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

Summary

Computing paradigms, such as calculators and analog and digital computers, have evolved over the years to assist humans in making rapid strides in technological developments and reaching new knowledge frontiers. The contributions of Jon von Neumann, Alan Turing, and Graham Moore have been immense in achieving superior computing power.

The current business environment has given rise to the need to make faster and more accurate decisions based on data. Hence, there is a need for faster, optimized computers to process large amounts of data.

Digital computers cannot solve NP-hard problems, including simulation, optimization, and pattern-matching problems, thus emphasizing the need for new computing technologies to do faster and more accurate calculations.

Emerging computing paradigms, such as quantum computing and molecular computing, promise to solve large-scale problems such as portfolio optimization, protein foldings, and supply chain route optimization more effectively and efficiently.

Quantum computing is based on the underlying principles of quantum mechanics such as qubits and the quantum states, superposition, interference, entanglement, and quantum measurement.

Current quantum hardware and microprocessors are based on technologies such as superconducting, trapped ions, annealing, cold atoms, and simulators.

The quantum computing value chain is based on the innovations achieved using quantum solutions and technologies such as quantum sensors, quantum communication, and the quantum internet.

Global players across the value chain in the quantum computing domain include giants such as IBM, Microsoft, and Google, and well-funded start-ups such as Rigetti, IQM, and Quantinuum.

Aligning business strategy with quantum computing involves developing the strategy roadmap for companies based on quantum computing eras such as NISQ, broad quantum advantage, and full-scale fault tolerance.

The future quantum workforce needs to work on three dimensions, concerning the development of hardware, software, and related quantum technologies.