Research team discussing pension funding data

Who We Are and Why We Care

A small team obsessed with one question: why do some pension funds quietly predict which firms thrive?

You have seen the headlines about underfunded pensions and market swings. We started in a cramped seminar room, arguing over spreadsheets, convinced the connection between the two was hiding in plain sight. That argument became a methodology, then a platform, then a community of analysts who refuse to accept that pension data is just background noise.

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From Academic Curiosity to Practical Insight

What began as a late-night debate over coffee-stained printouts has grown into a resource trusted by institutional analysts who need clarity, not cheerleading.

The Original Question

You are looking at two firms in the same sector. One runs a pension surplus; the other carries a gaping deficit. Conventional wisdom says this is an accounting footnote. We asked: what if it is a signal? Our earliest work tested whether cross-sectional differences in pension funding status could predict relative stock performance. The results were noisy, occasionally contradictory, and genuinely fascinating.

Building the Dataset

You cannot test a hunch without clean data. We spent eighteen months reconciling footnotes from annual reports, regulatory filings, and actuarial disclosures. The process was tedious, occasionally maddening, and absolutely necessary. That dataset became the backbone of every analysis we publish today.

Opening the Conversation

You deserve to see the methodology, not just the conclusion. We started sharing our findings at small industry gatherings, expecting polite skepticism. Instead, we found analysts asking harder questions than we had asked ourselves. That dialogue reshaped our approach and continues to drive our work.

Where We Are Now

You are reading this on a platform that exists because institutions kept asking for deeper, more accessible pension analytics. We are still a lean team. We still argue over spreadsheets. And we still believe that understanding pension funding effects is not a niche concern; it is central to understanding modern corporate risk.

What Guides Our Work

We are not selling certainty. We are offering a framework, tested, challenged, and refined through use.

You should expect every claim to carry a citation, every model to disclose its assumptions, and every conclusion to acknowledge its limitations. We do not polish away the uncertainty; we map it.
Independence: You might never meet the retiree whose pension depends on the funding decisions we analyze. We keep that person in mind. Good research should ultimately protect the people counting on these systems.

The People Behind the Analysis

Dr. Eleanor Vance

Lead Research Director

Eleanor spent a decade in academic finance before deciding that the most interesting questions were buried in corporate footnotes. She oversees our analytical framework and still manually checks the first draft of every major report.

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Marcus O'Brien

Head of Data Operations

Marcus built the infrastructure that turns thousands of annual reports into a queryable dataset. He is suspicious of any number he did not verify himself and believes the best insight often hides in the reconciliation table.

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Sarah Lin

Senior Quantitative Analyst

Sarah translates our research into models that institutions can stress-test against their own portfolios. She is the reason our findings leave the page and enter actual decision-making workflows.

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David Okafor

Editorial and Outreach Lead

David ensures our analysis is readable without being dumbed down. He manages our relationships with institutional readers and insists that every report pass the 'explain this to a skeptical colleague' test before publication.

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Recognition and Citations

2023

IPEPA

Research Excellence Award

Honored for sustained contributions to empirical pension finance research and open methodology disclosure practices.

2021

EFMA

Best Paper Citation

Recognized for advancing understanding of cross-sectional pension funding effects on equity risk premiums.

2022

SFI

Data Transparency Prize

Awarded for pioneering open-source pension liability dataset construction and peer-review integration.

2024

Pensions Europe

Institutional Impact Award

Acknowledged for research directly informing pension fund board discussions across European markets.

Contact

How to Reach Us

Whether you have a methodological question, a dataset inquiry, or a partnership idea, we read every message. Response times vary, but thoroughness does not.

Phone: +353-21-463-8682
Email: content@latarteistie.world
Office: The Plaza, East Point Business Park Dublin 3 D03 E5R6, Ireland