Advances in Financial Machine Learning
by Marcos Lopez de Prado · first published 2018
64% recommend36% neutral
Why HN recommends it
Practical guide to applying machine learning to financial data, with strong coverage of backtesting pitfalls and strategy risk; suits quants and engineers moving from general ML into trading strategy work.
Summarised by Claude from recommending comments
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Advances in Financial Machine Learning by Marcos Lopez de Prado is one of the best books i read last year. Especially on back testing, strategy risk are my fav.
on “Introduction to Machine Learning for Finance” ↗…just need to do well in one of the rounds where everyone else fails so you can go through the process of 'what did I do that I'm not aware of that made me succeed where everyone else failed' 2. Read Advances in Financial Machine Learning by Marcos Lopez de Prado. This goes over the false assumptions that outsiders make, and then outlines rookie mistakes(I made many of the mistakes described in the book, then read this book when it came…
on “Building AI Trading Systems” ↗…Using C++", Stroustrup Quant: "Quantitative Trading", Dr. Ernest Chan "Algorithmic Trading", Dr. Ernest Chan "Machine Trading: Deploying Computer Algorithms to Conquer the Markets", Dr. Ernest Chan "Advances in Financial Machine Learning", Marcos Lopez de Prado "Options, Futures and Other Derivatives (10th edition)", John C. Hull Buddhism: "Open Heart, Clear Mind", Thubten Chodron "Buddhism For Beginners", Thubten Chodron "Working…
on “Ask HN: What books do you keep on your desk?” ↗…What books would you recommend for financial quants interested in trading strategies rather than derivatives pricing (the areas can overlap)? I have worked in this capacity. Here are a few books I like: Advances in Financial Machine Learning (2018) by Marcos Lopez de Prado Non-Linear Time Series Models in Empirical Finance (2000) by Philip Hans Franses and Dick van Dijk (covers Markov chains, used by RenTech, among other topics) A Non-Random…
on “Renaissance Technologies Solved the Market: Part 1 – Pipeline” ↗…pattern recognition. If you are interested in stochastic calculus and convex strategies, John Hull's "Options, Futures and Other Derivatives" is a classic read. Another good book is Marcos Lopez de Prado's "Advances in Financial Machine Learning."
on “Ask HN: Does a CFA Matter in FinTech?” ↗1. Inside the Black Box Introduction to quantitative finance and to learn what strategies are used by firms who are supposed to beat the market. 2. Advances in Financial Machine Learning Deep dive into ML techniques if you want to start making money from data and math.
on “Ask HN: End of Year Book Recommendations” ↗…ignore flavor of the day frameworks and tech but rather focus on the basics. For example, if you're working in financial modeling, one way to improve as an engineer to get better at the domain. Maybe "Advances in Financial Machine Learning" by Marcos López de Prado. You'd have to work through the math and pick up finance on the go (which I assume should be easier part). As for people doing cool stuff in Zig / Rust, what matters is the problem…
on “Ask HN: Reading list for being a better engineer?” ↗The latest version of mlfinlab (Github) has been released. A package based on the book: Advances in Financial Machine Learning by Marcos Lopez de Prado. ```pip install mlfinlab``` This new release is our biggest to date and includes code for: 1. Sequentially Bootstrapped Ensembles (Regression & Classification) 2. Purged…
on “Advances in Financial Machine Learning Package (Python)” ↗…for Finance: Mastering Data-Driven Finance Never Split the Difference: Negotiating as if Your Life Depended on it Alpha Masters Fooling Some of the People All of Time Dark Pools When Genius Failed Advances in Financial Machine Learning Algorithmic Trading Other: Getting Things Done: The Art of Stress-Free productivity Mythology: Timeless Tales of Gods and Heroes Chaos: Making a New Science Networks, Crowds, and Markets: Reasoning…
on “Ask HN: Books you plan to read in 2020?” ↗…into technical analysis, I'd recommend "Evidence-Based Technical Analysis" by David Arons (a spoiler: the evidence is not good). If you're interested in ML applied to trading, I keep seeing references to Advances in Financial Machine Learning (Marcos Lopez de Prado), although I haven't actually read it. Regarding other financial products, CME has a large number of resources available for understanding futures trading, although futures are…
on “SIPC Says It Has Serious Concerns About Robinhood's New Product” ↗…Microstructural Features * Entropy Features Other: * ONC Clustering Algorithm * Improved Feature importance * Add time data structure * Add Z-score filters We are just about finished with the textbook Advances in Financial Machine Learning and have started to implement a few papers from the Journal of Financial Data Science. Namely: 1. Codependence module based on information theory. 2. Feature Importance: Model Fingerprint If you have…
on “MLFinLab 0.5.0 Release and Looking for New Research” ↗> For example, in Advances in Financial Machine Learning, the author discusses how to pick sensible thresholds and transform the data to convert the regression into a classification problem. This is interesting! Standard wisdom says that you get more statistical…
on “Lessons learned building an ML trading system that turned $5k into $200k (2019)” ↗