Use case: Investigating applications of Explainable AI to algorithmic trading

Context:

Study the influence of technical analysis and macroeconomic indicators on the future performance of an underlying asset for Geneva-based quantitative trader.

Objective:

Quantify the predictive power of individual indicators using an interpretable machine learning (ML) algorithm.

Technologies:

  • R, Python

Solution:

A generic R+Python ML framework for forecasting future price projections, using robust cross-validation and back testing strategies.

Precise quantification of individual feature importance via Shapley value ranking.

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