Essentials of Excel VBA, Python, and R
Volume II: Financial Derivatives, Risk Management and Machine Learning
John Lee author Lie-Jane Kao author Cheng-Few Lee author Jow-Ran Chang author
Format:Hardback
Publisher:Springer International Publishing AG
Published:25th Mar '23
Should be back in stock very soon
This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data with the applications of Excel VBA, Python and R. Each chapter engages the reader with sample data drawn from individual stocks, stock indices, options, and futures. Now in its second edition, it has been expanded into two volumes, each of which is devoted to specific parts of the business analytics curriculum. To reflect the current age of data science and machine learning, the used applications have been updated from Minitab and SAS to Python and R, so that readers will be better prepared for the current industry.
This second volume is designed for advanced courses in financial derivatives, risk management, and machine learning and financial management. In this volume we extensively use Excel, Python, and R to analyze the above-mentioned topics. It is also a comprehensive reference for active statistical finance scholars and business analysts who are looking to upgrade their toolkits. Readers can look to the first volume for dedicated content on financial statistics, and portfolio analysis.
ISBN: 9783031142826
Dimensions: unknown
Weight: unknown
523 pages
2nd ed. 2023