Quant Edge: Intro to Algorithmic Trading & Backtesting
Quant Edge: Intro to Algorithmic Trading & Backtesting, Backtest trading strategies with AI: turn ideas into rules, test mean reversion on real data, and read the results.
What you’ll learn
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Explain the difference between algorithmic and discretionary trading, and why a rule you can state in advance is a rule you can test before risking money
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Turn any trading idea into a simple if/then rule — the logic every algorithmic strategy is built from, no coding required
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Describe a mean-reversion trading strategy in plain English and understand why “buy oversold, sell the bounce” is a real, testable idea
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Run a real backtest against historical market data by describing a strategy in plain language, with zero code written
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Read and interpret an equity curve, total return, max drawdown, and win rate to judge whether a result is actually meaningful
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Iterate on a trading idea quickly — adjust an assumption, re-test, and compare results in seconds instead of hours
Course Description
Every trading strategy is a rule. Most traders never write theirs down, so they never find out whether it actually works.
This course fixes that in under an hour. You’ll turn a trading hunch into a precise IF / THEN rule, and then test it for real. You describe the rule in plain English, AI writes the strategy code, and a quant engine runs it as a backtest on historical market data.
SECTION 1: THINK IN RULES
Learn why your best trade may have been noise, not signal. See why every algorithmic strategy comes down to one condition and one action. Then turn “buy the dip” into a precise mean-reversion rule using RSI. At the end of the section you’ll write a rule of your own in 90 seconds.
SECTION 2: TEST IT FOR REAL
Watch a plain-English rule become a backtest in QuantIDE. The result isn’t rehearsed: nobody knows the output until the engine returns it. Then you’ll pause the course and run your own rule on your own screen. Next you’ll learn the four metrics that judge any strategy: equity curve, total return, max drawdown and win rate. Finally, you’ll see how a great-looking backtest can prove nothing, and why sample size is what separates a real edge from a lucky streak.
BY THE END, YOU’LL BE ABLE TO:
– Rewrite any trading idea as a testable rule
– Define a mean-reversion strategy with an exact entry and exit
– Have AI turn your rule into strategy code and backtest it on real historical data
– Read an equity curve, total return, max drawdown and win rate
– Spot a backtest result that looks impressive but proves nothing
– Use the describe → test → read → adjust loop on any new idea
WHO THIS IS FOR
Traders who have acted on tips or gut feel and want evidence instead. It’s also for anyone curious about algorithmic trading who assumed they’d need a maths degree or years of programming first.
You need a computer and the free QuantIDE app. You don’t need to know how to program, and you don’t need a finance background.
This course is for education only. Backtests describe the past and don’t guarantee future results.
Who this course is for:
- Complete beginners who assume algo trading requires coding first — it doesn’t, and this course proves it in 30 minutes
- Anyone who’s traded on a gut feeling or a tip and wants to test an idea *before* risking money, not after
- Manual/discretionary traders curious whether a system removes the emotional decisions manual trading is prone to
- Anyone who’s downloaded a trading app or platform and felt intimidated opening it, unsure where to start
- People deciding if algo trading is a realistic hobby or side skill — just wanting one real result to know if it’s worth going further
