AI in Finance
Machine Learning for Trading, Risk, Fraud and Forecasting
About this guide
A concise exam companion for AI in finance, written for finance students, not just computer scientists. It covers machine learning from scratch for markets, financial data and the leakage trap, forecasting, trading signals, credit scoring, fraud detection, portfolio construction, language models for filings and news, backtesting and model risk, explainability and regulation. Every chapter ends with a worked example carried through step by step, so you can check the reasoning yourself.
Inside the guide
- Learning from scratch for markets
- Financial data and the leakage trap
- Forecasting
- Trading signals
- Credit scoring
- Fraud detection
- Portfolio construction
- Language models for filings and news
- Backtesting and model risk
- Explainability and regulation
Questions students ask
What does AI in Finance cover?
It covers machine learning from scratch for markets, financial data and the leakage trap, forecasting, trading signals, credit scoring, fraud detection, portfolio construction, language models for filings and news, backtesting and model risk, explainability and regulation.
Who is AI in Finance for?
It is written for finance students meeting machine learning, and for lecturers and librarians choosing a clear, exam-focused reading-list text.
What format does it come in?
Kindle ebook and paperback on Amazon.
Can I read part of it for free?
Full Marks Press offers a free sample chapter at fullmarkspress.com/free, and the full guide is free to read with Kindle Unlimited.