Investment research perspectives for the private investor who wants to think more clearly about markets, companies and decisions.
Investment research has never been more information-rich or more analytically demanding. The volume of data available to a private investor today would have been unimaginable a generation ago — but volume alone does not produce clarity. The challenge is not finding information; it is knowing which information is material, how to place it in context and what it actually implies for the investment decisions you are facing. That is the territory this publication explores.
The Resquinalen Insights blog is written for investors who want to think more rigorously about how they research. Each piece focuses on a specific dimension of investment analysis — how to read a market signal, how to stress-test a scenario, how to examine the assumptions embedded in a valuation, how to maintain analytical discipline when sentiment is running hard in one direction. The aim is not to tell you what to think about any particular company or market. It is to sharpen the thinking tools you bring to your own research.
You will not find recommendations here, and you will not find invented figures dressed up as evidence. What you will find is considered, honest writing about the craft of investment research — the habits, frameworks and questions that help a serious private investor arrive at views that are genuinely their own. Resquinalen does not replace professional financial advice, and nothing published here should be read as a substitute for it. What it offers is a more rigorous way of thinking before you decide.
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Low volatility is often read as a signal of stability. But periods of unusual calm in equity markets can reflect something more ambiguous — a compression of uncertainty rather than its absence. This piece examines how to read low-volatility environments as a research input rather than a green light, and what questions a careful investor should be asking when the surface looks smooth.
Read the piece →Every investment thesis contains assumptions that never make it onto the page. They are the things you believe to be true without having explicitly decided to believe them — about management quality, about competitive durability, about the reliability of a revenue stream. This piece looks at how unexamined assumptions accumulate in a research process and what a more disciplined approach to surfacing them looks like in practice.
Read the piece →Most investment analysis is built around a single central scenario — the base case. But a base case is not a forecast; it is a working assumption. This piece explores how to build a more complete scenario framework: one that takes the downside seriously, stress-tests the conditions under which the thesis holds and helps you understand how much of the current valuation depends on things going exactly to plan.
Read the piece →Earnings releases are designed to communicate — but they are also designed to frame. The metrics a company chooses to lead with, the comparisons it selects and the language it uses to describe performance all shape the impression a reader forms before they reach the underlying numbers. This piece examines how to approach an earnings release as a research document rather than a narrative, and what to look for beyond the headline figures.
Read the piece →It is possible to research a company thoroughly and still make a poor portfolio decision. The reason is usually context: a stock that looks compelling in isolation may add concentration, amplify an existing exposure or introduce a correlation you had not accounted for. This piece looks at how to hold portfolio-level thinking alongside company-level research — and why the two conversations need to happen at the same time.
Read the piece →One of the hardest moments in investment research is when your analysis points in a different direction from the prevailing market view. The discomfort is real and the temptation to defer is strong. This piece examines how to maintain analytical discipline in that situation — how to distinguish between a contrarian view that is well-founded and one that is merely stubborn, and how to use the disagreement itself as a research input.
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