Open research community
Read quant research. Challenge the method.
Start with 18 annotated papers. Then inspect a public project that found no measurable edge in its own signals, and bring your questions to the group.
6,788 signals. No measured edge.
In a July 2026 evaluation, directional calls across 7 assets matched the direction-adjusted base rate over the next 10 bars. The failed hypotheses and corrections are part of the record.
Read the case study- BTC -1.7 pp
- ETH -0.7 pp
- SOL -0.3 pp
- AAPL +2.0 pp
- MSFT -0.5 pp
- GOOGL +0.1 pp
- NVDA +0.7 pp
Reported in the July 2026 findings ↗. The spread is noise around zero; it does not establish an edge.
What you actually get.
A reading list, not a link dump
18 papers, from foundational asset pricing to modern market data. Each note explains why that paper made the list.
Open the reading listPeople reading the same things
The LinkedIn group is the place to share a paper, ask about its method, and discuss it with other readers.
Join the groupSomewhere to put your work
Written a replication, a negative result, or a useful method note? Email a short summary and a link. We can discuss whether it fits the site.
Get in touchStart with these.
Three of the 18 papers on the list. Not summaries — the reason each one is still worth your time.
- Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk The CAPM. Read it for the argument, not the result: Sharpe derives a single price of risk from equilibrium alone, and every factor model since is a fight about what he left out.
- A Simple Approach to the Theory of Asset Prices Prices assets as bundles of moment-characteristics without assuming expected utility. A useful antidote if you have only ever seen pricing derived one way.
- The Value Premium and the CAPM The direct sequel to Sharpe: value beats the market, and the CAPM beta cannot explain it. Pairs with the 1993 three-factor paper below.
Shorter notes from the work.
- Testing Regime-Based Factor Rotation A concrete test plan for factor rotation: observable signals, point-in-time inputs, a static baseline, and costs.
- Testing a Financial Document Classification Prompt A small worked example for classifying financial documents with evidence, abstention, and explicit evaluation.
- Deflated Sharpe Ratios: Start with the Selection Problem A reproducible simulation shows why the best Sharpe from many backtests is misleading, and what a formal correction must account for.
- Why Quant Research Should Be Open The case for doing quantitative research in the open — and why secrecy is overrated for most alpha.
You'll probably fit if…
- You're starting out A student or career-switcher looking for a path through the papers the field actually reads.
- You can already build An engineer or data scientist who can ship a model but wants to know which published results survive contact with real data.
- You do this for a living A working quant who wants to compare methods and assumptions with people outside their own desk.
Read closely. Show your work.
QuantHQ curates papers worth reading and publishes articles about quantitative finance methods. Each reading note explains why its paper is on the list. Our aim is to make assumptions, limitations, and sources easy to inspect.
Our articles use QuantHQ Team as the editorial byline. Sources are linked, and corrections or contributions can be sent through contact. Discussion happens in the LinkedIn group.
Bring a paper or a question.
The public LinkedIn group is the place to discuss a method, share a replication, or ask what a result leaves out.
Curious what the research tooling looks like? The lab has interactive demos — everything there runs on simulated sample data.