Repository for the explanation method Calibrated Explanations (CE)

Python implementation of binary and multi-class Venn-ABERS calibration

I built a real-time streaming data pipeline using kafka, consuming deribit-api-v2 limit order book prices 📈 and transforming them into an order flow imbalance indicator.

Скрипты для загрузки исторических данных для Deribit

Download Cryptocurrency Option Data from Deribit via public API and stored data in a remote Ubuntu server in an SQLite database.

Repository for the paper "Transformer Conformal Prediction for Time Series"

Books

Hierarchical PCA from Marco Avellaneda

Code for Machine Learning for Algorithmic Trading, 2nd edition.

Use Python like a spreadsheet!

Common functions in actuarial and financial routines

All Jupyter Notebooks implemented by Open Source Modelling in one place.

Python script for calculating the (type I) equity risk solvency capital charge ("SCR") under Solvency II

Python proxy implementation of Solvency 2 (EIOPA) rates module

Data Quality Rules for Solvency 2 and FTK QRTs

Package for reading the Solvency 2 Risk-Free Interest Rate Term Structures and deriving the term structures for alternative extrapolations

Jupyter notebooks for an introduction to F#.

A curated list of free and open source actuarial software

Matlab Notebook for visualizing random matrix theory results and their applications to machine learning

Random Matrix Theory library - RMT analysis and simulation in Python

Python library for Random Matrix Theory, cleaning schemes for correlation matrices, and portfolio optimization

Машинное обучение на ФКН ВШЭ

This project is centred around a Kaggle competition, and seeks to use Machine Learning techniques to create a recommender system. In this competition, H&M Group have invited contributors to make pr…

This project applies market basket analysis to transactional data from Big Bakery in India to identify frequent item sets and association rules using the Apriori algorithm. The results help optimiz…

Market Basket Analysis is one of the key techniques used by large retailers to uncover associations between items. It works by looking for combinations of items that occur together frequently in tr…

Scalable machine 🤖 learning for time series forecasting.

Stochastic volatility models and their application to Deribit crypro-options exchange

A Munch is a Python dictionary that provides attribute-style access (a la JavaScript objects).