Quantitative risk and performance analysis package for financial time series powered by the Julia language.
Full documentation is available here.
simple_returns(prices::AbstractVector; drop_first=false, first_value=NaN)
simple_returns(prices::AbstractMatrix; drop_first=false, first_value=NaN)
log_returns(prices::AbstractVector; drop_first=false, first_value=NaN)
log_returns(prices::AbstractMatrix; drop_first=false, first_value=NaN)
volatility(returns; multiplier=1.0)
drawdowns(returns; geometric::Bool=false)
drawdowns_pnl(pnl)
expected_shortfall(returns, α, method::Symbol; multiplier=1.0)
information_ratio(asset_returns, benchmark_returns; multiplier=1.0)
jensen_alpha(asset_returns, benchmark_returns; risk_free=0.0)
modified_jensen(asset_returns, benchmark_returns; risk_free=0.0)
skewness(x; method::Symbol=:moment)
kurtosis(x; method::Symbol=:excess)
omega_ratio(returns, target_return)
relative_risk_contribution(weights, covariance_matrix)
sharpe_ratio(returns; multiplier=1.0, risk_free=0.0)
adjusted_sharpe_ratio(returns; multiplier=1.0, risk_free=0.0)
sortino_ratio(returns; multiplier=1.0, MAR=0.0)
tracking_error(asset_returns, benchmark_returns; multiplier=1.0)
treynor_ratio(asset_returns, benchmark_returns; multiplier=1.0, risk_free=0.0)
downside_deviation(returns, threshold; method::Symbol=:full)
upside_deviation(returns, threshold; method::Symbol=:full)
upside_potential_ratio(returns, threshold; method::Symbol=:partial)
value_at_risk(returns, α, method::Symbol; multiplier=1.0)
capm(asset_returns, benchmark_returns; risk_free=0.0)
lower_partial_moment(returns, threshold, n, method::Symbol)
higher_partial_moment(returns, threshold, n, method::Symbol)Please report any issues via the GitHub issue tracker.
This package was inspired by the R package PerformanceAnalytics of Peter Carl and Brian G. Peterson.