Tag: Gaussian

Can We Use Mixture Models to Predict Market Bottoms? (Part 2)

Post Outline * Recap * Model Update * Model Testing * Model Results * Conclusions * Code Recap In the previous post I gave a basic "proof" of concept, where we designed a trading strategy using Sklearn's implementation of Gaussian mixture models. The strategy attempts to predict an asset's return distribution such that returns that fall outside the predicted distribution are considered outliers and likely to mean revert. It showed some promise but had many areas in need of improvement.

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Intro to Expectation-Maximization, K-Means, Gaussian Mixture Models with Python, Sklearn

Post Outline * Part 1 Recap * Part 2 Goals * Jupyter (IPython) Notebook * References part 1 recap In part 1 of this series we got a feel for Markov Models, Hidden Markov Models, and their applications. We went through the process of using a hidden Markov model to solve a toy problem involving a pet dog. We concluded the article by going through a high level quant finance application of Gaussian mixture models to detect historical regimes. part 2 goals In this post, my goal is to impar

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