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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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# http://www.apache.org/licenses/LICENSE-2.0
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import numpy as np
from qf_lib.containers.series.qf_series import QFSeries
[docs]def cvar(qf_series: QFSeries, percentage: float) -> float:
"""
Calculates Conditional Value at Risk for a given percentage. Percentage equal to 0.05 means 5% CVaR.
Parameters
----------
qf_series: QFSeries
Series of returns/prices
percentage: float
Percentage defining CVaR (what percentage of worst-case scenarios should be considered"
Returns
-------
float
Conditional value at risk as a number from range (-1,1). Simplifying: means how much money can be lost
in the worst "percentage" % of all cases.
"""
returns_tms = qf_series.to_simple_returns()
number_of_returns = len(returns_tms.values)
tail_length = round(number_of_returns * percentage)
assert tail_length > 0, 'Too few values in the series'
sorted_returns = sorted(returns_tms.values)
tail_returns = sorted_returns[:tail_length]
return np.mean(tail_returns, dtype=np.float64)