Blazing fast Julia backtester.

Quantitative risk and performance analysis package for financial time series powered by the Julia language.

A transport-agnostic, high-performance, header-only C++23 WebSocket client library with minimal dependencies.

NATS client written in pure Julia.

ClickHouse database client written in native Julia.

Beautiful and intuitive terminal plotting in native Julia.

Julia Dates compatible UNIX timestamps with nanoseconds precision based on Int64 storage type.

Utility functions commonly used in quantitative finance.

Fast binary serialization for C++ and Julia data objects used for IPC and efficient storage.

Fast single-producer, single-consumer queue implementation in Julia.

C++ POSIX IPC based on shared memory and lock-free queues.

An easy-to-use C++20 client for NATS based on the official C client library.

Short-term momentum trading strategy implemented for the lecture "Systematic risk premia strategies traded at hedge funds" at University of Zurich, FS 2018.

Files for course "Modern econometric and statistical learning methods forquantitative asset management" at University of Zurich, taught by Prof. Dr. Marc Paolella, 2020.

Portfolio Optimization using different risk indexation techniques.

Exercise code for lecture "Learning in Deep Artificial and Biological Neuronal Networks" at ETH Zurich, 2019.

Modeling conditional betas with DCC-GARCH and COMFORT-DCC models with application in asset allocation.

Delaunay triangulation and Voronoi diagrams algorithms.