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Desk2Quant Desk Simulator
Diagnose a broken trading desk P&L. Free, no signup.
Most quant-prep tools are quizzes or PDFs — nothing like the actual job. Desk Simulator drops you into a realistic desk incident (a P&L break, a broken yield curve, a Monte Carlo Greek that won't reconcile) with a limited investigation budget. You earn evidence by running the right diagnostic tests, then submit a root cause, fix, and preventive controls — scored against what a real investigation needs to prove. Free, no signup, 3 incidents live at launch.
I'm Amit — a quant/model-risk developer. Most "learn quant finance" content is either a textbook PDF or a multiple-choice quiz, and neither looks anything like the actual job. The actual job looks like: someone says "the number is wrong," and you have until the morning P&L call to figure out why.
So I built a simulator around that instead of another quiz. You get a realistic desk incident, a limited investigation budget, and evidence you have to earn by running the right diagnostic tests — not handed to you upfront. At the end you submit a root cause, a fix, and preventive controls, and get scored against what a real investigation would need to prove.
Free, no signup, 4 incidents live at launch (a P&L break, a yield curve bootstrap failure, and a Monte Carlo Greeks mismatch — pricing, risk, and model validation, one each).
Would love feedback, especially from anyone who's sat on a desk or done model validation — did I get the mechanics right? What incident would you want to see next?
About Desk2Quant Desk Simulator on Product Hunt
“Diagnose a broken trading desk P&L. Free, no signup.”
Desk2Quant Desk Simulator was submitted on Product Hunt and earned 3 upvotes and 3 comments, placing #160 on the daily leaderboard. Most quant-prep tools are quizzes or PDFs — nothing like the actual job. Desk Simulator drops you into a realistic desk incident (a P&L break, a broken yield curve, a Monte Carlo Greek that won't reconcile) with a limited investigation budget. You earn evidence by running the right diagnostic tests, then submit a root cause, fix, and preventive controls — scored against what a real investigation needs to prove. Free, no signup, 3 incidents live at launch.
On the analytics side, Desk2Quant Desk Simulator competes within Education, Developer Tools and Finance — topics that collectively have 602.6k followers on Product Hunt. The dashboard above tracks how Desk2Quant Desk Simulator performed against the three products that launched closest to it on the same day.
Who hunted Desk2Quant Desk Simulator?
Desk2Quant Desk Simulator was hunted by Amit Kumar Jha . A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Desk2Quant Desk Simulator including community comment highlights and product details, visit the product overview.
Amit Kumar Jha 
Hey Product Hunt 👋
I'm Amit — a quant/model-risk developer. Most "learn quant finance"
content is either a textbook PDF or a multiple-choice quiz, and neither
looks anything like the actual job. The actual job looks like: someone
says "the number is wrong," and you have until the morning P&L call to
figure out why.
So I built a simulator around that instead of another quiz. You get a
realistic desk incident, a limited investigation budget, and evidence
you have to earn by running the right diagnostic tests — not handed to
you upfront. At the end you submit a root cause, a fix, and preventive
controls, and get scored against what a real investigation would need
to prove.
Free, no signup, 4 incidents live at launch (a P&L break, a yield curve
bootstrap failure, and a Monte Carlo Greeks mismatch — pricing, risk,
and model validation, one each).
Would love feedback, especially from anyone who's sat on a desk or done
model validation — did I get the mechanics right? What incident would
you want to see next?