Case study · Asset management

Cross-asset research platform

Pipelines and Dash apps that give a sovereign wealth fund’s bonds and FX researchers one place to pull, compare and backtest market data.

Client: Research desk at a sovereign wealth fund
Result: In daily use by research and trading for 3+ years
Stack: Bloomberg BQL/BQuant, Macrobond, Apache Airflow, Python, Plotly Dash

The problem

The research team covering sovereign bonds and FX worked across Bloomberg, Macrobond and internal datasets by hand. Every new question started with re-pulling and re-joining the same data.

The work

BQL/BQuant data apps that pull the series analysts need, on demand.
Apache Airflow pipelines that bring Bloomberg, Macrobond and internal market data into one research store.
Plotly Dash apps for portfolio drill-downs and scenario analysis.
Backtesting and forecasting workflows for sovereign-bond and FX research.
Research agents that assemble the morning market brief.

Outcome

Research and trading teams have used the platform daily for more than three years. The data work now happens once, in the pipelines.

The client isn’t named, to respect confidentiality. I can share more detail on a call where permitted.

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