This repsoitory holds code examples supporting the chapters of the book.
Make sure you create a local environment and install listed requirements before running the code.
pip install -r requirements.txt
Also, additional connectivity to DWave, IBM and cloud providers (Azure, AWS) will require accounts in those services to fully reproduce existing bits of code.
Data shown under the data folder is the one used by all the examples. It was obtained using Binance's API and the script named retrive_data.py using the following command
python retrieve_data.py --day "2022-11-04"
That command looks back for 30 days and retrieves data from 5 assets by default. More information on how to use this functionality can be obtained by the command
python retrieve_data.py --help
Derivative pricing is one of those canonical examples in finance modelling. It tries to set the price for an option at a time
Portfolio optimization another of those examples where a subset from all the available STOCKs should be selected so that the selection meets budget and risk willingness constraints while maximizing the expected revenue from the asset selection.
This chapter performs a risk analysis in UK househoolds using classical and quantum Machine Learning models to develop models for risk analysis and assess the financial stability for a given case. This chapter explores several techniques such as SVM and NN so a working knowledge on those will help the reader catch up when the Quantum version is presented.
This chapter revolves around how to connect to major Cloud providers and their Quantum Computing offering. It is important that there exists a resource estimation before sending the circuits to the cloud hosted resource given these can be rather expensive devices to use.
It is important we understand the fundamental differences between the two and the role noise plays when emulating our circuits in a realstic setup. Restrictions given by the physical chip need to be taken into consideration when transpiling the theoretical circuit.
In this chapter we covered some interesting facts regarding current NISQ devices. On e needs to be aware of the complications that will be faced when working on actual devices and how to deal with their imperfections. It is just a brief reference on some of the problems and pottential techniques to aliviate those.