
## 2017-01-06      1.321878e-02
## 2017-01-09      4.868296e-03
## 2017-01-10     -6.500634e-04
## 2017-01-11      4.625730e-03


This does not rebalance the portfolio. To do this, just add the rebalance_on argument. In this case, it is going to be done monthly.

portReturnsRebalanced <- Return.portfolio(stockReturns, c(0.5, 0.5), rebalance_on = "months")
##            portfolio.returns
## 2017-01-04     -7.620906e-05
## 2017-01-05      7.068722e-03
## 2017-01-06      1.321878e-02
## 2017-01-09      4.868296e-03
## 2017-01-10     -6.500634e-04
## 2017-01-11      4.625730e-03


You can also get an annual table of performance using the table.AnnualizedReturns function. The arguments are an xts object of portfolio returns (can be multiple) and the risk-free rate, used to calculate the Sharpe ratio. In this example, the non-rebalanced portfolio will be compared to the monthly rebalanced portfolio.

allPortReturns <- cbind(portReturns, portReturnsRebalanced)
colnames(allPortReturns) <- c("Non-Rebalanced", "Monthly Rebalanced")
table.AnnualizedReturns(allPortReturns, Rf = 0.1/252)
##                            Non-Rebalanced Monthly Rebalanced
## Annualized Return                  0.1647             0.1769
## Annualized Std Dev                 0.2114             0.2104
## Annualized Sharpe (Rf=10%)         0.2549             0.3085