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A YouTube strategy β an AI-built algo π¦
Watch Claude build a no-adjustment NIFTY Broken Wing Butterfly on Tradetron, then explore its backtest.
Strategy Markdown included so you can follow along.
βΆοΈ piped.video/kahSCewPnqI
#AlgoTrading #NIFTY
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Want to build it yourself? π
π Strategy Markdown: linked in the video description
piped.video/kahSCewPnqI
π€ Connect Claude to Tradetron:
mcp.tradetron.tech/
Upload the file, ask Claude to build it, then review and backtest.
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The original strategy discussion that inspired this build π
Credit to Kundan Prajapati from Trading Scholars and @sourabhsiso19 for sharing the setup π¦
Watch their explanation:
piped.video/watch?v=B0wkNECzβ¦
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From a YouTube video to a ready algo π€
Today at 5 PM IST, weβll show you how to build and backtest this zero-adjustment NIFTY Butterfly strategy using Claude AI + Tradetron. No coding needed.
π₯ New video on YouTube. Stay tuned!
#Tradetron #AlgoTrading #ClaudeAI
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Entry time: 9:20 AND 10:20 β°
Stop loss: 20%, 30%, 40%, 50% π
Exit: 3:15, 4:00, 2:00 β±οΈ
Every combination becomes its own backtest.
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16 backtests. One go. 6 years of historic data. π
Then you can see which combination is actually worth betting money on. π―
βΆοΈ piped.video/__u25Lihv10
#ParameterSweep #Backtesting
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Build a strategy. Backtest it on 6 years of option data. The graph is fine. π
But fine isn't good enough. So you start optimising. π
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3/ 40 versions later: your account is a mess, you need a spreadsheet to track them, and the strategy looks nothing like what you designed. π
This is where people get lost. π§
βΆοΈ piped.video/__u25Lihv10
#Backtesting #AlgoTrading
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Next time someone shows you a backtest with fancy numbers, ask one question: π§
"Kya aapne in-sample out-sample analysis kiya kya?" π£οΈ
Holding up = the in-sample result repeated on data it never saw. β
Everything else is untested. π
βΆοΈ piped.video/8pKHucYFv5I
#Backtesting #AlgoTrading
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You can now build a Tradetron strategy by describing it.
Typed: "9:20 NIFTY short straddle, 20% target, 30% SL per leg, exit 3:15"
Claude built it (entry, legs, exits) and then backtested it.
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DEGRADES β οΈ
In-sample it did X. Out-of-sample it came in below X.
Didn't fail β just weakened. Worth refining a few points of it.
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HOLDING UP β
The in-sample result repeated on data it had never seen.
Out of every variant tested here, one was holding up. That's the one you pick. π―
βΆοΈ piped.video/8pKHucYFv5I
#Backtesting #AlgoTrading
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The heat grid is not your full backtest result. π₯
Almost everyone reads it as if it is π§΅π
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The grid comes from the split you set.
Optimise on the 70%. Run a separate backtest on the 30% it never saw. π
So the grid is in-sample vs out-of-sample. That's the whole point of it. π
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Your full 100% backtest is the section underneath β separate number, separate meaning. β οΈ
The table below that breaks out every sample tested. π
βΆοΈ piped.video/8pKHucYFv5I
#Backtesting #AlgoTrading
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