Ten minutes, one real strategy, twenty-seven years of real S&P 500 data. By the end of this page you will know what a quant is, why software beats emotions, and how to run your first strategy without watching a chart ever again.
No hunches, no headlines, no 3am chart staring. An idea becomes criteria, criteria become a program, the program runs somewhere reliable and executes through a brokerage API. That is the entire job description.
Today QuantGPT covers the idea, the criteria and the test on real data. The cloud box is the runner, coming to QuantGPT Pro. Execution happens at your broker, on your keys, at your direction. The trade is yours.
This is the S&P 500, real data, 1999 to 2026, from the QuantGPT warehouse. Ten thousand dollars riding it the whole way becomes about sixty-one thousand. The index is a great machine. It is also a machine that occasionally sets your money on fire: twice in this window it cut an account nearly in half or worse.
What if you only rode the index while it was healthy? One of the oldest findings in the research: compare the price to its own 200-day moving average. Above the line, the market spends most of its time going up. Below the line is where the catastrophes live: the crashes, the panics, the year-long bleeds.
Paint the same history by which side of the line the market is on. Green: above the average. Red: below it. Nearly all of the misery, 2000 to 2003, 2008 to 2009, the 2020 crash, the 2022 bleed, happens in red. The idea works. Armed with this knowledge, take this observation, validated by data, and USE IT to build a trading system.
Simple rule, right? Except executing it by hand means watching the close every single day for twenty-seven years. And the naive version of this rule, sell the moment price dips below the line, buy the moment it pokes above, would have flipped your account 196 times. Every triangle below is a trade the naive rule demands. Most are whipsaws: false alarms that cost money, patience, and sleep. This is where humans break: they hesitate, they revenge-trade, they stop following the rule the week before it matters most. Software has none of those feelings.
So we tune the rule to trade less and mean it more: go long only when the close is 1% or more above the 200-day average; go flat only when it closes 3% or more below. The buffer kills the whipsaws: 42 trades in 27 years instead of 196. And flat does not mean idle: while out of the market the cash earns the going money market rate, the real 3-month Treasury bill yield of each day, straight from the Fed's own data. Here is that machine against buy-and-hold, on the same real data:
THERE YOU GO. THAT WAS A QUANT STRATEGY, AND YOU JUST UNDERSTOOD EVERY PIECE OF IT.
One more move. The rule you just built is a crash filter, and a crash filter is worth the most on the index that crashes hardest: the Nasdaq 100. Same signal, same 42 trades, same money market while flat, but the long leg holds NDX instead of the S&P. Riding the Nasdaq raw meant an 83% drawdown in the dot-com bust, a hole almost nobody holds through. Behind the filter it kept most of the rocket, dodged most of the crater, and finished ahead of buy-and-hold on both indexes:
A strategy is useless on a laptop that sleeps. So the program goes on a machine that is always on, always watching the close, with no emotions. Then it points at your brokerage API with your own keys, and the trades land in your account. Two ways to get there: run it on the runner when it opens, or on your own machine, against your Alpaca account for U.S.-listed stocks and ETFs. Or run any strategy as a plain screener in the terminal, see what it would own today, and place the trades yourself. Your call, always.
Coming to QuantGPT Pro: the runner will host your own code and send its orders to your own Alpaca account, under your keys. We never decide a trade. It opens after review.
Trend is the simplest quant strategy, not the only one. The same loop, idea, criteria, program, applies to every documented edge:
Low P/E plus real profitability: the classic value screen, run as a machine.
Buy strength, rebalance monthly, let winners compound. The most documented edge in the literature.
Margins, balance sheets, earnings growth: own only companies that clear the bar.
From the Strategy Library, or build your own criteria in the terminal and test them on real data.
On the runner when it opens, or download your criteria and run them on your own machine. Both are yours.
Your own Alpaca account, for U.S.-listed stocks and ETFs. Your account, your keys, your trades.
This page is the written companion to chapter S1 of QuantGPT University, "What a quant is". Members play the lesson, open the 200-day rule in the terminal and take the three-question check there.
Start your 3-day trial Or start free, no card Chapter S1 in University Everything on Learn