If you’ve ever found yourself staring at TradingView, trying to code a trading strategy but getting stuck halfway, you’re not alone. Like many traders exploring quantitative and algorithmic strategies, I started with a rough idea based on Bollinger Bands and the Weekly VWAP. I wanted a way to enter trades when volatility was high but prices seemed oversold — and then ride the trend safely with a trailing stop.
As I was refining this BB & VWAP Weekly trading strategy in my TradingView Ideas section, a thought hit me: Why not ask ChatGPT to generate a Pine Script version of it? Before diving into something complex, I decided to test if ChatGPT could handle even a simple strategy first.
Prompting ChatGPT: The Power of AI for Traders
Here’s the exact prompt I used:
“Using Pine Script, generate a strategy for TradingView platform. Use Bollinger Bands and VWAP weekly for entries. After entry, use the 10% trailing stop loss to track trade. Exit the trade when trailing stop loss is hit. Include code to draw trailing stop loss.“
Here is the screenshot of chatGpt Prompt
Within seconds, ChatGPT generated a complete Pine Script strategy. The code looked clean and ready to deploy. I copied the output and added it to my TradingView strategy editor. To my surprise, it worked almost instantly — although there was a small variable scope error at first. I fixed that manually (yes, in hindsight I could’ve just asked ChatGPT to fix it too).
Strategy Components Explained
The strategy uses two primary indicators:
- Bollinger Bands (BB) – a volatility indicator that identifies overbought and oversold levels.
- Weekly VWAP (Volume Weighted Average Price) – to determine the average price level over a weekly period.
The entry condition is straightforward: when price closes below the lower Bollinger Band and then crosses above the weekly VWAP, a long trade is triggered.
After entering the trade, a 10% trailing stop loss is applied. The highest price reached since entry is constantly tracked, and if the price drops by 10% from that peak, the trade is exited.
Code Screenshot of Pine Script in TradingView Editor
Enhancing the Strategy with Real-World Testing
Once I fixed the small variable error, I ran the backtest on TSLA (Tesla) using 1-hour and 4-hour charts. The results were surprisingly encouraging.
What stood out most:
- The strategy managed to capture significant trends when price rebounded from volatility zones.
- The 10% trailing stop allowed me to stay in the trade long enough to benefit from upward swings without getting stopped out too early.
- Adjusting the stop loss percent to a tighter or looser range had a direct impact on win ratio vs. profit per trade — a crucial trade-off for any trader.
TSLA 4-Hour Chart with Strategy Applied
Why ChatGPT Makes Strategy Creation Easy
You don’t need to be a seasoned developer to use Pine Script anymore. Here’s why using ChatGPT as your trading assistant is a game changer:
- Rapid Prototyping: You can test dozens of strategies without wasting hours on debugging.
- Custom Adjustments: Need to tweak an indicator? Just ask ChatGPT to revise it.
- Error Fixing: Whether it’s variable scopes, type mismatches, or unexpected behavior — you can debug collaboratively.
- Documentation and Learning: The AI not only gives you code but explains the logic, helping you become a better algo trader.
The Final Strategy Code (Simplified View)
Here’s a simplified preview of the code that ChatGPT gave me:
//@version=5
strategy("BB & VWAP Strategy with Trailing Stop", overlay=true)
// Inputs
length = input.int(20, title="BB Length")
mult = input.float(2.0, title="Multiplier")
trailPerc = input.float(10.0, title="Trailing %")
// BB and VWAP
basis = ta.sma(close, length)
dev = mult * ta.stdev(close, length)
lower = basis - dev
isNewWeek = ta.change(time("W"))
var float wvwap = na
wvwap := isNewWeek ? close : (wvwap * (bar_index - ta.valuewhen(isNewWeek, bar_index, 1)) + close) / (bar_index - ta.valuewhen(isNewWeek, bar_index, 1) + 1)
// Entry
entryLong = ta.crossover(close, wvwap) and close < lower
strategy.entry("Long", strategy.long, when=entryLong)
// Trailing Stop
var float highest = na
var float trailStop = na
if (strategy.opentrades > 0)
highest := na(highest) ? high : math.max(highest, high)
trailStop := highest * (1 - trailPerc / 100)
strategy.exit("Exit", from_entry="Long", stop=trailStop)
plot(trailStop, "Trailing Stop", color=color.red)Trailing Stop Plotted on Chart
How You Can Build Your Own Trading Strategy with AI
Whether you’re a day trader, swing trader, or algorithmic enthusiast, this approach opens the door for you to build:
- Fully automated strategies for backtesting.
- Real-time scripts with alerts and trailing mechanisms.
- Custom conditions like RSI, MACD, EMA crossovers, or even news sentiment indicators.
You’re no longer limited by coding knowledge. You just need:
- An idea
- A TradingView account
- ChatGPT to do the heavy lifting
Tips for Better Results
- Always backtest on different timeframes.
- Combine multiple strategies into one and optimize entries.
- Adjust trailing stops and risk thresholds depending on market conditions.
- Use visual markers like plots to monitor entry/exit conditions.
Performance Backtest Summary on TSLA 1-HR Chart
Final Thoughts
This entire strategy started with a simple idea and a single prompt. In less than an hour, I had:
- Clean Pine Script code
- Functional strategy on TradingView
- Backtest results on a high-volatility stock
- A better understanding of how trailing stops can protect and grow capital
So here’s my takeaway: Anyone can write a TradingView strategy using ChatGPT. You don’t need to be a coder. You just need curiosity, a bit of logic, and the courage to experiment.
I hope this walkthrough inspires you to build and automate your own strategies. Use AI smartly — and trade wisely.
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