weight_by_volatility: Volatility-Based Portfolio Weighting

In PortfolioTesteR: Test Investment Strategies with English-Like Code

Volatility-Based Portfolio Weighting

Description

Weights securities based on their volatility characteristics. Can prefer low-volatility (defensive) or high-volatility (aggressive) stocks.

Usage

weight_by_volatility(
  selected_df,
  vol_timeframe_data,
  strategy_timeframe_data = NULL,
  lookback_periods = 26,
  low_vol_preference = TRUE,
  vol_method = "std",
  weighting_method = c("rank", "equal", "inverse_variance")
)

Arguments

selected_df	Binary selection matrix (1 = selected, 0 = not)
vol_timeframe_data	Price data for volatility calculation (usually daily)
strategy_timeframe_data	Price data matching strategy frequency
lookback_periods	Number of periods for volatility (default: 26)
low_vol_preference	TRUE = lower vol gets higher weight (default: TRUE)
vol_method	"std", "range", "mad", or "abs_return"
weighting_method	"rank", "equal", or "inverse_variance"

Value

Data.table with volatility-based weights

Examples

data("sample_prices_weekly")
data("sample_prices_daily")
momentum <- calc_momentum(sample_prices_weekly, lookback = 12)
selected <- filter_top_n(momentum, 10)
daily_vol <- calc_rolling_volatility(sample_prices_daily, lookback = 252)
aligned_vol <- align_to_timeframe(daily_vol, sample_prices_weekly$Date)
weights <- weight_by_volatility(selected, aligned_vol, low_vol_preference = TRUE)

PortfolioTesteR documentation built on Nov. 5, 2025, 5:23 p.m.