IMC Prosperity 4 algorithmic trading retrospective: strategies, backtester, market microstructure analysis, and round-by-round research notes. Top 0.5% overall.
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Jun 17, 2026 - Jupyter Notebook
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imc-prosperity-4
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Team research repository for IMC Prosperity 4: algorithmic trading, backtesting, manual challenge modeling, and multi-round quantitative strategy development.
python data-analysis game-theory algorithmic-trading backtesting market-microstructure options-trading quantitative-research imc-prosperity-4
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Jun 12, 2026 - HTML
DTU Quant Lab — 28th worldwide (out of 18,803) at IMC Prosperity 4. Trader files, data, dashboard and the literature review behind every shipped strategy.
python quantitative-finance algorithmic-trading backtesting statistical-arbitrage dtu market-making options-pricing imc-prosperity imc-prosperity-4
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Jun 6, 2026 - Python
Our IMC Prosperity 4 entry. Market making, basket arbitrage and Black-Scholes IV strategies in Python. 1,275 of 18,803 teams, reached the final round.
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Aug 19, 2026 - Jupyter Notebook
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