BaseInstrument¶

class pfhedge.instruments.BaseInstrument[source]¶

Base class for all financial instruments.

bfloat16()[source]¶

Casts all floating point parameters and buffers to torch.bfloat16 datatype.

Note

This method modifies the instrument in-place.

Returns: self

cpu()[source]¶

Moves all buffers of this instrument and its underlier to the CPU.

Note

This method modifies the instrument in-place.

Returns: self

cuda(device=None)[source]¶

Moves all buffers of this instrument and its underlier to the GPU.

Note

This method modifies the instrument in-place.

Parameters: device (int, optional) – If specified, all buffers will be copied to that device.
Returns: self

double()[source]¶

Casts all floating point parameters and buffers to torch.float64 datatype.

Note

This method modifies the instrument in-place.

Returns: self

extra_repr()[source]¶

Set the extra representation of the instrument.

To print customized extra information, you should re-implement this method in your own instruments. Both single-line and multi-line strings are acceptable.

float()[source]¶

Casts all floating point parameters and buffers to torch.float32 datatype.

Note

This method modifies the instrument in-place.

Returns: self

float16()[source]¶: Alias for half().

float32()[source]¶: Alias for float().

float64()[source]¶: Alias for double().

half()[source]¶

Casts all floating point parameters and buffers to torch.float16 datatype.

Note

This method modifies the instrument in-place.

Returns: self

abstract property is_listed¶: Returns whether it is listed or not.

abstract simulate(n_paths, time_horizon, **kwargs)[source]¶

Simulate time series associated with the instrument itself (for a primary instrument) or its underlier (for a derivative) and add them as buffers.

Parameters

n_paths (int) – The number of paths to simulate.
time_horizon (float) – The period of time to simulate the price.

Returns

None

abstract property spot¶: Returns the spot price of self.

abstract to(*args, **kwargs)[source]¶

Moves and/or casts the buffers of the instrument.

This can be called as

to(device=None, dtype=None)[source]¶

to(tensor)[source]¶

to(instrument)[source]¶

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.