MarketQuotations.MarketData¶

Classes

`List`	Methods
`MarketData`(underlying_level: float, ...)	Container class to encapsulate market data.
`RawDiscountRateCurve`(...)	Container class to describe a discount rate curve.

class MarketQuotations.MarketData.MarketData(underlying_level: float, atm_vol: float, moneyness: typing.List[float], skew_values: typing.List[float], raw_discount_rate_curve: Rates.RawDiscountRateCurve.RawDiscountRateCurve)[source]¶

Container class to encapsulate market data.

Parameters:

underlying_level : float

The quotation of the option underlying value.

atm_vol : float

The quotation of the At-The-Money volatility of an option.

moneyness : List[float]

A list specifying the deltas used to represent the smile.

skew_values : List[float]

A list where the ith element represents the relative difference between the volatility of the option having a moneyness corresponding to moneyness[i] and the atm volatility.

raw_discount_rate_curve : RawDiscountRateCurve

A raw representation (without interpolation) of the discount curve term structure used to discount future flows.

Examples

>>> from MarketQuotations.MarketData import MarketData
>>> from Rates.RawDiscountRateCurve import RawDiscountRateCurve
>>> import numpy as np
>>> underlying_level = 100.0
>>> atm_vol = 0.3
>>> moneyness = np.array([0.05,0.25,0.5,0.75,0.95])
>>> skew_values = np.array([0.238, 0.117, 0, -0.110, -0.110])
>>> rate_durations = np.array([0.0,1.0,2.0,3.0])
>>> discounts = np.array([1.0,0.98,0.83,0.75])
>>> raw_discount_rate_curve = RawDiscountRateCurve("USD-LIBOR", rate_durations, discounts)
>>> market_data = MarketData(underlying_level, atm_vol, moneyness, skew_values, raw_discount_rate_curve)
>>> print(market_data.underlying_level)
100.0
>>> print(market_data.atm_vol)
0.3

Attributes

`atm_vol`
`moneyness`
`raw_discount_rate_curve`
`skew_values`
`underlying_level`