Machine learningRTools of the trade
The Graphical Lasso and its Financial Applications
Way back in November 2007, literally weeks after SPX put in its pre-GFC all-time high, Friedman, Hastie and Tibshirani published
Machine Learning
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Machine learningNeural networksQuant trading
From Potential to Proven: Why AI is Taking Off in the Finance World
This article is a departure from the quantitative research that usually appears on the Robot Wealth blog. Until recently, I
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BacktestingMachine learningNeural networksQuant tradingRZorro
Neural Network Trading: A Getting Started Guide for Algo Trading
This article is adapted from one of the units of Advanced Algorithmic Trading. If you like what you see, check
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FXMachine learningQuant tradingR
Optimal Data Windows for Training a Machine Learning Model for Financial Prediction
It would be great if machine learning were as simple as just feeding data to an out-of-the box implementation of
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Machine learningQuant trading
Machine Learning in Algorithmic Trading Systems: Opportunities and Pitfalls
Last night it was my pleasure to present at the Tyro Fintech Hub in Sydney on the topic of using
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FXMachine learningQuant tradingRZorro
Machine learning for Trading: Part 2
Introduction My first post on using machine learning for financial prediction took an in-depth look at various feature selection methods
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Machine learningR
Machine learning for Trading:
Adventures in Feature SelectionUpdates: 2019: In this first Machine Learning for Trading post, we’ve added a section on feature selection using the Boruta
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BacktestingFXk-means clusteringMachine learningQuant tradingRTrading strategiesZorroA Robust Trading Framework Built with K-Means Clustering
Important preface: This post is in no way intended to showcase a particular trading strategy. It is purely to share
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BacktestingFXk-means clusteringMachine learningQuant tradingR
Unsupervised candlestick classification for fun and profit – part 2
In the last article, I described an application of the k-means clustering algorithm for classifying candlesticks based on the relative position
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FXk-means clusteringMachine learningQuant tradingR
Unsupervised candlestick classification for fun and profit – part 1
Candlestick patterns were used to trade the rice market in Japan back in the 1800’s. Steve Nison popularised the idea