Blackswanquants
This Organization contains the repositories of projects developed by the programmers team in the BlackswanQuants Student Organization.
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If you're a new member and you have access to the organization, read this guide for new programmers.
If you're just a visitor, check out some of our projects:
A quantitative research project focused on detecting and characterizing market regimes through Hidden Markov Models applied to financial time series. Project in collaboration with Polimi Data Scien…
Jupyter Notebook 5
Project based on analysing causal impact and LSTM sinergies in the NASDAQ
Project to develop a Python pricing engine for European options using the Fast Fourier Transform (FFT). The goal is to value options using the characteristic function, overcoming model limitations …
Jupyter Notebook 2
Using the S&P 500 dataset, this paper applies dynamic time warping (DTW) to analyze shifting lead-lag relationships in economic time series.
This analysis uses natural language processing (NLP) to assess the impact of central bank communications on the economy, capturing insights into policy effects and market responses.
Reproducible implementation and extension of an intraday momentum strategy on SPY + QuantConnect-ready research framework.
Jupyter Notebook 1
Project to develop a Python pricing engine for European options using the Fast Fourier Transform (FFT). The goal is to value options using the characteristic function, overcoming model limitations (e.g., Black-Scholes) and extending analysis to more realistic models like Heston or Merton.
Recreate and professionalize a Hurst-filtered RSI pullback strategy in Python, validated via Walk-Forward Analysis
A quantitative research project focused on detecting and characterizing market regimes through Hidden Markov Models applied to financial time series. Project in collaboration with Polimi Data Scientists.
Reproducible implementation and extension of an intraday momentum strategy on SPY + QuantConnect-ready research framework.
This repository contains the two projects developed by our teams during the AI Hackathon organized by GDG (Google Developer Groups) in Milan, may 2025.
Project based on analysing causal impact and LSTM sinergies in the NASDAQ
A comprehensive collection of algorithmic trading strategies developed by our team, including research implementations, competition submissions, and relevant academic papers.
Using the S&P 500 dataset, this paper applies dynamic time warping (DTW) to analyze shifting lead-lag relationships in economic time series.
A repository with the modules containing helper modules for specific tasks within our projects
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