Financial Data Analytics with Machine Learning, Optimization and Statistics, 1st Edition eBook

Delivery: Can be download immediately after purchasing. For new customer, we need process for verification from 30 mins to 12 hours.
Version: PDF/EPUB. If you need EPUB and MOBI Version, please contact us.
Compatible Devices: Can be read on any devices.

An essential introduction to data analytics and Machine Learning techniques in the business sector

In Financial Data Analytics with Machine Learning, Optimization and Statistics, a team consisting of a distinguished applied mathematician and statistician, experienced actuarial professionals, and working data analysts delivers an expertly balanced combination of traditional financial statistics, effective machine learning tools, and mathematics. The book focuses on contemporary techniques used for data analytics in the financial sector and the insurance industry with an emphasis on mathematical understanding and statistical principles and connects them with common and practical financial problems. Each chapter is equipped with derivations and proofs—especially of key results—and includes several realistic examples which stem from common financial contexts. The computer algorithms in the book are implemented using Python and R, two of the most widely used programming languages for applied science and in academia and industry, so that readers can implement the relevant models and use the programs themselves.

This book can help readers become well-equipped with the following skills:

To evaluate financial and insurance data quality, and use the distilled knowledge obtained from the data after applying data analytic tools to make timely financial decisions
To apply effective data dimension reduction tools to enhance supervised learning
To describe and select suitable data analytic tools as introduced above for a given dataset depending upon classification or regression prediction purpose
The book covers the competencies tested by several professional examinations, such as the Predictive Analytics Exam offered by the Society of Actuaries, and the Institute and Faculty of Actuaries’ Actuarial Statistics Exam.

Besides being an indispensable resource for senior undergraduate and graduate students taking courses in financial engineering, statistics, quantitative finance, risk management, actuarial science, data science, and mathematics for AI, Financial Data Analytics with Machine Learning, Optimization and Statistics also belongs in the libraries of aspiring and practicing quantitative analysts working in commercial and investment banking.

This is a digital product.

Financial Data Analytics with Machine Learning, Optimization and Statistics 1st Edition is written by Sam Chen; Ka Chun Cheung; Phillip Yam and published by Wiley-Blackwell. The Digital and eTextbook ISBNs for Financial Data Analytics with Machine Learning, Optimization and Statistics are 9781119863397, 1119863392 and the print ISBNs are 9781119863373, 1119863376. Additional ISBNs for this eTextbook include 9781119863403.