BSEuropeanBinaryOption

class pfhedge.nn.BSEuropeanBinaryOption(call=True, strike=1.0, derivative=None)[source]

Black-Scholes formula for a European binary option.

Note

Risk-free rate is set to zero.

See also

References

  • John C. Hull, 2003. Options futures and other derivatives. Pearson.

Parameters
  • call (bool, default=True) – Specifies whether the option is call or put.

  • strike (float, default=1.0) – The strike price of the option.

Shape:
  • Input: \((N, *, 3)\), where \(*\) means any number of additional dimensions. See inputs() for the names of input features.

  • Output: \((N, *, 1)\). All but the last dimension are the same shape as the input.

Examples

>>> from pfhedge.nn import BSEuropeanBinaryOption
...
>>> m = BSEuropeanBinaryOption(strike=1.0)
>>> m.inputs()
['log_moneyness', 'time_to_maturity', 'volatility']
>>> input = torch.tensor([
...     [-0.01, 0.1, 0.2],
...     [ 0.00, 0.1, 0.2],
...     [ 0.01, 0.1, 0.2]])
>>> m(input)
tensor([[6.2576],
        [6.3047],
        [6.1953]])
delta(log_moneyness=None, time_to_maturity=None, volatility=None)[source]

Returns delta of the derivative.

Parameters
  • log_moneyness – (torch.Tensor, optional): Log moneyness of the underlying asset.

  • time_to_maturity (torch.Tensor, optional) – Time to expiry of the option.

  • volatility (torch.Tensor, optional) – Volatility of the underlying asset.

Shape:
  • log_moneyness: \((N, *)\)

  • time_to_maturity: \((N, *)\)

  • volatility: \((N, *)\)

  • output: \((N, *)\)

Returns

torch.Tensor

Note

Parameters are not optional if the module has not accepted a derivative in its initialization.

forward(input)

Returns delta of the derivative.

Parameters

input (torch.Tensor) – The input tensor. Features are concatenated along the last dimension. See inputs() for the names of the input features.

Returns

torch.Tensor

classmethod from_derivative(derivative)[source]

Initialize a module from a derivative.

Parameters

derivative (pfhedge.instruments.EuropeanBinaryOption) – The derivative to get the Black-Scholes formula.

Returns

BSEuropeanBinaryOption

Examples

>>> from pfhedge.instruments import BrownianStock
>>> from pfhedge.instruments import EuropeanBinaryOption
>>>
>>> derivative = EuropeanBinaryOption(BrownianStock(), strike=1.1)
>>> m = BSEuropeanBinaryOption.from_derivative(derivative)
>>> m
BSEuropeanBinaryOption(strike=1.1000)
gamma(log_moneyness=None, time_to_maturity=None, volatility=None)[source]

Returns gamma of the derivative.

Parameters
  • log_moneyness (torch.Tensor, optional) – Log moneyness of the underlying asset.

  • time_to_maturity (torch.Tensor, optional) – Time to expiry of the option.

  • volatility (torch.Tensor, optional) – Volatility of the underlying asset.

Shape:
  • log_moneyness: \((N, *)\)

  • time_to_maturity: \((N, *)\)

  • volatility: \((N, *)\)

  • output: \((N, *)\)

Returns

torch.Tensor

Note

args are not optional if it doesn’t accept derivative in this initialization.

implied_volatility(log_moneyness=None, time_to_maturity=None, price=None, precision=1e-06)[source]

Returns implied volatility of the derivative.

Parameters
  • log_moneyness (torch.Tensor, optional) – Log moneyness of the underlying asset.

  • time_to_maturity (torch.Tensor, optional) – Time to expiry of the option.

  • price (torch.Tensor) – Price of the derivative.

  • precision (float) – Computational precision of the implied volatility.

Shape:
  • log_moneyness: \((N, *)\)

  • time_to_maturity: \((N, *)\)

  • price: \((N, *)\)

  • output: \((N, *)\)

Returns

torch.Tensor

Note

args are not optional if it doesn’t accept derivative in this initialization. price seems optional in typing, but it isn’t. It is set for the compatibility to the previous versions.

inputs()[source]

Returns the names of input features.

Returns

list

price(log_moneyness=None, time_to_maturity=None, volatility=None)[source]

Returns price of the derivative.

Parameters
  • log_moneyness (torch.Tensor, optional)) – Log moneyness of the underlying asset.

  • time_to_maturity (torch.Tensor, optional)) – Time to expiry of the option.

  • volatility (torch.Tensor, optional)) – Volatility of the underlying asset.

Shape:
  • log_moneyness: \((N, *)\)

  • time_to_maturity: \((N, *)\)

  • volatility: \((N, *)\)

  • output: \((N, *)\)

Returns

torch.Tensor

Note

args are not optional if it doesn’t accept derivative in this initialization.

theta(log_moneyness=None, time_to_maturity=None, volatility=None)[source]

Returns theta of the derivative.

Parameters
  • log_moneyness (torch.Tensor, optional) – Log moneyness of the underlying asset.

  • time_to_maturity (torch.Tensor, optional) – Time to expiry of the option.

  • volatility (torch.Tensor, optional) – Volatility of the underlying asset.

Shape:
  • log_moneyness: \((N, *)\)

  • time_to_maturity: \((N, *)\)

  • volatility: \((N, *)\)

  • output: \((N, *)\)

Note

Risk-free rate is set to zero.

Returns

torch.Tensor

Note

args are not optional if it doesn’t accept derivative in this initialization.

vega(log_moneyness=None, time_to_maturity=None, volatility=None)[source]

Returns vega of the derivative.

Parameters
  • log_moneyness (torch.Tensor, optional) – Log moneyness of the underlying asset.

  • time_to_maturity (torch.Tensor, optional) – Time to expiry of the option.

  • volatility (torch.Tensor, optional) – Volatility of the underlying asset.

Shape:
  • log_moneyness: \((N, *)\)

  • time_to_maturity: \((N, *)\)

  • volatility: \((N, *)\)

  • output: \((N, *)\)

Returns

torch.Tensor

Note

args are not optional if it doesn’t accept derivative in this initialization.