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Financial Modeling Using Quantum Computing

Financial Modeling Using Quantum Computing

By : Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere
5 (8)
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Financial Modeling Using Quantum Computing

Financial Modeling Using Quantum Computing

5 (8)
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)
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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

Quantum Machine Learning Algorithms and Their Ecosystem

In recent decades, many quantum computing scientists have leaned towards researching and generating quantum algorithms and their practical realization (Cerezo et al., 2021; Montanaro, 2016). As discussed in the previous chapter, quantum computers differ from classical computers mainly in the form of computation they employ. They can solve problems that are intractable for classical systems (Arute et al., 2019). In a quantum computer, instead of classical bits, qubits are the fundamental unit of information. The implementation of quantum algorithms is based fundamentally on the physical qualities of these qubits compared to classical bits. Still, the physical realization of quantum computers has not yet reached the level of maturity attained by their classical counterparts, where millions of transistors can be placed in a limited space without compromising their accuracy or functioning.

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