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Trading strategy ideas using Graph Theory, Tensors and Supervised Learning techniques, developed during the Blackrock Algothon 2019

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AndreasTheodoulou/Blackrock-Algothon-2019

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Algothon-BlackRock-2019

Quantitative trading strategies enhanced with graph-theory (clustering), tensors and XGBoost. Signals were derived from Fundemental, Supply-chain and Sentiment data. Strategy components include risk premia signals, alpha signals, diversification, and risk manamagement.

Ranked as Finalists in the algothon.

Please see the presentation for an overview of our project.

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Trading strategy ideas using Graph Theory, Tensors and Supervised Learning techniques, developed during the Blackrock Algothon 2019

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