Transfer Entropy Causality - Quant Researcher Interview Question
Difficulty: Hard
Category: machine_learning
Asked at: Citadel, WorldQuant, Two Sigma, Citadel Securities, JPMorgan, AQR Capital Management, Man Group
Topics: information_theory, time_series, causality, statistics
Problem Description
Identifying non-linear causal relationships between assets is crucial for pairs trading, lead-lag analysis, and market microstructure. Transfer Entropy (TE) is a non-parametric measure based on information theory that quantifies directed, asymmetric information transfer between time series, capturing relationships that standard correlation misses.
Task
Implement a function solution that calculates the Transfer Entropy from a source time series prices_x to a target time series prices_y. The calc
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