\documentclass{article}
\usepackage{amsmath}
\usepackage{verbatim}
\usepackage{Rd}
%\VignetteIndexEntry{Portfolio Returns}
%\VignetteDepends{PerformanceAnalytics}
%\VignetteKeywords{returns, performance, portfolio}
%\VignettePackage{PerformanceAnalytics}

\begin{document}
\SweaveOpts{concordance=TRUE}

\begin{abstract}
This vignette provides an overview of calculating portfolio returns through time with an emphasis on the math used to develop the \verb"Return.portfolio" function in \pkg{PerformanceAnalytics}. We first introduce some basic definitions, then give simple examples of computing portfolio returns in a prices and shares framework as well as a returns and weights framework. We then introduce \verb"Return.portfolio" and demonstrate the function with a few examples.
\end{abstract}

\tableofcontents

\section{Basic definitions}

Suppose we have a portfolio of $N$ assets. The value of asset $i$, $V_i$, in the portfolio is defined as
\begin{eqnarray*}
V_i = \lambda_i * P_i
\end{eqnarray*}

where:
\begin{eqnarray*}
\lambda_i \text{ is the number of shares of asset $i$}\\
P_i \text{ is the price of asset $i$}\\
\end{eqnarray*}

The total portfolio value, $V_p$, is defined as
\begin{eqnarray*}
V_P = \sum_{i=1}^N V_i
\end{eqnarray*}

The weight of asset $i$, $w_i$, in the portfolio is defined as
\begin{eqnarray*}
w_i = V_i / V_P
\end{eqnarray*}

where:
\begin{eqnarray*}
V_i \text{ is the value of asset $i$}\\
V_P \text{ is the total value of the portfolio}\\
\end{eqnarray*}

The portfolio return at time $t$, $R_t$, is defined as
\begin{eqnarray*}
R_t = \frac{V_{p_{t}} - V_{p_{{t-1}}}}{V_{p_{{t-1}}}}
\end{eqnarray*}

\begin{eqnarray*}
V_{p_{t}} \text{ is the portfolio value at time $t$}\\
\end{eqnarray*}

\section{Simple Example: Prices and Shares Framework}
Suppose we have a portfolio of $N = 2$ assets, asset A and asset B. The prices for assets A and B are given as

<<>>=
prices = cbind(c(5, 7, 6, 7),
                c(10, 11, 12, 8))
dimnames(prices) = list(paste0("t",0:3), c("A", "B"))
prices
@


We wish to form an equal weight portfolio, that is, form a portfolio where
\begin{equation*}
w_i = \frac{1}{N} \text{ for } i \in 1, \hdots, N.
\end{equation*}

Let $V_{P0} = 1000$ be the portfolio value at $t_0$.

Step 1: Compute the number of shares of each asset to purchase.
\begin{eqnarray*}
w_i &=& \frac{V_i}{V_P}\\
&=& \frac{\lambda_i * P_i}{V_P}\\
\end{eqnarray*}

Solve for $\lambda_i$.
\begin{eqnarray*}
\lambda_i &=& \frac{w_i * V_P}{P_i}
\end{eqnarray*}

\begin{eqnarray*}
\lambda_A &=& \frac{w_A * V_P0}{P_A} = \frac{0.5 * \$1000}{\$5} = 100\\
\lambda_B &=& \frac{w_B * V_P0}{P_B} = \frac{0.5 * \$1000}{\$10} = 50\\
\end{eqnarray*}

<<>>=
V_P0 = 1000
N = ncol(prices)
w = rep(1 / N, N)
lambda = w * V_P0 / prices["t0",]
lambda
@


Step 2: Compute the asset value and portfolio value for $t \in 0, \hdots, 3$.
<<>>=
# Compute the value of the assets
V_assets <- matrix(0, nrow(prices), ncol(prices), dimnames=dimnames(prices))
for(i in 1:nrow(prices)){
  V_assets[i,] = prices[i,] * lambda
}
V_assets
@

<<>>=
# Compute the value of the portfolio
V_P = rowSums(V_assets)
V_P
@


Step 3: Compute the portfolio returns for $t \in 1, \hdots, 3$.
<<>>=
# Compute the portfolio returns
R_t = diff(V_P) / V_P[1:3]
R_t
@


Step 4: Compute the weights of each asset in the portfolio for $t \in 0, \hdots, 3$
<<>>=
weights = V_assets / V_P
weights
@

We have shown that calculating portfolio weights, values, and returns is simple in a prices and shares framework. However, calculating these metrics becomes more challenging in a weights and returns framework.

\section{Example: Weights and Returns Framework}

We will use the monthly returns during 1997 of the first 5 assets in the edhec dataset for the following example.
<<>>=
library(PerformanceAnalytics)
data(edhec)
R = edhec["1997", 1:5]
colnames(R) = c("CA", "CTAG", "DS", "EM", "EMN")
R
@

Suppose that on 1996-12-31 we wish to form an equal weight portfolio such that the weight for asset $i$ is given as:

\begin{equation*}
w_i = \frac{1}{N} \quad \text{for } i \in 1, \hdots, N
\end{equation*}

where $N$ is equal to the number of assets.

<<>>=
N = ncol(R)
weights = xts(matrix(rep(1 / N, N), 1), as.Date("1996-12-31"))
colnames(weights) = colnames(R)
weights
@

There are two cases we need to consider when calculating the beginning of period (bop) value.

Case 1: The beginning of period $t$ is a rebalancing event. For example, the rebalance weights at the end of \verb"1996-12-31" take effect at the beginning of \verb"1997-01-31". This means that the beginning of \verb"1997-01-31" is considered a rebalance event.

The beginning of period value for asset $i$ at time $t$ is given as
\begin{equation*}
V_{{bop}_{t,i}} = w_i * V_{t-1}
\end{equation*}

where $w_i$ is the weight of asset $i$ and $V_{t-1}$ is the end of period (eop) portfolio value of the prior period.

Case 2: The beginning of period $t$ is not a rebalancing event.
\begin{equation*}
V_{{bop}_{t,i}} = V_{{eop}_{t-1,i}}
\end{equation*}

where $V_{{eop}_{t-1,i}}$ is the end of period value for asset $i$ from the prior period.

The end of period value for asset $i$ at time $t$ is given as
\begin{equation*}
V_{{eop}_{t,i}} = (1 + R_{t,i}) * V_{{bop}_{t,i}}
\end{equation*}

Here we demonstrate this and compute values for the periods 1 and 2. For the first period, $t=1$, we need an initial value for the portfolio value. Let $V_0 = 1$ denote the initial portfolio value. Note that the initial portfolio value can be any arbitrary number. Here we use $V_0 = 1$ for simplicity.

<<>>=
V_0 = 1
bop_value = eop_value = matrix(0, 2, ncol(R))
@

Compute the values for $t=1$.
<<>>=
t = 1
bop_value[t,] = coredata(weights) * V_0
eop_value[t,] = coredata(1 + R[t,]) * bop_value[t,]
@

Now compute the values for $t=2$.
<<>>=
t = 2
bop_value[t,] = eop_value[t-1,]
eop_value[t,] = coredata(1 + R[t,]) * bop_value[t,]
@

It is seen that the values for the rest of the time periods can be computed by iterating over $ t \in 1, \hdots, T$ where $T=12$ in this example.

The weight of asset $i$ at time $t$ is calculated as
\begin{equation*}
w_{t,i} = \frac{V_{t,i}}{\sum_{i=0}^N V_{t,i}}
\end{equation*}

Here we compute both the beginning and end of period weights.
<<>>=
bop_weights = eop_weights = matrix(0, 2, ncol(R))
for(t in 1:2){
  bop_weights[t,] = bop_value[t,] / sum(bop_value[t,])
  eop_weights[t,] = eop_value[t,] / sum(eop_value[t,])
}
bop_weights
eop_weights
@

The portfolio returns at time $t$ are calculated as
\begin{equation*}
R_{P_t} = \frac{V_t - V_{t-1}}{V_{t-1}}
\end{equation*}

<<>>=
V = c(V_0, rowSums(eop_value))
R_P = diff(V) / V[1:2]
R_P
@

The contribution of asset $i$ at time $t$ is calculated as
\begin{equation*}
contribution_{t,i} = \frac{V_{{eop}_{t,i}} - V_{{bop}_{t,i}}}{\sum_{i=1}^N V_{{bop}_{t,i}}}
\end{equation*}

<<>>=
contribution = matrix(0, 2, ncol(R))
for(t in 1:2){
  contribution[t,] = (eop_value[t,] - bop_value[t,]) / sum(bop_value[t,])
}
contribution
@

Note that contribution can also be calculated as
\begin{equation*}
contribution_{t,i} = R_{t,i} * w_{t,i}
\end{equation*}

\section{Return.portfolio Examples}

<<>>=
args(Return.portfolio)
@

If no \verb"weights" are specified, then an equal weight portfolio is computed. If \verb"rebalance_on=NA" then a buy and hold portfolio is assumed. See \verb"?Return.portfolio" for a detailed explanation of the function and arguments.

<<tidy=FALSE>>=
# Equally weighted, buy and hold portfolio returns
Return.portfolio(R)

# Equally weighted, rebalanced quarterly portfolio returns
Return.portfolio(R, rebalance_on="quarters")

# Equally weighted, rebalanced quarterly portfolio returns.
# Use verbose=TRUE to return additional information
# including asset values and weights
Return.portfolio(R, rebalance_on="quarters", verbose=TRUE)
@

\section{Transaction Costs}

The \verb"Return.portfolio" function supports the application of transaction costs during rebalancing events. This is specified via the \verb"rebal_cost" parameter. It allows the user to define a proportional transaction cost applied to the fractional change in weights.

When \verb"rebal_cost" is non-zero, the absolute change in weights (the turnover) is calculated for each asset at the rebalance date. The total turnover is multiplied by the \verb"rebal_cost" to calculate the transaction cost drag, which is then subtracted from the total portfolio value at the beginning of the new period. This effectively reduces the portfolio return by the amount of the transaction costs incurred during rebalancing. The cost is also proportionally allocated to the individual asset contributions, so that the sum of the contributions still correctly equals the portfolio return.

\end{document}
