Automatically linking fixed income and equity data

Qudol unlocks value across the organization by algorithmically deep-linking fixed income and equity data, helping to enhance research and portfolio construction.

Rick Johnson

For asset managers, missing the deep links across history between fixed income and equity instruments poses two key concerns:

  • Limited access to research across asset classes: Typically, fixed income teams have limited access to equity research, especially when company names and identifiers change over time due to corporate action.
  • Higher risk exposure to single companies: Incomplete linkages across asset classes can mean greater than intended exposure to specific companies.

Earlier this year, we launched Security Master in the cloud to tackle data challenges like these. Qudol Security Master simplifies data operations by providing deep linkages across history and asset classes, providing customers with a more complete picture of their data, research, and portfolios. Qudol Security Master generates linking identifiers (QUIDs) to unravel complex, nested hierarchies across multiple records, time periods, vendor identifiers, and asset classes.


Key Benefits of Linking Across Asset-Classes:

  • Access to Research: Linking fixed income and equity instruments - often issued by multiple subsidiaries with unique names and identifiers - allows for better research and analytics across asset classes.
  • Portfolio Construction: Optimal asset distribution is a complex process; Qudol Security Master takes care of the data so you can focus on what really matters.
  • Risk Control: Gain a better understanding of your total exposure to each investment across asset classes.

Case Study: Ford Motor and Ford Credit

Let's first look at a relatively simple example: Ford.

Ford Motor Company and Ford Motor Credit Company are well-known entities: the first sells cars, and the latter is its financial services arm (subsidiary). Because their businesses are inextricably linked, many asset managers would likely want to consider both equity and fixed income research at the same time.

However, data for Ford Motor and Ford Credit are associated with different organization identifiers. Additionally, Ford Motor's equity instruments have different display names, identifiers, and historical availability across different data vendors. Qudol solves this issue in three simple steps:

  1. Algorithmically links all equity instrument records across time for Ford Motor.
  2. Algorithmically links all fixed income instrument records across time for Ford Credit.
  3. Builds a cross-asset-class map between Ford Motor and Ford Credit using data from a combination of data vendors.

* Identifiers have been hidden for compliance. Names may be fictitious, but are representative and meaningful.

The result is simple but powerful: Qudol Security Master provides nested, hierarchical relationship between all records through the QUID. Qudol has the intelligence to break down walls in the data assets that you already own. The properties and identifiers from each individual data source is insufficient for full linkage, but Qudol can figure it out, automatically and continuously.

Wasn't that too obvious?

Ford Motor is a relatively simple example of linking across asset classes. In reality, fixed income investors are obviously going to know that Ford Credit is associated with the parent automobile manufacturing company.

Not everything is so clear cut, however. Here's another example - take a look at AEP in a dataset that I recently worked with:


* Identifiers have been hidden for compliance. Names may be fictitious, but are representative and meaningful.

I've provided asset display names here to provide a visualization of corporate actions, regulatory enforcement, and legal entity names over time that impacted both asset classes. By this point, Qudol has already reconciled all of the historical data for AEP within each asset class. Qudol then builds the links across fixed income and equity data, building the complete picture.

In a complete dataset, we may see thousands of examples like this, including even more complex ones. Qudol Security Master takes care of them algorithmically and automatically, allowing research and analytics teams to focus on what matters.

Furthermore, we benefit from more-informed risk control and portfolio construction. With deep linkages, we can understand cumulative risk exposure to a single company across all financial instruments, even if it's a combination of bonds from Indiana Michigan Power Co, bonds from Appalachian Power Co, and equity positions in AEP.

These are just a few select examples that I've seen recently - please feel free to get in touch any time if you have any questions.

Rick Johnson
Research at Qudol

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