# skfolio.measures.cdar ### skfolio.measures.cdar(drawdowns, beta=0.95) Compute the historical CDaR (conditional drawdown at risk). * **Parameters:** **drawdowns** *ndarray of shape (n_observations,) or (n_observations, n_assets)* : Vector of drawdowns. **beta** *float, default = 0.95* : The CDaR confidence level (expected drawdown on the worst (1-beta)% observations). * **Returns:** **value** *float or ndarray of shape (n_assets,)* : CDaR. If `returns` is a 1D-array, the result is a float. If `returns` is a 2D-array, the result is a ndarray of shape (n_assets,).