Hands-On AI Trading with Python, QuantConnect and AWS

Texte du rabat

"Book Summary: This book is tailored for students, traders, and quants in finance who want to understand modern trading strategies and enhance them with artificial intelligence. It assumes basic knowledge of Python 3.x and familiarity with finance and trading concepts. Goals: AI Overview: Introduces key AI algorithms and best practices in financial trading. Intuitive Learning: Uses real-world examples to explain how algorithms work. Easy Experimentation: Provides a straightforward setup using QuantConnect.com for testing algorithms without complex infrastructure. The book avoids detailed infrastructure setup and large model training, instead using pre-trained models from AWS Bedrock, MLFinLab, or PredictNow.ai, making it accessible for readers to apply AI in trading strategies effectively"--

Contenu

Biographies

Introduction

Preface: About QuantConnect

Part I

Chapter 1: Foundations of Modern markets

Chapter 2: Foundations of Quantitative Trading

Part II

Part Overview

Chapter 3: Problem Definition

Chapter 4: Dataset Preparation

Chapter 5: Model Choice, Training and Application

Part III

Part Overview

Chapter 6: Applied Machine Learning Part 1 and 2

Chapter 7: Better Hedging by Reinforcement Learning

Chapter 8: AI for Risk Management and Optimization

Chapter 9: Application of LLM and Generative AI

References