Book Image

Financial Modeling Using Quantum Computing

By : Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere
5 (1)
Book Image

Financial Modeling Using Quantum Computing

5 (1)
By: Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere

Overview of this book

Quantum computing has the potential to revolutionize the computing paradigm. By integrating quantum algorithms with artificial intelligence and machine learning, we can harness the power of qubits to deliver comprehensive and optimized solutions for intricate financial problems. This book offers step-by-step guidance on using various quantum algorithm frameworks within a Python environment, enabling you to tackle business challenges in finance. With the use of contrasting solutions from well-known Python libraries with quantum algorithms, you’ll discover the advantages of the quantum approach. Focusing on clarity, the authors expertly present complex quantum algorithms in a straightforward, yet comprehensive way. Throughout the book, you'll become adept at working with simple programs illustrating quantum computing principles. Gradually, you'll progress to more sophisticated programs and algorithms that harness the full power of quantum computing. By the end of this book, you’ll be able to design, implement and run your own quantum computing programs to turbocharge your financial modelling.
Table of Contents (16 chapters)
1
Part 1: Basic Applications of Quantum Computing in Finance
5
Part 2: Advanced Applications of Quantum Computing in Finance
10
Part 3: Upcoming Quantum Scenario

Simulators and HPC’s Role in the NISQ Era

Now that we know how to make quantum and classical computing resources available and have reviewed how to pose our problems in both domains, we should evaluate the available mechanisms and strategies for exploiting those resources efficiently. By that, we mean cost and time efficiency, given that those axes will also need to be considered when it comes to including these techniques in our company’s daily processes.

Nowadays, the classical resources in most companies comprise a mixture of on-premises and cloud-enabled resources. This is the common case for most experimental projects aiming to improve operational processes using analytics. Ephemeral computing resources may have different needs, depending on the project or the nature of the technique we envision using. That is why the cloud-native pay-per-use model has become a good option for most companies.

Depending on the tasks, graphical processing units (GPUs) for machine...