Hands-on AI trading with python, quantconnect and AWS (Record no. 10401)

MARC details
000 -LEADER
fixed length control field 03927 a2200241 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251022201132.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781394268436
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 332.6420285
Item number PIC
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Pik, Jiri
245 ## - TITLE STATEMENT
Title Hands-on AI trading with python, quantconnect and AWS
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. New Jersey
Name of publisher, distributor, etc. Wiley
Date of publication, distribution, etc. 2025
300 ## - PHYSICAL DESCRIPTION
Extent xxvi, 381p.
365 ## - TRADE PRICE
Price type code USD
Price amount 54.95
500 ## - GENERAL NOTE
General note Biographies xiii<br/><br/>Preface: QuantConnect xv<br/><br/>Introduction xxiii<br/><br/>Part I Foundations of Capital Markets and Quantitative Trading 1<br/><br/>Chapter 1 Foundations of Capital Markets 3<br/><br/>Market Mechanics 3<br/><br/>Market Participants 4<br/><br/>Trading Is the “Play” 4<br/><br/>The Stage and Basic Rules of Trading—The Limit Order Book 4<br/><br/>Actors—Liquidity Trader, Market Maker, and<br/><br/>Informed Trader 5<br/><br/>Liquidity Trader 5<br/><br/>Market Maker 5<br/><br/>Informed Trader 6<br/><br/>AI Actors Wanted! 7<br/><br/>Data and Data Feeds 7<br/><br/>Custom and Alternative Data 9<br/><br/>Brokerages and Transaction Costs 10<br/><br/>Transaction Costs 11<br/><br/>Security Identifiers 13<br/><br/>Assets and Derivatives 15<br/><br/>US Equities 15<br/><br/>US Equity Options 19<br/><br/>Index Options 21<br/><br/>US Futures 21<br/><br/>Cryptocurrency 23<br/><br/>Chapter 2 Foundations of Quantitative Trading 25<br/><br/>Research Process 25
520 ## - SUMMARY, ETC.
Summary, etc. Master the art of AI-driven algorithmic trading strategies through hands-on examples, in-depth insights, and step-by-step guidance<br/><br/>Hands-On AI Trading with Python, QuantConnect, and AWS explores real-world applications of AI technologies in algorithmic trading. It provides practical examples with complete code, allowing readers to understand and expand their AI toolbelt.<br/><br/>Unlike other books, this one focuses on designing actual trading strategies rather than setting up backtesting infrastructure. It utilizes QuantConnect, providing access to key market data from Algoseek and others. Examples are available on the book's GitHub repository, written in Python, and include performance tearsheets or research Jupyter notebooks.<br/><br/>The book starts with an overview of financial trading and QuantConnect's platform, organized by AI technology used:<br/><br/>Examples include constructing portfolios with regression models, predicting dividend yields, and safeguarding against market volatility using machine learning packages like SKLearn and MLFinLab.<br/>Use principal component analysis to reduce model features, identify pairs for trading, and run statistical arbitrage with packages like LightGBM.<br/>Predict market volatility regimes and allocate funds accordingly.<br/>Predict daily returns of tech stocks using classifiers.<br/>Forecast Forex pairs' future prices using Support Vector Machines and wavelets.<br/>Predict trading day momentum or reversion risk using TensorFlow and temporal CNNs.<br/>Apply large language models (LLMs) for stock research analysis, including prompt engineering and building RAG applications.<br/>Perform sentiment analysis on real-time news feeds and train time-series forecasting models for portfolio optimization.<br/>Better Hedging by Reinforcement Learning and AI: Implement reinforcement learning models for hedging options and derivatives with PyTorch.<br/>AI for Risk Management and Optimization: Use corrective AI and conditional portfolio optimization techniques for risk management and capital allocation.<br/>Written by domain experts, including Jiri Pik, Ernest Chan, Philip Sun, Vivek Singh, and Jared Broad, this book is essential for hedge fund professionals, traders, asset managers, and finance students. Integrate AI into your next algorithmic trading strategy with Hands-On AI Trading with Python, QuantConnect, and AWS. (https://www.wiley.com/en-us/Hands-On+AI+Trading+with+Python%2C+QuantConnect%2C+and+AWS-p-9781394268436)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Chan, Ernest P.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Broad, Jared
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Sun, Philip
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Singh ,Vivek
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Accession Number Date last seen Copy number Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     Indian Institute of Management LRC Indian Institute of Management LRC General Stacks 10/16/2025   3186.00   009206 10/16/2025 1 4901.54 10/16/2025 Book

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