Financial Analytics / (Record no. 45039)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04294nam a22002657a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260817061623.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260817b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 978-93-5464-418-4 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | AKCL |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 332.0285 |
| Item number | MOH-F |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Mohanty, Pitabas |
| 245 ## - TITLE STATEMENT | |
| Title | Financial Analytics / |
| Statement of responsibility, etc. | Pitabas Mohanty |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | New Delhi: |
| Name of publisher, distributor, etc. | Wiley India Pvt. Ltd., |
| Date of publication, distribution, etc. | 2026 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XX,664p. |
| 490 ## - SERIES STATEMENT | |
| Series statement | Wiley Analytics Series for Management |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Financial Analytics applies modern data science tools to explore and understand interesting financial data patterns. Though the use of quantitative tools is nothing new in finance, modern financial analytics is different due to three recent trends: i) improved computing power with the availability of GPUs and TPUs, ii) advanced ML and AI algorithms, and iii) access to large volumes of practically all types of data. The new-age Financial Analytics takes a data-driven approach to study finance. Instead of making assumptions about the distribution of data or the relationship between variables, it simply lets the data speak for itself. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Economics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Banking |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Money |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Personal Finance |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 1. Introduction to Finance Analytics<br/><br/>1.1 Analytics in Finance<br/><br/>1.2 Data-Driven Finance<br/><br/>1.3 Organization of the Book<br/><br/>1.4 Use of R and Python<br/><br/>1.5 What this Book is Not About<br/><br/>1.6 Data and Codes Used in this Book<br/><br/>1.7 Skills and Resources Needed to Excel in Finance Analytics<br/><br/>2. Data in Finance<br/><br/>2.1 Introduction<br/><br/>2.2 Fundamental Data<br/><br/>2.3 Obtaining Fundamental Data<br/><br/>2.4 Marker Data<br/><br/>2.5 Analysts’ Data<br/><br/>2.6 Alternate Data<br/><br/>2.7 Downloading Data Using an API<br/><br/>3. Wrangling Financial Data<br/><br/>3.1 Reading Financial Data<br/><br/>3.2 Check Data Types (Variable Types)<br/><br/>3.3 Clean Variable Names<br/><br/>3.4 Managing Missing Data<br/><br/>3.5 Managing Invalid Data<br/><br/>3.6 Managing Outliers<br/><br/>3.7 Long and Wide Form Data<br/><br/>4. Exploratory Analysis of Financial Data<br/><br/>4.1 Introduction<br/><br/>4.2 Univariate Analysis of Fundamental Data<br/><br/>4.3 Bi-variate and Multi-variate Analysis of Fundamental Data<br/><br/>4.4 Analysis of Time Series Data<br/><br/>5. Understanding Basic Finance using R and Python<br/><br/>5.1 Introduction<br/><br/>5.2 Time Value of Money<br/><br/>5.3 Risk and Return<br/><br/>5.4 Asset Valuation<br/><br/>6. Accounting Data Analytics<br/><br/>6.1 Introduction<br/><br/>6.2 Case 1: Detecting Patterns in Financial Statements<br/><br/>6.3 Case 2: Predicting Corporate Bankruptcy<br/><br/>7. Applications of Natural Language Processing in Finance<br/><br/>7.1 Sourcing Text Data<br/><br/>7.2 Text Preprocessing<br/><br/>7.3 Case 1: Summarizing a Document<br/><br/>7.4 Case 2: Sentiment Analysis<br/><br/>7.5 Case 3: Sentiment Analysis Using Machine Learning<br/><br/>8. Financial Fraud Analytics<br/><br/>8.1 Benford’s Law<br/><br/>8.2 Predicting Credit Card Frauds<br/><br/>9. Valuation Analytics<br/><br/>9.1 Introduction<br/><br/>9.2 Theory of Valuation<br/><br/>9.3 Building a Valuation Model<br/><br/>9.4 Creating a Valuation Function<br/><br/>9.5 Estimating Implied Returns<br/><br/>9.6 Extension of the Model<br/><br/>9.7 Building the Valuation Function in Python<br/><br/>9.8 Valuation of Walmart Inc.<br/><br/>10. Portfolio Analytics<br/><br/>10.1 Introduction<br/><br/>10.2 Return and Risk of a Portfolio<br/><br/>10.3 Markowitz Optimization Process<br/><br/>10.4 Portfolio Optimization using Python<br/><br/>10.5 Portfolio Performance Evaluation<br/><br/>10.6 Portfolio Insurance<br/><br/>11. Developing and Backtesting Technical Trading Rules<br/><br/>11.1 Trend Indicators<br/><br/>11.2 Momentum Indicators<br/><br/>11.3 Volatility Indicators<br/><br/>11.4 Volume Indicators<br/><br/>11.5 Backtesting<br/><br/>11.6 Technical Analysis in Python<br/><br/>11.7 Comparing 5-day EMA with 21-day EMA in Python<br/><br/>11.8 Quantstrat to Automate Backtesting<br/><br/>12. Predicting Stock Prices/Returns<br/><br/>12.1 Predicting Stock Returns Based on Accounting Ratios<br/><br/>12.2 Predicting Stock Returns (Prices) using Past Stock Returns (Prices) Data<br/><br/>12.3 Predicting Stock Prices using Technical Indicators<br/><br/>12.4 Predicting Stock Returns using Valuation Multipliers and Value Drivers<br/><br/>12.5 Predicting Returns Based on Factor Exposures/Stock Characteristics<br/><br/>Appendix 1: Installing R and Python<br/><br/>Appendix 2: Introduction to R<br/><br/>Appendix 3: Introduction to Python<br/><br/>Appendix 4: A Concise Introduction to Machine Learning<br/><br/>Index |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Suppress in OPAC | No |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Date acquired | Cost, normal purchase price | Total Checkouts | Full call number | Barcode | Date last seen | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | ARCHBISHOP KAVUKATTU CENTRAL LIBRARY | ARCHBISHOP KAVUKATTU CENTRAL LIBRARY | 08/17/2026 | 1089.00 | 332.0285 MOH-F | 69327 | 08/17/2026 | 1089.00 | 08/17/2026 | Books |