Alternative Data and Artificial Intelligence Techniques : Applications in Investment and Risk Management

著者名：Zhang, Qingquan Tony/Li, Beibei/Xie, Danxia

Palgrave Macmillan（2022/10/31発売）

• 言語：ENG
• ISBN：9783031116117
• eISBN：9783031116124

Description

This book introduces a state-of-art approach in evaluating portfolio management and risk based on artificial intelligence and alternative data. The book covers a textual analysis of news and social media, information extraction from GPS and IoTs data, and risk predictions based on small transaction data, etc. The book summarizes and introduces the advancement in each area and highlights the machine learning and deep learning techniques utilized to achieve the goals. As a complement, it also illustrates examples on how to leverage the python package to visualize and analyze the alternative datasets, and will be of interest to academics, researchers, and students of risk evaluation, risk management, data, AI, and financial innovation.

Table of Contents

Chapter 1: The introduction of the portfolio management and risk evaluation .- Chapter 2: The major trends in financial portfolio management.- Chapter 3: Machine Learning and AI in financial portfolio management.- Chapter 4: Introduction of Alternative data in Finance.- Chapter 5: Alternative Data utilization from country perspective.- Chapter 6: Smart Beta and Risk Factors based on Textural Data and Machine Learning.- Chapter 7: Smart Beta and Risk Factors based on IoTs and AIoTs Data.- Chapter 8: Environmental, Social Responsibility and Corporate Governance on Corporations.- Chapter 9: Case Study – Fraud and Deception Detection: Text-based Data Analytics .- Chapter 10: Case Study – Investment Risk Analysis based on Sentiment Analysis and implementation .- Chapter 11: Case Study – Analyzing the corporation performance with ESG Factors.- Chapter 12: Alternative Data Visualization in Python.