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

pfhedge.stochastic.generate_cir(): The stochastic process.

Parameters

kappa (float, default=1.0) – The parameter $κ$ .
theta (float, default=0.04) – The parameter $θ$ .
sigma (float, default=2.0) – The parameter $σ$ .
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.