Blog
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Basic DSPy RAG tutorial on DataGrapple blog posts
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Prompting is Programming with LMQL
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Selected ML Papers from ICML 2023
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[Active Reading with ChatGPT] Systematic Investing in Credit
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[Active Reading with ChatGPT] Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage
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Building a S&P 500 company classification from Wikipedia articles (guided by ChatGPT)
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[Book] Volatility Trading
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SetFit: Fine-tuning a LLM in 10 lines of code and little labeled data
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Performance attribution of a crypto market-neutral book on a statistical risk model
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[Book] Interview with ChatGPT about its book 'From Data to Trade: A Machine Learning Approach to Quantitative Trading'
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AWS S3 to Lambda to Aurora to Lambda to Binance | Serverless architecture for crypto trading
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Takeaways from Complex Networks 2022 in Palermo, Italy
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Getting ready for Complex Networks 2022 in Palermo, Italy
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Hierarchical PCA x Hierarchical clustering on crypto perpetual futures
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Crypto PCA First Eigenvector
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Bayesian net and Boparan 7.625% 30 Nov 2025 Prospectus
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Speaker identification in 'Marine Le Pen vs. Emmanuel Macron 2017 French Presidential Debate'
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Standard readability measures (applied on Shakespeare's plays)
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Naive modelling of Matalan defaulting on its MTNLN 9.5 01/31/24 Notes
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Naive modelling of credit defaults using a Markov Random Field
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Back to basics: PCA on stocks returns
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[Book] Advanced Portfolio Management -- A Quant's Guide for Fundamental Investors
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[paper] Top2Vec: Distributed Representations of Topics
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[HKML] Hong Kong Machine Learning Meetup Season 4 Episode 2
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Embeddings of Sectors and Industries using Graph Neural Networks
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Mind the Jensen Gap!
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The Swelling Effect: Think twice before averaging covariance matrices
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Conditional CorrGAN: An example in Google Colab
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Classification of Correlation Matrices using SPDNet with Riemannian Batch Normalization
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[Paper] Summary of 'Interpretable Machine Learning – A Brief History, State-of-the-Art and Challenges'
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AutoGL and the Open Graph Benchmark: Datasets for Machine Learning on Graphs
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Some further assessment of the original CorrGAN model (2019)
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[Paper] Summary of 'Explaining by Removing: A Unified Framework for Model Explanation'
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From Fundamental To Quantamental Investing
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[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 4
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[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 3
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[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 2
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[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 1
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Some Thoughts on the Applications of Deep Generative Models in Finance
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Can we predict a market regime from correlation matrix features?
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[Book] Commented summary of Probabilistic Graphical Models -- A New Way of Thinking in Financial Modelling
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Which portfolio allocation method to choose? Look at the correlation matrix!
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Portfolio construction methods and risk metrics: in- and out-of-sample comparisons on simulated data
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Extraction of features from a given correlation matrix
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Release of a few pretrained CorrGAN models
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How to combine a handful of predictors using empirical copulas and maximum likelihood
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CopulaGAN (the 3d case) - A first naive attempt
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Clustering Marginal Distributions of Stocks Returns, and Sampling from their Wasserstein Barycenter
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Sampling from Empirical Copulas of Stocks
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Wasserstein Barycenters of Stocks Empirical Copulas
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[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 8
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[Paper + Implementation] Hierarchical PCA and Applications to Portfolio Management
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Mutual Information Is Copula Entropy
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Measuring non-linear dependence with Optimal Transport
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[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 7
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[Book] Commented summary of Machine Learning for Factor Investing by Guillaume Coqueret and Tony Guida
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[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 6
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[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 5
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[Book] Commented summary of Machine Learning for Asset Managers by Marcos Lopez de Prado
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[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 4
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[Paper + Implementation] The Hierarchical Equal Risk Contribution Portfolio (Part I)
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[Paper + Experimentation] CartoonGAN applied to Hong Kong landscapes using Streamlit
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CorrVAE: A VAE for sampling realistic financial correlation matrices (Tentative II)
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CorrVAE: A VAE for sampling realistic financial correlation matrices (Tentative I)
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S&P 500 Sharpe vs. Correlation Matrices - Building a dataset for generating stressed/rally/normal scenarios
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[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 3
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How to define an intrisic Mean of Correlation Matrices in a Riemannian sense?
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Comparison of Network-based and Minimum Variance Portfolios Using CorrGAN
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Hierarchical Risk Parity - Implementation & Experiments (Part III)
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[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 2
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TF 2.0 DCGAN for 100x100 financial correlation matrices
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[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 1
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TF 2.0 GAN MLP for 100x100 financial correlation matrices
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[HKML] Supercharge your Marketing with Data & ML . [HKML <> IAB] . Off-Season #1
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Permutation invariance in Neural networks
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Using LIME to 'explain' Snorkel Labeler
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 12 (Season Finale)
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Stylized Facts of Financial Correlations
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CorrGAN: A GAN for sampling correlation matrices (Part II)
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CorrGAN: A GAN for sampling correlation matrices (Part I)
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[ICML 2019] Day 5 - Workshop Time Series
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[ICML 2019] Day 4 - Interpretability, Natural Language Processing, Smarter than AI four year old kids, Unsupervised Learning
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[ICML 2019] Day 3 - Robotics, Good ol' Sparse Coding, misc. applications, Transfer, Multitask and Active Learning
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 11
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[ICML 2019] Day 2 - U.S. Census, Time Series, Hawkes Processes, Shapley values, Topological Data Analysis, Deep Learning & Logic, Random Matrices, Optimal Transport for Graphs
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[ICML 2019] Day 1 - Tutorials
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Experimenting with LIME - A tool for model-agnostic explanations of Machine Learning models
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[ICML 2019] Reading list of accepted papers
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 10
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May the Fourth: VADER for Credit Sentiment?
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Snorkel Credit Sentiment - Part 1
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 9
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 8
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 7
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 6
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 5
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[Paper] A Backtesting Protocol in the Era of Machine Learning
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 4
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[Book] The UnRules - Man, Machines and the Quest to Master Markets
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Hierarchical Risk Parity - Implementation & Experiments (Part II)
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Network-based vs. Minimum Variance portfolios: Any deep connections?
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 3
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How to sample uniformly over the space of correlation matrices? The onion method
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Hierarchical Risk Parity - Implementation & Experiments (Part I)
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[Book] Neural Network Methods for Natural Language Processing
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``Combination of Rankings'' - The Stationary Distribution
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``Combination of Rankings'' - The Full Coverage Case
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[Bloomberg Meetup] The Forefront of Technologies in Finance
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A Monte Carlo study of the ``Combination of Rankings'' methods
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 2
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Combination of Rankings
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[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 1
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[ICML 2018] Retrospectives
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[ICML 2018] Day 4 - Time-Series Analysis, NLP, and More Human-like Learning Machines
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[ICML 2018] Day 3 - Energy, GANs, Rankings, Curriculum Learning, and our paper
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[ICML 2018] Day 2 - Representation Learning, Networks and Relational Learning
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[ICML 2018] Day 1 - Tutorials
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On the difficulty of reading numbers in different languages
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Neural Style Transfer applied to paintings
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How to compute the Planar Maximally Filtered Graph (PMFG)
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How to detect false strategies? The Deflated Sharpe Ratio
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APIs for getting crypto related data
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Physiological analytics for sports
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AQR Academic Factors
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Quant Blogs
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Tail Dependence Coefficients
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Riemannian Geometry of Correlation Matrices
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PhD defense - Some contributions to the clustering of financial time series
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[Correlation] How to visualize dependence between two variables?
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[Clustering] How to sort a distance matrix
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[Field report] Data Science Summer School at Ecole Polytechnique (with Bengio, Russell, Bousquet, Archambeau and others)
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Download & Play with Cryptocurrencies Historical Data in Python
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Reading list of NLP stuff
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Quick correlation study between BTC/USD and ETH/USD
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Field reports from ICML 2017 in Sydney
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Study of US Stocks Correlations, Hierarchies and Clusters
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Ether vs. Bitcoin -- Part 0 bis
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Ether vs. Bitcoin -- Part 0
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June Ethereum London Meetup at Imperial College
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Swap Data Repositories for Credit Default Swaps
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[Clustering] How and Where should you cut a dendrogram?
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