class_docstr: Volatility. The degree of variation of a series over time as measured by
  the standard deviation of daily returns.
  https://en.wikipedia.org/wiki/Volatility_(finance)
  
  **Default Inputs:** [Returns(window_length=2)]
  
  Parameters
  ----------
  annualization_factor : float, optional
      The number of time units per year. Defaults is 252, the number of NYSE
      trading days in a normal year.
class_docstr_tok: ["Volatility",".","The","degree","of","variation","of","a","series","over","time","as","measured","by","the","standard","deviation","of","daily","returns",".","https",":","\/\/en.wikipedia.org\/wiki\/Volatility_","(","finance",")","*","*","Default","Inputs",":","*","*","[","Returns","(","window_length=2",")","]","Parameters","--","--","--","--","--","annualization_factor",":","float",",","optional","The","number","of","time","units","per","year",".","Defaults","is","252",",","the","number","of","NYSE","trading","days","in","a","normal","year","."]
code: def compute(self, today, assets, out, returns, annualization_factor):
      out[:] = nanstd(returns, axis=0) * (annualization_factor**0.5)
  
imports: from numbers import Number
  from numpy import arange, average, clip, copyto, exp, fmax, full, isnan, log, NINF, sqrt, sum, unique
  from zipline.pipeline.data import EquityPricing
  from zipline.utils.input_validation import expect_types
  from zipline.utils.math_utils import nanargmax, nanmax, nanmean, nanstd, nansum
  from zipline.utils.numpy_utils import float64_dtype, ignore_nanwarnings
  from .factor import CustomFactor
  from ..mixins import SingleInputMixin
label_desc: Use image node_id 1 for calling the AnnualizedVolatility obj's underlying member method code with example usage: obj.compute(today, assets, out, returns, annualization_factor) without return types