class_docstr: Arranging underlying volatility market in easier to read format. Also provides methods for calculating various
  volatility metrics, such as realized_vol volatility and volatility risk premium. Has extensive support for estimating
  implied_vol volatility addons.
class_docstr_tok: ["Arranging","underlying","volatility","market","in","easier","to","read","format",".","Also","provides","methods","for","calculating","various","volatility","metrics",",","such","as","realized_vol","volatility","and","volatility","risk","premium",".","Has","extensive","support","for","estimating","implied_vol","volatility","addons","."]
code: def __init__(self, market_df=None, intraday_spot_df=None):
      self._market_df = market_df
      self._intraday_spot_df = intraday_spot_df
  
      self._calculations = Calculations()
      self._timezone = Timezone()
      self._filter = Filter()
  
file_path: finmarketpy/finmarketpy/curve/volatility/volstats.py
imports: import math
  import pandas
  from pandas.tseries.offsets import CustomBusinessDay
  from findatapy.timeseries import Calculations, Filter, Timezone
  from findatapy.timeseries import Calendar
label_desc: Use image node_id 1 to create a new VolStats object from inherited base classes: object with example: obj = VolStats(market_df, intraday_spot_df)