Delta 1 products are financial instruments that aim to replicate the performance of an underlying asset or index. They require accurate and timely data on the asset's price movements, dividends, interest rates, and other relevant factors. Obtaining and processing such data can be complex, especially when dealing with a wide range of assets or indices. Delta 1 products can still present a data challenge due to the number of rules involved.

The accuracy and quality of the data used to create and manage Delta 1 products are crucial. Errors or discrepancies in the data can result in inaccurate tracking and performance deviations from the underlying asset. Ensuring data accuracy often involves thorough data validation, cleansing, and reconciliation processes.

The client was calculating its P&L and P&L explain in excel across multiple locations. It needed a standard process that worked with and accepted the data nuances across all centres, complicated by a mix of trading and physical processing.

Excel is great. It’s flexible, powerful and quick. In general, it’s the number one choice for ad hoc analysis. But it’s not so good at connecting to data sources, or for large amounts of data or repeatable workflow. And the latter is where we see it so often because it is so flexible and quick to react to the nuances and variations in data. A full revaluation P&L attribution is conceptually simple. Isolate the drivers and re-run the P&L calculation by varying the drivers one at a time. The practical difficulties often arise in getting all the requisite data from different sources and running all the scenarios whilst isolating second order effects. Often, the underlying P&L reporting process is not fully automated or may not allow for multiple scenario data to be generated and then run through it. So parallel excel spreadsheets are made.

Spreadsheets had evolved in different directions to take into account local data nuances and trading conventions.
FIFO waterfall calculation was required to allocate contracts to physical forecasts so variations in scheduling, volumes or planning would change P&L due to phasing.
The P&L model meant that data variations could have upstream and downstream effects.
Management overlay rules created additional second order effects
Fifty to sixty single and pairwise scenarios would typically be required to explain the P&L.