CIRRate

class pfhedge.instruments.CIRRate(kappa=1.0, theta=0.04, sigma=0.2, cost=0.0, dt=0.004, dtype=None, device=None)[source]

A rate which follow the CIR process.

See also

Parameters
  • kappa (float, default=1.0) – The parameter \(\kappa\).

  • theta (float, default=0.04) – The parameter \(\theta\).

  • sigma (float, default=2.0) – The parameter \(\sigma\).

  • cost (float, default=0.0) – The transaction cost rate.

  • dt (float, default=1/250) – The intervals of the time steps.

  • dtype (torch.device, optional) – Desired device of returned tensor. Default: If None, uses a global default (see torch.set_default_tensor_type()).

  • device (torch.device, optional) – Desired device of returned tensor. Default: if None, uses the current device for the default tensor type (see torch.set_default_tensor_type()). device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types.

Buffers:
  • spot (torch.Tensor): The spot rate of the instrument. This attribute is set by a method simulate(). The shape is \((N, T)\) where \(N\) is the number of simulated paths and \(T\) is the number of time steps.

Examples

>>> from pfhedge.instruments import CIRRate
...
>>> _ = torch.manual_seed(42)
>>> rate = CIRRate()
>>> rate.simulate(n_paths=2, time_horizon=5/250)
>>> rate.spot
tensor([[0.0400, 0.0408, 0.0411, 0.0417, 0.0422, 0.0393],
        [0.0400, 0.0457, 0.0440, 0.0451, 0.0458, 0.0472]])
property default_init_state

Returns the default initial state of simulation.

simulate(n_paths=1, time_horizon=0.08, init_state=None)[source]

Simulate the spot rate and add it as a buffer named spot.

The shape of the spot is \((N, T)\), where \(N\) is the number of simulated paths and \(T\) is the number of time steps. The number of time steps is determinded from dt and time_horizon.

Parameters
  • n_paths (int, default=1) – The number of paths to simulate.

  • time_horizon (float, default=20/250) – The period of time to simulate the price.

  • init_state (tuple[torch.Tensor | float], optional) – The initial state of the instrument. This is specified by a tuple \((S(0),)\) where \(S(0)\) is the initial values of of spot. If None (default), it uses the default value (See default_init_state).

to(*args, **kwargs)

Moves and/or casts the buffers of the instrument.

This can be called as

to(device=None, dtype=None)
to(tensor)
to(instrument)

Its signature is similar to torch.nn.Module.to(). It only accepts floating point dtypes. See Instrument dtype and device for details.

Note

This method modifies the instrument in-place.

See also

  • float(): Cast to torch.float32.

  • double(): Cast to torch.float64.

  • half(): Cast to torch.float16.

  • bfloat16(): Cast to torch.bfloat16.

  • cuda(): Move to CUDA memory.

  • cpu(): Move to CPU memory.

Parameters
  • dtype (torch.dtype) – The desired floating point dtype of the buffers in this instrument.

  • device (torch.device) – The desired device of the buffers in this instrument.

  • tensor (torch.Tensor) – Tensor whose dtype and device are the desired dtype and device of the buffers in this instrument.

  • instrument (BaseInstrument) – Instrument whose dtype and device are the desired dtype and device of the buffers in this instrument.

Returns

self