Book Image

Machine Learning for Finance

By : Jannes Klaas
Book Image

Machine Learning for Finance

By: Jannes Klaas

Overview of this book

Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including insurance, transactions, and lending. This book explains the concepts and algorithms behind the main machine learning techniques and provides example Python code for implementing the models yourself. The book is based on Jannes Klaas’ experience of running machine learning training courses for financial professionals. Rather than providing ready-made financial algorithms, the book focuses on advanced machine learning concepts and ideas that can be applied in a wide variety of ways. The book systematically explains how machine learning works on structured data, text, images, and time series. You'll cover generative adversarial learning, reinforcement learning, debugging, and launching machine learning products. Later chapters will discuss how to fight bias in machine learning. The book ends with an exploration of Bayesian inference and probabilistic programming.
Table of Contents (15 chapters)
Machine Learning for Finance
Contributors
Preface
Other Books You May Enjoy
Index

Practical tips for RL engineering


In this section, we will be introducing some practical tips for building RL systems. We will also highlight some current research frontiers that are highly relevant to financial practitioners.

Designing good reward functions

Reinforcement learning is the field of designing algorithms that maximize a reward function. However, creating good reward functions is surprisingly hard. As anyone who has ever managed people will know, both people and machines game the system.

The literature on RL is full of examples of researchers finding bugs in Atari games that had been hidden for years but were found and exploited by an RL agent. For example, in the game "Fishing Derby," OpenAI has reported a reinforcement learning agent achieving a higher score than is ever possible according to the game makers, and this is without catching a single fish!

While it is fun for games, such behavior can be dangerous when it occurs in financial markets. An agent trained on maximizing returns...