analyze_performance: Analyze Backtest Performance with Daily Monitoring

In PortfolioTesteR: Test Investment Strategies with English-Like Code

Analyze Backtest Performance with Daily Monitoring

Description

Calculates comprehensive performance metrics using daily price data for enhanced accuracy. Provides risk-adjusted returns, drawdown analysis, and benchmark comparison even when strategy trades at lower frequency.

Usage

analyze_performance(
  backtest_result,
  daily_prices,
  benchmark_symbol = "SPY",
  rf_rate = 0,
  confidence_level = 0.95
)

Arguments

backtest_result	Result object from run_backtest()
daily_prices	Daily price data including all portfolio symbols
benchmark_symbol	Symbol for benchmark comparison (default: "SPY")
rf_rate	Annual risk-free rate for Sharpe/Sortino (default: 0)
confidence_level	Confidence level for VaR/CVaR (default: 0.95)

Value

performance_analysis object with metrics and daily tracking

Examples

data("sample_prices_weekly")
data("sample_prices_daily")

# Use overlapping symbols; cap to 3
syms_all <- intersect(names(sample_prices_weekly)[-1], names(sample_prices_daily)[-1])
stopifnot(length(syms_all) >= 1)
syms <- syms_all[seq_len(min(3L, length(syms_all)))]

# Subset weekly (strategy) and daily (monitoring) to the same symbols
P <- sample_prices_weekly[, c("Date", syms), with = FALSE]
D <- sample_prices_daily[,  c("Date", syms), with = FALSE]

# Simple end-to-end example
mom <- calc_momentum(P, lookback = 12)
sel <- filter_top_n(mom, n = 3)
W   <- weight_equally(sel)
res <- run_backtest(P, W)

# Pick a benchmark that is guaranteed to exist in D
perf <- analyze_performance(res, D, benchmark_symbol = syms[1])
print(perf)
summary(perf)

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