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Apex Quant
A 12-factor stock signal engine with Monte Carlo simulation.
Apex Quant is a live, institutional-grade quantitative stock analysis platform built entirely from scratch. Every signal is built from first principles: a 12-factor engine combining RSI, MACD, Bollinger Bands, EMA crossovers, Kelly Criterion, OBV, and ATR. Monte Carlo simulation runs 300 paths using geometric Brownian motion. Sharpe and Sortino ratios benchmark every strategy against risk-adjusted return.
Hey Product Hunt! I'm Neil, the student who built this.
Apex Quant started as a question I couldn't let go of: how does Wall Street actually make decisions? Not the theory but the real mechanics. So I spent months teaching myself quantitative finance from scratch and building the tools to test it.
Every line of math in this platform I wrote myself without financial libraries because I needed to understand it, not just use it.
I'm a rising senior at NCSSM conducting neutrino physics research at Duke during the day and building this at night. Happy to answer any questions about the methodology, the tech stack, or how a 17-year-old ended up here.
Would love to hear what you think, and if you have feedback on the signal engine or the backtesting framework, I'm all ears.
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About Apex Quant on Product Hunt
“A 12-factor stock signal engine with Monte Carlo simulation.”
Apex Quant was submitted on Product Hunt and earned 8 upvotes and 1 comments, placing #46 on the daily leaderboard. Apex Quant is a live, institutional-grade quantitative stock analysis platform built entirely from scratch. Every signal is built from first principles: a 12-factor engine combining RSI, MACD, Bollinger Bands, EMA crossovers, Kelly Criterion, OBV, and ATR. Monte Carlo simulation runs 300 paths using geometric Brownian motion. Sharpe and Sortino ratios benchmark every strategy against risk-adjusted return.
Apex Quant was featured in Fintech (47.5k followers), Tech (631.9k followers) and Finance (6.3k followers) on Product Hunt. Together, these topics include over 194k products, making this a competitive space to launch in.
Who hunted Apex Quant?
Apex Quant was hunted by Neil Saini. 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.
Want to see how Apex Quant stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Neil Saini
Hey Product Hunt! I'm Neil, the student who built this.
Apex Quant started as a question I couldn't let go of: how does Wall Street actually make decisions? Not the theory but the real mechanics. So I spent months teaching myself quantitative finance from scratch and building the tools to test it.
Every line of math in this platform I wrote myself without financial libraries because I needed to understand it, not just use it.
I'm a rising senior at NCSSM conducting neutrino physics research at Duke during the day and building this at night. Happy to answer any questions about the methodology, the tech stack, or how a 17-year-old ended up here.
Would love to hear what you think, and if you have feedback on the signal engine or the backtesting framework, I'm all ears.