Can ChatGPT Write Pine Script v6? We Tested It Properly
ChatGPT can write Pine Script — but can it write v6 that compiles on the first try in TradingView? We ran real tests on strategies, indicators, and multi-timeframe logic. Here is the honest result.
The short answer
Yes, ChatGPT can write Pine Script. No, it does not reliably write Pine Script v6 that compiles on the first attempt. In our testing it produced code with the right idea but the wrong syntax — usually a mix of v4, v5, and v6 conventions that TradingView rejects.
The reason is structural, not a knowledge gap you can prompt around: ChatGPT was trained on years of Pine Script examples, most of which are v4 and v5. Pine Script v6 changed the namespace (ta., request., math.), the type system, and several function signatures. Without the current v6 reference in context, the model averages across versions and produces code that looks right but fails to compile.
- Compiles first try: inconsistent — simple indicators often yes, strategies often no.
- v6 namespace (ta.ema not ema): frequently wrong.
- Input syntax (title= not label=): a recurring error.
- Scope rules (plot/alertcondition must be global): often violated.
Test 1: A simple RSI indicator
Prompt: 'Write a Pine Script v6 RSI indicator with overbought at 70 and oversold at 30, plotted in a separate pane.'
ChatGPT got this mostly right — a simple, common pattern it has seen thousands of times. The one slip was using rsi(close, 14) instead of ta.rsi(close, 14), a v6 namespace error that fails to compile. One quick fix and it worked.
Takeaway: for very common, simple indicators, ChatGPT is close. You will still hit a namespace error or two, but it is usable with light editing.
Tip
If you only ever build simple single-indicator scripts, generalist AI plus a few fix rounds is workable. The pain starts with strategies and anything multi-timeframe.
Test 2: A strategy with risk management
Prompt: 'Write a Pine Script v6 strategy — EMA 9/21 crossover, ATR-based stop loss at 1.5x ATR, 2:1 take profit, alerts on entries.'
This is where it broke down. ChatGPT recalculated the stop loss from strategy.position_avg_price on every bar instead of storing it at entry in a var float — a subtle bug that compiles but produces a drifting, incorrect stop. It also placed an alertcondition() inside an if block (a scope error) and missed alerts on the short side.
Three issues, two of which compile silently and only show up as wrong backtest behavior. A trader who is not a Pine Script expert would not catch the drifting stop loss at all.
Test 3: Multi-timeframe with request.security()
Prompt: 'Pine Script v6 strategy that only goes long when the daily trend is up, using request.security on the daily timeframe.'
ChatGPT used lookahead=barmerge.lookahead_on and referenced the live close instead of close[1] for the higher-timeframe value. Both introduce future-data bias (repainting) — the backtest looks great and live trading does not match it. This is the single most dangerous category of Pine Script error because it makes a bad strategy look profitable.
TradePilot, for contrast, defaults to lookahead_off, close[1] on the HTF series, and gaps=barmerge.gaps_off, because the full v6 reference and the repainting rules are injected on every request.
When ChatGPT is the right tool
For learning and ideation, ChatGPT is genuinely excellent. Ask it to explain RSI divergence, debate whether to use ATR or percentage stops, or brainstorm strategy ideas — it is a great thinking partner and we use it for exactly that.
For producing Pine Script v6 that compiles and backtests correctly on the first attempt, a specialist tool with the v6 reference in context wins — and closes the copy-paste-debug loop inside TradingView instead of leaving you bouncing between two tabs.
TradePilot Team
Traders and engineers building the fastest way to go from idea to live Pine Script strategy, right inside TradingView.
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