Artificial Intelligence for Capital Markets - Hasan Jafar, Syed; K, Hemachandran; El-Chaarani, Hani;(ed.) - Prospero Internet Bookshop
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Artificial Intelligence for Capital Markets

 
Edition number: 1
Publisher: Chapman and Hall
Date of Publication:
 
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Short description:

This book throws light on application of AI/ML techniques in the financial capital markets. It discusses the challenges posed by these techniques as these are prone to "black box" syndrome. The complexity of understanding the underlying dynamics of these methods is one of the major concerns which is highlighted in this book.

Long description:

Artificial Intelligence for Capital Market throws light on the application of AI/ML techniques in the financial capital markets. This book discusses the challenges posed by the AI/ML techniques as these are prone to "black box" syndrome. The complexity of understanding the underlying dynamics for results generated by these methods is one of the major concerns which is highlighted in this book.


Features:



  • Showcases artificial intelligence in finance service industry

  • Explains credit and risk analysis

  • Elaborates on cryptocurrencies and blockchain technology

  • Focuses on the optimal choice of asset pricing model

  • Introduces testing of market efficiency and forecasting in the Indian stock market

This book serves as a reference book for academicians, industry professionals, traders, finance managers and stock brokers. It may also be used as textbook for graduate level courses in financial services and financial analytics.

Table of Contents:

1. Artificial Intelligence in the Financial Service Industry. 2. Machine Learning and Big Data in Finance Services. 3. Artificial Intelligence in Financial Services: Advantages and Disadvantages. 4. Upscaling Profits in Financial Market. 5. Credit and Risk Analysis in the Financial and Banking Sectors: An Investigation. 6. Cryptocurrencies and Blockchain Technology Applications. 7. Machine Learning and the Optimal Choice of Asset Pricing Model. 8. Testing for Market Efficiency Using News-Driven Sentiment: Evidence from Select NYSE Stocks. 9. Comparing Statistical, Deep Learning, and Additive Models for Forecasting in the Indian Stock Market. 10. Applications and Impact of Artificial Intelligence in the Finance Sector.