Machine learning

Neural Networks and Why Data Matters for AI in Finance

This section of Chapter 3 is where things start to click. Hilpisch moves from talking about AI algorithms in general to showing how neural networks actually work. And then he drops a truth bomb that a lot of people skip over: your model is only as good as your data.

AI Algorithms: Types of Data, Learning, and Problems

Chapter 3 of Artificial Intelligence in Finance opens with the quote about AlphaGo beating a human Go player. That event was a big deal back in 2016. People thought it would take at least another decade. It didn’t. And that sets the tone for this chapter. AI moves faster than experts predict.

Big Data, Machine Learning, and the Future of Emerging Markets

The investment industry loves a good buzzword. And for the last several years, “big data” and “machine learning” have been the ones getting all the attention. Fund managers talk about them in the same breath, like they’re the same thing. They’re not. And the authors make that distinction very clear in this final chapter.

Artificial Intelligence in Finance: A Book Worth Reading in 2025

Book: Artificial Intelligence in Finance Author: Yves Hilpisch Publisher: O’Reilly, 2020 ISBN: 978-1-492-05543-3


Why This Book, Why Now

Here’s a question that bugs me. Can AI actually beat the stock market? Not in a sci-fi movie way. In a real, consistent, make-money-while-you-sleep way.