The Financial Data Playbook (Algorithmic Trading) - Softcover

Conlan, Chris

Softcover

ISBN 13: 9798534050783

Publisher: Independently published, 2021

Synopsis

The Financial Data Playbook is a compendium of thoughtful business lessons from a career financial machine learning engineer. It offers insights on how to navigate the business expectations and theoretical challenges of modern applied finance.

Each argument is presented as a careful mathematical discussion that illustrates how investors, executives, and engineers think about and allocate resources to high-risk high-reward research and development projects.

Readers will learn about:

• Measuring the business value of improving model accuracy
• Improving the accuracy and validity of investment performance simulations
• Estimating the amount of data required to improve a model
• Choosing the right model for the data
• Comparing the performance of modern and legacy methods
• Accounting for counter-party expectations to improve accuracy
• And more ...

This book is written for finance and data business managers who want to maximize their financial data science R&D investment by understanding the opportunities and constraints presented by recent advances in financial machine learning.

About this title

About the Author

Chris Conlan is the founder and CEO of Conlan Scientific, a financial data science consultancy based out of Charlotte, North Carolina. He works with his team of data scientists to build machine learning solutions for banks, lenders, investors, traders, and fintech companies. Chris graduated University of Virginia's College of Arts & Sciences with a degree in statistics, where he later co-taught a data science capstone course.

Edition details

• Publisher: Independently published
• Publication date: 2021
• Language: English
• ISBN 13: 9798534050783
• Binding: Paperback
• Number of pages: 92