Torrent details for "Dong H. Data Analytics in Finance 2025" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
None
Total Size:
25.2 MB
Info Hash:
CEE3385EDDE95446B1487BC4FF4FD4C809DDB298
Added By:
Added:
April 20, 2026, 5:39 a.m.
Stats:
|
(Last updated: April 20, 2026, 5:39 a.m.)
| File | Size |
|---|---|
| ['Dong H. Data Analytics in Finance 2025.pdf'] | 0 bytes |
Name
DL
Uploader
Size
S/L
Added
-
132.6 MB
[34
/
28]
2025-07-22
| Uploaded by andryold1 | Size 132.6 MB | Health [ 34 /28 ] | Added 2025-07-22 |
-
25.2 MB
[16
/
10]
2026-04-20
| Uploaded by andryold1 | Size 25.2 MB | Health [ 16 /10 ] | Added 2026-04-20 |
-
34.0 MB
[30
/
13]
2025-06-27
| Uploaded by andryold1 | Size 34.0 MB | Health [ 30 /13 ] | Added 2025-06-27 |
NOTE
SOURCE: Dong H. Data Analytics in Finance 2025
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
Textbook in PDF format Data Analytics in Finance covers the methods and application of data analytics in all major areas of finance, including buy-side investments, sell-side investment banking, corporate finance, consumer finance, financial services, real estate, insurance, and commercial banking. It explains statistical inference of big data, financial modeling, machine learning, database querying, data engineering, data visualization, and risk analysis. Emphasizing financial data analytics practices with a solution- oriented purpose, it is a "one-stop-shop" of all the major data analytics aspects for each major finance area. The book paints a comprehensive picture of the data analytics process including: Statistical inference of big data Financial modeling Machine learning and AI Database querying Data engineering Data visualization Risk analysis Each chapter is crafted to provide complete guidance for many subject areas including investments, fraud detection, and consumption finance. Avoiding data analytics methods widely available elsewhere, the book focuses on providing data analytics methods specifically applied to key areas of finance. Written as a roadmap for researchers, practitioners, and students to master data analytics instruments in finance, the book also provides a collection of indispensable resources for the readers' reference. Offering the knowledge and tools necessary to thrive in a data-driven financial landscape, this book enables readers to deepen their understanding of investments, develop new approaches to risk management, and apply data analytics to finance
×