Antonov’s latest paper, co-authored with Lopez de Prado and Adia’s co-head of quant R&D Alexander Lipton, compares HRP with the original Markowitz method and finds that it produces more robust risk ...

Alexandre Antonov, Alexander Lipton and Marcos Lopez de Prado compare and contrast two portfolio allocation methods: the classical Markowitz approach and the hierarchical risk parity (HRP) approach.

Inspired by high-dimensional data and the ideals of open science, high-energy physicists are using artificial intelligence to ...

Covariance matrix: A matrix that describes the variance and covariance between multiple variables, indicating how much the variables change together. Power of a test: The probability that the test ...

Our method involves reconstructing the covariance matrix using the proposed CNN model, which is trained with covariance matrices from the actual received signals to their corresponding covariance ...

This code is used to demonstrate the results/figures of the paper: 'Achieving Oracle Property for Low-rank Covariance Matrix Estimation from Quadratic Measurements'.

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Dr. JeFreda R. Brown is a financial ...

Positive definite matrices are widely used in machine learning and probabilistic modeling, especially in applications related to graph analysis and Gaussian models. It is not uncommon that positive ...

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