AssetAllocation (version 1.1.1)

backtest_allocation: Backtesting of asset allocation strategies

Description

backtest_allocation computes a backtest of a given portfolio allocation rule.

Usage

backtest_allocation(strat, P, R, risk_free = 0, start_date = NULL)

Value

An object of class "List" with the following elements:

strat

The strat provided to the function

returns

An xts object with the daily returns of the strategy

table_performance

A table with performance metrics

rebalance_dates

Vector of rebalancing dates

rebalance_weights

Vector of rebalancing dates

Arguments

strat

A list representing an asset allocation strategy.

P

An xts object with daily prices of the tickers in strat.

R

An xts object with daily returns of the tickers in strat.

risk_free

Either an xts object with daily returns of the risk-free asset, or a scalar numeric with the annual risk-free rate in decimals.

start_date

Optional starting date

Details

The function first determines the rebalancing dates based on strat$rebalance_frequency. Then, it cycles through intermediate dates and calculates daily returns based on the allocation. If the optional parameter start_date is provided, the backtest will start on that date. Otherwise, it will start from the date from which data on all assets becomes available.

Examples

# Example 1: backtesting one of the asset allocations in the package
us_60_40 <- asset_allocations$static$us_60_40
bt_us_60_40 <- backtest_allocation(us_60_40,
                                  ETFs$Prices,
                                  ETFs$Returns,
                                  ETFs$risk_free)

# show table with performance metrics
bt_us_60_40$table_performance
# Example 2: creating and backtesting an asset allocation from scratch

# create a strategy that invests equally in momentum (MTUM), value (VLUE),
# low volatility (USMV) and quality (QUAL) ETFs.

factor_strat  <- list(name = "EW Factors",
                      tickers = c("MTUM", "VLUE", "USMV", "QUAL"),
                      default_weights = c(0.25, 0.25, 0.25, 0.25),
                      rebalance_frequency = "month",
                      portfolio_rule_fn = "constant_weights")

# get data for tickers using getSymbols
factor_ETFs <- get_data_from_tickers(factor_strat$tickers,
                                     starting_date = "2020-01-01")
# backtest the strategy
bt_factor_strat <- backtest_allocation(factor_strat,
                                       factor_ETFs$P,
                                       factor_ETFs$R)
# show table with performance metrics
bt_factor_strat$table_performance