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An Introduction to Quantum Finance

Authors

Course creators: Jack Streeter, Edward Hall, Adam Fattal and Alice Bru.

We are a group of students studying Physics at Durham University. We hope this introductory course will help you gain an insight into some applications of quantum computing in finance.

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If you have any questions please contact us here:

Jack Streeter (2nd year, MPhys Physics) - [email protected]

Edward Hall (2nd year, Bsc Physics) - [email protected]

Adam Fattal (2nd year, Bsc Physics) - [email protected]

Alice Bru (3rd year, Natural Sciences) - [email protected]

Introduction

Welcome to this introductory course on the applications of quantum computing to finance. In this course, we will be taking you through four applications of quantum computational methods through lectures videos and notes, spread over a week. On the final day (day 5), you will be run through the covered applications with some coding exercises.

Both academically and commericially, Quantum Computation is attracting an ever-increasing amount of research interest; an industry that seems to be particularly interested in the utilisation of quantum computers is the financial industry. This week long course is designed to introduce basic Quantum Computing and display a few examples of how it can be applied to the world of finance. The course is targeted toward undergraduates in quantitative fields such as physics, mathematics and computer science, however the course assumes no prior knowledge or background in these topics.

"One who finds the niche of quantum computing application will become the new market leader" Viacheslav Petrenko

Course Content:

Pre-requisites: The pre-requisite folder contains three chapters; vectors (quantum states), matrices (quantum operators) and classical computation. It is thorougly advised to look through these before engaging with the course content.

Day 1: Introduces quantum computation both theoretically and practically.

Day 2: Introduces Quantum Risk Analysis, and its importance in everyday financial operations.

Day 3: Introduces Classical and Quantum Machine Learning and algorithms used in supply chain management and credit scoring.

Day 4: Introduces the use of Quantum Computing in Portfolio Optimization.

Day 5: A lab session that applies the content on day 4 to optimize a 5 stock portfolio.

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