Learning from People Who Actually Do This Work
Investment research isn't something you pick up from textbooks alone. It's shaped by years spent tracking market movements, making calls that don't always work out, and figuring out what matters when everything's moving at once.
Our teaching approach comes from that experience. Not theory first, then practice. We start with what's happening right now in the markets and work backward to understand why it matters.
Eamonn Devereux
Research Lead
Teaching Through Real Market Context
Start with Current Events
Eamonn doesn't begin with historical case studies. His sessions start with what moved markets this week. Could be a central bank announcement, an earnings surprise, or something geopolitical. Then we dig into the research process that helps make sense of it.
Show the Messy Parts
Most courses show you the perfect analysis that led to the right call. That's not useful. Eamonn walks through the analyses that didn't pan out, the signals that were misleading, the times when the obvious answer turned out wrong. That's where the learning happens.
Build Your Own Framework
There's no single method that works for everyone. Some people are better with quantitative models. Others have stronger instincts for qualitative factors. The goal is helping you figure out which approach fits how your brain actually works, then strengthening that.
What's Changing in Investment Research
The field keeps evolving. Here's what we're seeing shape the work in 2025 and why it matters for anyone learning this craft.
Alternative Data Integration
Satellite imagery, credit card data, web traffic patterns. Sources that didn't exist ten years ago are now standard. Learning to assess which data actually matters and which is just noise takes practice.
Regulatory Complexity
ESG reporting requirements, disclosure rules, sustainability frameworks. The compliance side of research work has gotten more involved. Understanding what companies have to report versus what they choose to report reveals a lot.
Cross-Border Dynamics
Markets don't respect borders anymore. A policy change in Brussels affects Irish equities. Supply chain issues in Asia impact European industrials. Research has to account for these connections constantly.
How We Structure Learning
This isn't a lecture series. It's a progression through increasingly complex research scenarios with guidance at each stage.
Information Gathering
Learn where to find reliable data sources and how to quickly assess credibility. Regulatory filings, management communications, industry reports. We show you what experienced researchers check first and why those sources matter more than others.
Pattern Recognition
After you've seen enough quarterly reports, certain patterns emerge. Management teams that consistently deliver versus those that make excuses. Financial metrics that signal trouble before it's obvious. This takes time and repeated exposure to develop.
Hypothesis Testing
Form an investment thesis, then actively try to prove yourself wrong. What could break this company's business model? What assumptions are you making that might not hold? Good research means questioning your own conclusions before anyone else does.
Communication Skills
Analysis is only half the job. You need to present findings clearly to people who don't have time for lengthy explanations. Write concise investment memos. Present recommendations that focus on what matters. Defend your conclusions when challenged.
Building Research Judgment Over Time
Technical skills are learnable. Financial modeling, data analysis, industry research methods. Those take a few months to get competent at.
Research judgment takes longer. Knowing when a sell-side report is genuinely insightful versus just well-written. Recognizing when market consensus is probably right versus when it's missing something. Understanding which management teams you can trust.
Active Learning Approach
Our autumn 2025 program runs through live market scenarios. You'll track actual companies, write real research notes, present to your cohort. Get feedback not just on technical accuracy but on whether your reasoning makes sense to experienced practitioners.
Long-Term Development
The program is intensive but it's not meant to make you an expert in six months. It's meant to give you the foundation and the feedback loops you need to keep improving on your own. Most participants stay in touch afterward because that ongoing discussion is valuable.
