Modern quantitative finance is based around the approach of pattern recognition in historical data. This approach requires teams of scientists to work in a collaborative and regulated setting in order to develop models that can be used to make trading predictions. With the growing influence of this field, both participants and regulators are looking to put in place mechanisms to understand how and why models have been developed, for reasons such as regulatory compliance and model reproducibility. We refer to this tractability problem as lineage.
The challenge of reproducibility and lineage in machine learning (ML) is three-fold: code lineage, data …
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