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Quantum Finance
https://github.com/qiskit-community/qiskit-finance

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Quantum Finance

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# Qiskit Finance



[![License](https://img.shields.io/github/license/Qiskit/qiskit-finance.svg?style=popout-square)](https://opensource.org/licenses/Apache-2.0)[![Build Status](https://github.com/qiskit-community/qiskit-finance/workflows/Finance%20Unit%20Tests/badge.svg?branch=main)](https://github.com/qiskit-community/qiskit-finance/actions?query=workflow%3A"Finance%20Unit%20Tests"+branch%3Amain+event%3Apush)[![](https://img.shields.io/github/release/Qiskit/qiskit-finance.svg?style=popout-square)](https://github.com/qiskit-community/qiskit-finance/releases)[![](https://img.shields.io/pypi/dm/qiskit-finance.svg?style=popout-square)](https://pypi.org/project/qiskit-finance/)[![Coverage Status](https://coveralls.io/repos/github/Qiskit/qiskit-finance/badge.svg?branch=main)](https://coveralls.io/github/Qiskit/qiskit-finance?branch=main)



**Qiskit Finance** is an open-source framework that contains uncertainty components for stock/securities problems,

applications, such as portfolio optimization, and data providers to source real or random data to

finance experiments.



## Installation



We encourage installing Qiskit Finance via the pip tool (a python package manager).



```bash

pip install qiskit-finance

```



**pip** will handle all dependencies automatically and you will always install the latest

(and well-tested) version.



If you want to work on the very latest work-in-progress versions, either to try features ahead of

their official release or if you want to contribute to Finance, then you can install from source.

To do this follow the instructions in the

 [documentation](https://qiskit-community.github.io/qiskit-finance/getting_started.html#installation).



----------------------------------------------------------------------------------------------------



### Creating Your First Finance Programming Experiment in Qiskit



Now that Qiskit Finance is installed, it's time to begin working with the finance module.

Let's try an experiment using Amplitude Estimation algorithm to

evaluate a fixed income asset with uncertain interest rates.



```python

import numpy as np

from qiskit.primitives import Sampler

from qiskit_algorithms import AmplitudeEstimation

from qiskit_finance.circuit.library import NormalDistribution

from qiskit_finance.applications import FixedIncomePricing



# Create a suitable multivariate distribution

num_qubits = [2, 2]

bounds = [(0, 0.12), (0, 0.24)]

mvnd = NormalDistribution(

    num_qubits, mu=[0.12, 0.24], sigma=0.01 * np.eye(2), bounds=bounds

)



# Create fixed income component

fixed_income = FixedIncomePricing(

    num_qubits,

    np.eye(2),

    np.zeros(2),

    cash_flow=[1.0, 2.0],

    rescaling_factor=0.125,

    bounds=bounds,

    uncertainty_model=mvnd,

)



# the FixedIncomeExpectedValue provides us with the necessary rescalings



# create the A operator for amplitude estimation

problem = fixed_income.to_estimation_problem()



# Set number of evaluation qubits (samples)

num_eval_qubits = 5



# Construct and run amplitude estimation

sampler = Sampler()

algo = AmplitudeEstimation(num_eval_qubits=num_eval_qubits, sampler=sampler)

result = algo.estimate(problem)



print(f"Estimated value:\t{fixed_income.interpret(result):.4f}")

print(f"Probability:    \t{result.max_probability:.4f}")

```

When running the above the estimated value result should be 2.46 and probability 0.8487.



### Further examples



Learning path notebooks may be found in the

[finance tutorials](https://qiskit-community.github.io/qiskit-finance/tutorials/index.html) section

of the documentation and are a great place to start.



----------------------------------------------------------------------------------------------------



## Contribution Guidelines



If you'd like to contribute to Qiskit, please take a look at our

[contribution guidelines](https://github.com/qiskit-community/qiskit-finance/blob/main/CONTRIBUTING.md).

This project adheres to Qiskit's [code of conduct](https://github.com/qiskit-community/qiskit-finance/blob/main/CODE_OF_CONDUCT.md).

By participating, you are expected to uphold this code.



We use [GitHub issues](https://github.com/qiskit-community/qiskit-finance/issues) for tracking requests and bugs. Please

[join the Qiskit Slack community](https://qisk.it/join-slack)

and for discussion and simple questions.

For questions that are more suited for a forum, we use the **Qiskit** tag in [Stack Overflow](https://stackoverflow.com/questions/tagged/qiskit).



## Authors and Citation



Finance was inspired, authored and brought about by the collective work of a team of researchers.

Finance continues to grow with the help and work of

[many people](https://github.com/qiskit-community/qiskit-finance/graphs/contributors), who contribute

to the project at different levels.

If you use Qiskit, please cite as per the provided

[BibTeX file](https://github.com/Qiskit/qiskit/blob/main/CITATION.bib).



## License



This project uses the [Apache License 2.0](https://github.com/qiskit-community/qiskit-finance/blob/main/LICENSE.txt).