Description: Essentials of Excel Vba, Python, and R : Financial Derivatives, Risk Management and Machine Learning, Hardcover by Lee, John; Chang, Jow-ran; Kao, Lie-jane; Lee, Cheng-Few, ISBN 3031142829, ISBN-13 9783031142826, Brand New, Free shipping in the US 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.
Price: 232.14 USD
Location: Jessup, Maryland
End Time: 2024-12-23T19:23:40.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 14 Days
Refund will be given as: Money Back
Return policy details:
Edition: 2
Book Title: Essentials of Excel VBA, Python, and R : Volume II: Financial Derivatives, Risk Management and Machine Learning
Number of Pages: Xv, 523 Pages
Language: English
Publisher: Springer International Publishing A&G
Topic: Programming Languages / General, Mathematical & Statistical Software, Finance / General, Statistics
Publication Year: 2023
Illustrator: Yes
Genre: Computers, Business & Economics
Item Weight: 60.4 Oz
Item Length: 11 in
Author: Lie Jane KAO, Cheng-Few Lee, John Lee, Jow-Ran Chang
Item Width: 8.3 in
Format: Hardcover
