Post by Category
AI (2)
What’s in a Name? AI Meets the Sociology of Naming November 17, 2024
[paper] Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models November 2, 2024
HKML (26)
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 1 July 18, 2018
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 1
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 10 May 15, 2019
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 10
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 11 June 12, 2019
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 11
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 12 (Season Finale) July 17, 2019
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 12 (Season Finale)
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 2 August 21, 2018
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 2
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 3 October 9, 2018
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 3
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 4 November 21, 2018
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 4
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 5 December 19, 2018
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 5
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 6 January 23, 2019
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 6
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 7 February 20, 2019
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 7
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 8 March 12, 2019
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 8
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 9 April 17, 2019
[HKML] Hong Kong Machine Learning Meetup Season 1 Episode 9
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 1 September 25, 2019
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 1
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 2 October 17, 2019
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 2
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 3 January 22, 2020
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 3
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 4 April 8, 2020
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 4
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 5 April 29, 2020
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 5
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 6 May 13, 2020
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 6
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 7 June 10, 2020
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 7
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 8 July 15, 2020
[HKML] Hong Kong Machine Learning Meetup Season 2 Episode 8
[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 1 September 30, 2020
[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 1
[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 2 October 8, 2020
[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 2
[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 3 October 28, 2020
[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 3
[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 4 November 4, 2020
[HKML] Hong Kong Machine Learning Meetup Season 3 Episode 4
[HKML] Hong Kong Machine Learning Meetup Season 4 Episode 2 October 27, 2021
[HKML] Hong Kong Machine Learning Meetup Season 4 Episode 2
[HKML] Supercharge your Marketing with Data & ML . [HKML <> IAB] . Off-Season #1 September 5, 2019
[HKML] Supercharge your Marketing with Data & ML . [HKML <> IAB] . Off-Season #1
ML (34)
A Monte Carlo study of the ``Combination of Rankings'' methods August 31, 2018
A Monte Carlo study of the ``Combination of Rankings’’ methods
Combination of Rankings August 16, 2018
Combination of Rankings - A Proper Merging of Experts Views
CorrGAN: A GAN for sampling correlation matrices (Part I) June 23, 2019
CorrGAN: A GAN for sampling correlation matrices (Part I)
CorrGAN: A GAN for sampling correlation matrices (Part II) July 1, 2019
CorrGAN: A GAN for sampling correlation matrices (Part II)
Experimenting with LIME - A tool for model-agnostic explanations of Machine Learning models May 26, 2019
Experimenting with LIME - A tool for model-agnostic explanations of Machine Learning models
Field reports from ICML 2017 in Sydney August 11, 2017
My colleague, Mikolaj Binkowski, at Hellebore Capital was at the 34th International Conference on Machine Learning ICML 2017 in Sydney to represent the comp...
May the Fourth: VADER for Credit Sentiment? May 4, 2019
May the Fourth: VADER for Credit Sentiment?
Permutation invariance in Neural networks September 1, 2019
Permutation invariance in Neural networks
PhD defense - Some contributions to the clustering of financial time series November 11, 2017
Here are the slides. The PhD studies were generously funded by Hellebore Capital.
Reading list of NLP stuff August 24, 2017
General NLP:
Snorkel Credit Sentiment - Part 1 May 1, 2019
First experiment with Snorkel Metal – Credit Sentiment on DataGrapple blogs
Study of US Stocks Correlations, Hierarchies and Clusters July 24, 2017
In this small study, we use hierarchical clustering techniques to explore the structure of correlations between US stocks. To do so, we first download a data...
Stylized Facts of Financial Correlations July 15, 2019
Stylized Facts of Financial Correlations
TF 2.0 DCGAN for 100x100 financial correlation matrices October 13, 2019
TF 2.0 DCGAN for 100x100 financial correlation matrices
TF 2.0 GAN MLP for 100x100 financial correlation matrices September 22, 2019
TF 2.0 GAN MLP for 100x100 financial correlation matrices
Using LIME to 'explain' Snorkel Labeler August 4, 2019
Using LIME to “explain” Snorkel Labeler
[Bloomberg Meetup] The Forefront of Technologies in Finance September 1, 2018
[Bloomberg Meetup] The Forefront of Technologies in Finance
[Book] Neural Network Methods for Natural Language Processing September 20, 2018
[Book] Neural Network Methods for Natural Language Processing
[Clustering] How and Where should you cut a dendrogram? May 12, 2017
[Clustering] How to sort a distance matrix September 7, 2017
Following the Ecole Polytechnique - Data Science Summer School where I got several times questions about how I produced the sorted correlation matrices disp...
[Field report] Data Science Summer School at Ecole Polytechnique (with Bengio, Russell, Bousquet, Archambeau and others) September 2, 2017
A small field report with personal viewpoint about the Data Science Summer School (Ecole Polytechnique) Monday, Aug. 28 – Friday, Sept. 1, 2017.
[ICML 2018] Day 1 - Tutorials July 10, 2018
[ICML 2018] Day 1 - Tutorials
[ICML 2018] Day 2 - Representation Learning, Networks and Relational Learning July 11, 2018
[ICML 2018] Day 2 - Representation Learning, Networks and Relational Learning
[ICML 2018] Day 3 - Energy, GANs, Rankings, Curriculum Learning, and our paper July 12, 2018
[ICML 2018] Day 3 - Energy, GANs, Rankings, Curriculum Learning, and our paper
[ICML 2018] Day 4 - Time-Series Analysis, NLP, and More Human-like Learning Machines July 13, 2018
[ICML 2018] Day 4 - Time-Series Analysis, NLP, and More Human-like Learning Machines
[ICML 2018] Retrospectives July 16, 2018
[ICML 2018] Retrospectives
[ICML 2019] Day 1 - Tutorials June 11, 2019
[ICML 2019] Day 1 - Tutorials
[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 June 11, 2019
[ICML 2019] Day 2 - U.S. Census, Time Series, Hawkes Processes, Shapley values, Topological Data Analysis, Deep Learning & Logic, Random Matrices, Optima...
[ICML 2019] Day 3 - Robotics, Good ol' Sparse Coding, misc. applications, Transfer, Multitask and Active Learning June 12, 2019
[ICML 2019] Day 3 - Robotics, Good ol’ Sparse Coding, misc. applications, Transfer, Multitask and Active Learning
[ICML 2019] Day 4 - Interpretability, Natural Language Processing, Smarter than AI four year old kids, Unsupervised Learning June 13, 2019
[ICML 2019] Day 4 - Interpretability, Natural Language Processing, Smarter than AI four year old kids, Unsupervised Learning
[ICML 2019] Day 5 - Workshop Time Series June 14, 2019
[ICML 2019] Day 5 - Workshop Time Series
[ICML 2019] Reading list of accepted papers May 19, 2019
[ICML 2019] Reading list of accepted papers
``Combination of Rankings'' - The Full Coverage Case September 2, 2018
``Combination of Rankings’’ - The Full Coverage Case
``Combination of Rankings'' - The Stationary Distribution September 5, 2018
``Combination of Rankings’’ - The Stationary Distribution
aws (1)
AWS S3 to Lambda to Aurora to Lambda to Binance | Serverless architecture for crypto trading December 17, 2022
business (1)
Bayesian Networks for Business: Modeling Profit and Loss of a Cafe in Hong Kong October 14, 2024
cryptocurrency (2)
APIs for getting crypto related data May 14, 2018
Following my blog post Download & Play with Cryptocurrencies Historical Data in Python, I got several times questions on how to get the historical data. ...
Download & Play with Cryptocurrencies Historical Data in Python August 25, 2017
To access the CryptoCompare public API in Python, we can use the following Python wrapper available on GitHub: cryCompare.
deep learning (3)
Neural Style Transfer applied to paintings June 23, 2018
In this short blog, we apply the fast style transfer as implemented in tensorflow/magenta.
On the difficulty of reading numbers in different languages June 25, 2018
On the difficulty of reading numbers in different languages
[Paper + Experimentation] CartoonGAN applied to Hong Kong landscapes using Streamlit March 22, 2020
ethereum (3)
Ether vs. Bitcoin -- Part 0 June 22, 2017
In this introduction notebook, we simply displayed the distribution of the returns and see that tails are heavy, meaning that standard quant models cannot be...
Ether vs. Bitcoin -- Part 0 bis June 28, 2017
For the last few days, ETH has lost 1/3 of its value with -20% several days in a row. We update the initial study with up-to-date data to take into account t...
June Ethereum London Meetup at Imperial College June 16, 2017
I attended this evening the June Ethereum London Meetup at Imperial College (I have been there a couple of times before). Imperial College’s big amphitheater...
healthtech (1)
Physiological analytics for sports March 4, 2018
I recently got a Garmin Forerunner 935 (advised by a good friend of mine). After using it for two months, I can say that I’m happy with it so far. It has lot...
math (1)
How to define an intrisic Mean of Correlation Matrices in a Riemannian sense? December 25, 2019
ml (17)
AutoGL and the Open Graph Benchmark: Datasets for Machine Learning on Graphs January 2, 2021
Bayesian net and Boparan 7.625% 30 Nov 2025 Prospectus May 16, 2022
Classification of Correlation Matrices using SPDNet with Riemannian Batch Normalization January 22, 2021
Illustration from "A Riemannian Network for SPD Matrix Learning" https://arxiv.org/pdf/1608.04233.pdf
Conditional CorrGAN: An example in Google Colab February 5, 2021
A few cCorrGAN-generated correlation matrices, and the confusion matrix of a SPDNet + RBN classification.
Crypto PCA First Eigenvector September 17, 2022
Getting ready for Complex Networks 2022 in Palermo, Italy November 5, 2022
Hierarchical PCA x Hierarchical clustering on crypto perpetual futures September 17, 2022
Mind the Jensen Gap! April 10, 2021
Preparing for ICML 2024: Main themes June 22, 2024
Selected ML Papers from ICML 2023 July 9, 2023
Speaker identification in 'Marine Le Pen vs. Emmanuel Macron 2017 French Presidential Debate' April 20, 2022
Standard readability measures (applied on Shakespeare's plays) February 19, 2022
Takeaways from Complex Networks 2022 in Palermo, Italy November 13, 2022
The Swelling Effect: Think twice before averaging covariance matrices February 13, 2021
A few ellipsoids representing the associated covariance matrices along the geodesic path from the leftmost to the rightmost matrices.
[Paper] Summary of 'Explaining by Removing: A Unified Framework for Model Explanation' December 3, 2020
Illustration from Explaining by Removing: A Unified Framework for Model Explanation
[Paper] Summary of 'Interpretable Machine Learning – A Brief History, State-of-the-Art and Challenges' January 9, 2021
[Paper] Summary of Interpretable Machine Learning – A Brief History, State-of-the-Art and Challenges
[paper] Top2Vec: Distributed Representations of Topics November 14, 2021
with application on 2020 10-K business descriptions
networks (1)
How to compute the Planar Maximally Filtered Graph (PMFG) June 3, 2018
How to compute the Planar Maximally Filtered Graph (PMFG)
qfin (33)
Can we predict a market regime from correlation matrix features? September 4, 2020
Clustering Marginal Distributions of Stocks Returns, and Sampling from their Wasserstein Barycenter July 29, 2020
Comparison of Network-based and Minimum Variance Portfolios Using CorrGAN December 21, 2019
Comparison of Network-based and Minimum Variance Portfolios Using CorrGAN
CopulaGAN (the 3d case) - A first naive attempt August 1, 2020
CorrVAE: A VAE for sampling realistic financial correlation matrices (Tentative I) February 4, 2020
CorrVAE: A VAE for sampling realistic financial correlation matrices (Tentative I)
CorrVAE: A VAE for sampling realistic financial correlation matrices (Tentative II) February 17, 2020
CorrVAE: A VAE for sampling realistic financial correlation matrices (Tentative II)
Extraction of features from a given correlation matrix August 14, 2020
Hierarchical Risk Parity - Implementation & Experiments (Part I) October 2, 2018
Hierarchical Risk Parity - Implementation & Experiments (Part I)
Hierarchical Risk Parity - Implementation & Experiments (Part II) October 15, 2018
Hierarchical Risk Parity - Implementation & Experiments (Part II)
Hierarchical Risk Parity - Implementation & Experiments (Part III) December 4, 2019
Hierarchical Risk Parity - Implementation & Experiments (Part III)
How to combine a handful of predictors using empirical copulas and maximum likelihood August 9, 2020
How to detect false strategies? The Deflated Sharpe Ratio May 30, 2018
Deflated Sharpe Ratio
Measuring non-linear dependence with Optimal Transport June 25, 2020
Mutual Information Is Copula Entropy July 1, 2020
Network-based vs. Minimum Variance portfolios: Any deep connections? October 10, 2018
Network-based vs. Minimum Variance portfolios: Any deep connections?
Portfolio construction methods and risk metrics: in- and out-of-sample comparisons on simulated data August 15, 2020
Quick correlation study between BTC/USD and ETH/USD August 22, 2017
import numpy as np import scipy import pandas as pd import matplotlib.pyplot as plt %matplotlib inline import seaborn as sns import json from datetime import...
Release of a few pretrained CorrGAN models August 11, 2020
Release of a few pretrained CorrGAN models
S&P 500 Sharpe vs. Correlation Matrices - Building a dataset for generating stressed/rally/normal scenarios February 3, 2020
S&P 500 Sharpe vs. Correlation Matrices - Building a dataset for generating stressed/rally/normal scenarios
Sampling from Empirical Copulas of Stocks July 28, 2020
Some further assessment of the original CorrGAN model (2019) December 18, 2020
Swap Data Repositories for Credit Default Swaps May 28, 2017
What are Swap Data Repositories?
Wasserstein Barycenters of Stocks Empirical Copulas July 26, 2020
Which portfolio allocation method to choose? Look at the correlation matrix! August 17, 2020
[Active Reading with ChatGPT] Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage May 28, 2023
[Active Reading with ChatGPT] Systematic Investing in Credit June 3, 2023
[Book] Advanced Portfolio Management -- A Quant's Guide for Fundamental Investors November 29, 2021
[Book] Commented summary of Machine Learning for Asset Managers by Marcos Lopez de Prado April 12, 2020
[Book] Commented summary of Machine Learning for Factor Investing by Guillaume Coqueret and Tony Guida May 19, 2020
[Book] Commented summary of Probabilistic Graphical Models -- A New Way of Thinking in Financial Modelling August 30, 2020
[Book] Volatility Trading April 30, 2023
[Paper + Implementation] Hierarchical PCA and Applications to Portfolio Management July 5, 2020
[Paper + Implementation] The Hierarchical Equal Risk Contribution Portfolio (Part I) March 22, 2020
[Paper + Implementation] The Hierarchical Equal Risk Contribution Portfolio (Part I)
quant (16)
AQR Academic Factors February 17, 2018
AQR has released an implementation of the well-known academic factors in its AQR Data Library:
Back to basics: PCA on stocks returns December 11, 2021
Basic DSPy RAG tutorial on DataGrapple blog posts April 16, 2024
Basic DSPy RAG tutorial on DataGrapple blog posts
Building a S&P 500 company classification from Wikipedia articles (guided by ChatGPT) May 7, 2023
Embeddings of Sectors and Industries using Graph Neural Networks August 13, 2021
node2vec embeddings of industries projected onto the 2d plane
From Fundamental To Quantamental Investing November 11, 2020
Naive modelling of Matalan defaulting on its MTNLN 9.5 01/31/24 Notes February 8, 2022
Naive modelling of credit defaults using a Markov Random Field January 30, 2022
Performance attribution of a crypto market-neutral book on a statistical risk model February 27, 2023
Prompting is Programming with LMQL February 11, 2024
Quant Blogs February 13, 2018
Here a tentative of a list of interesting blogs to keep up with quant best practices to study financial markets. I hope that my readers will help me curate t...
SetFit: Fine-tuning a LLM in 10 lines of code and little labeled data March 11, 2023
Some Thoughts on the Applications of Deep Generative Models in Finance September 27, 2020
[Book] Interview with ChatGPT about its book 'From Data to Trade: A Machine Learning Approach to Quantitative Trading' January 4, 2023
[Book] The UnRules - Man, Machines and the Quest to Master Markets October 16, 2018
[Book] The UnRules - Man, Machines and the Quest to Master Markets
[Paper] A Backtesting Protocol in the Era of Machine Learning December 9, 2018
[Paper] A Backtesting Protocol in the Era of Machine Learning
stats (4)
How to sample uniformly over the space of correlation matrices? The onion method October 5, 2018
How to sample uniformly over the space of correlation matrices? The onion method
Riemannian Geometry of Correlation Matrices November 13, 2017
Research material:
Tail Dependence Coefficients December 4, 2017
Research material:
[Correlation] How to visualize dependence between two variables? November 5, 2017
In this blog, we provide a snippet of code to explore the dependence between two variables. We illustrate its use on visualizing the dependence between a few...