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Showing posts with the label financial engineering

Causal Modeling

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                                                               generated by meta ai Yes. In fact, causal  modelling  is one of the most advanced topics in quantitative finance and is becoming increasingly important because traditional ML models (LSTM, XGBoost, Transformers) often learn  correlations , whereas causal models aim  to discover why prices move. Since I am  pursuing an  MSc in Financial Engineering  at  WQU , I'll teach it at that level, covering  theory, mathematics, and Python implementations. Learning Roadmap We'll build from scratch. Correlation vs Causation Structural Causal Models (SCM) Directed Acyclic Graphs (DAGs) Causal Discovery Algorithms Do-Calculus (Pearl) Counterfactual Prediction Causal Forecasting Applying causal models to stock prediction Building an end-t...