cliquet_return_estimation

This module implements the ae_clique_return_estimation function that allows to the user configure a cliquet option, encode the expected value integral to compute in a quantum state and estimate it using the different AE algorithms implemented in the QQuantLib.AE package.

The function deals with all the mandatory normalisations for returning the desired price estimation.

Authors: Alberto Pedro Manzano Herrero & Gonzalo Ferro Costas

QQuantLib.finance.cliquet_return_estimation.ae_cliquet_estimation(**kwargs)

Configures a cliquet option return estimation problem and solving it using AE integration techniques

Parameters:

  • n_qbits (kwargs, int) – Number of qubits for domain discretization

  • s_0 (kwargs, float) – Value of the asset at initial time step

  • risk_free_rate (kwargs, float) – Risk free rate for discounting the expected value of the payoff

  • volatility (kwargs, float) – Volatility of the asset

  • reset_dates (kwargs, list) – List with the reset dates to asset evaluation

  • bounds (kwargs, float) – Bound for truncating the probability density

  • local_cap (kwargs, float) – For upper truncation of the return at each reset date

  • local_floor (kwargs, float) – For lower truncation of the return at each reset date

  • global_cap (kwargs, float) – For upper truncation of the final return

  • global_floor (kwargs, float) – For lower truncation of the final return

Note

Other kwargs input dictionary keys will be related with the encoding of the integral into the quantum circuit (see QQuantLib.DL.encoding_protocols) and for the configuration of the AE algorithm used (see QQuantLib.AE.ae_class)

Returns:

pdf – DataFrame with the configuration of the AE problem and the solution

Return type:

Pandas DataFrame