Predicting post-merger operating performance with interpretable ML
Can pre-deal firm and transaction information predict post-merger operating performance?
Finding signal without hiding the noise.
Each investigation moves from scattered evidence to a claim that can survive a second look.
Trajectory / four connected practices
From financial questions to empirical systems.
The through-line is not an industry label. It is the work of turning uncertain evidence into something rigorous, inspectable, and useful.
Financial Engineering
A foundation in markets, corporate finance, statistics, and the discipline of testing what a number can support.
M&A / valuation
Questions about transactions and value sharpened the habit of separating an attractive story from measurable operating evidence.
Empirical AI research
Public-data studies now examine how AI capability, adoption, and displacement risk meet firm outcomes and market prices.
Technical building
Research becomes reproducible systems, interactive explanations, and software that keeps assumptions open to inspection.
Selected investigations
Three questions about what the available evidence can actually support.
A change of scale
Evidence becomes a system.
Individual observations gain meaning through relationships, comparison, and uncertainty.
Living Systems
Research is a living system.
The useful result is not a final image. It is a way of seeing that can adapt when the evidence changes.