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Are you intrigued by ads or videos claiming a “guaranteed” or “perfect” trading strategy? Ever see backtests boasting unimaginable returns — like +4,218,186,988%?
Don’t be fooled!
This blog post will show you how these so-called “perfect” indicators trick people and why they don’t work in real life.
Backtest doesn’t mean everything
“But it made 4 billion percent returns!”
If an indicator claims Earth-shattering returns that dwarf even legendary investors like Warren Buffett, that’s a red flag. Backtesting is performed on historical price data. While it can provide helpful insights, it’s easy to manipulate by fitting an indicator exactly to past market conditions (known as “overfitting”). This makes the indicator look perfect on old data but worthless on new data.
Let me show you how it’s done
Below is a condensed piece of code (Less than 20 lines) demonstrating how scammers artificially create perfect buy/sell signals. It uses TradingView’s Pine Script, intentionally “peeking” into the future:
//@version=5strategy("Perfect Daily High/Low Strategy (Overfitting Demo)", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100)
Buy 100% of Portfolio
This tells TradingView to use your entire account equity (100%) every time you enter a position. In real trading, going “all in” on a single strategy is hugely risky. However, because the code already “knows” the future, it’s tempting to allocate maximum capital to show massive (fake) returns.
// Get the "future" high and low of the current day using lookaheadfuture_day_high = request.security(syminfo.tickerid, "D", high, lookahead=barmerge.lookahead_on)future_day_low = request.security(syminfo.tickerid, "D", low, lookahead=barmerge.lookahead_on)
Using Future Data
Here, the code calls “request.security” to fetch the current day’s high and low from a daily chart, but crucially, it uses lookahead=barmerge.lookahead_on. This means the script can see the entire day’s high and low even before that day’s trading has ended — effectively “peeking” into the future. In a realistic strategy, you’d only know the daily high or low after it’s formed, not in advance.
// Detect if current bar is the daily high or low (using future info)is_daily_high = high == future_day_highis_daily_low = low == future_day_low
Identifying Daily Highs and Lows
The logic checks whether the intraday bar’s high matches the future daily high and whether the bar’s low matches the future daily low. Because we already have the future daily high/low, we can pinpoint the exact bars in real time during a backtest, making it look like a magical strategy.
// Entry signalsif is_daily_low strategy.entry("Buy at Daily Low", strategy.long, comment="Buy")if is_daily_high strategy.entry("Sell at Daily High", strategy.short, comment="Sell")
Flawless Buy & Sell
If the intraday bar just so happens to be the daily low, the script immediately goes long. If the bar is the daily high, it goes short. Because the strategy grabs future data, it knows exactly when to buy at the bottom and sell at the top — something impossible without a time machine in real trading.
// Plot labels for visual clarityplotshape(is_daily_high, title="Sell (Day High)", style=shape.labeldown, location=location.abovebar, color=color.red, text="Sell", size=size.tiny)plotshape(is_daily_low, title="Buy (Day Low)", style=shape.labelup, location=location.belowbar, color=color.green, text="Buy", size=size.tiny)
Visual Buy/Sell Labels
Finally, the script adds labels so you can see each perfect entry and exit on the chart. This makes for a compelling backtest or marketing teaser video. But remember — these labels are based on future-peeking data. It looks impressive but has zero real-world reliability.
Faking Backtesting Videos
If you copy and paste the overfitted strategy code into TradingView as-is, you’ll see an incredible backtest result on the historical chart.
However, if you try to run bar playback (TradingView’s replay feature) to simulate price movement bar by bar, it won’t work anymore — because in playback mode, the script no longer has access to future bars.
This is where some scammers get creative to produce “perfect” replay videos.
The Fake “Perfect Indicator” Playback Trick
Below is a simplified snippet showing how they hard-code specific prices and timestamps, so it looks like the script predicts future price action when replaying the chart:
//@version=5indicator("Fake Playback Demo", overlay=true)// Hard-coded highs and lowssell_label = high == 69684.7buy_label = low == 68050.0// Hard-coded timestamp for a “Sell” signaltarget_time = timestamp("America/New_York", 2024, 4, 1, 9, 30)sell_time = (time == target_time)// Plot shapesplotshape(sell_label or sell_time, title="Sell (Day High)", style=shape.labeldown, location=location.abovebar, color=color.red, text="Sell", size=size.tiny)plotshape(buy_label, title="Buy (Day Low)", style=shape.labelup, location=location.belowbar, color=color.green, text="Buy", size=size.tiny)
How Does This Code Work?
1. Hard-Coded Prices:
The script checks if the current bar’s high equals a specific value ($69684.7) or if the bar’s low is exactly $68050.0. Because these are known future prices, the script can display a Sell or Buy label right when the playback reaches that bar.
2. Hard-Coded Timestamp:
There’s also a check for a specific timestamp (2024–04–01 09:30 in New York time). If the current bar’s time matches that moment, the script plots another Sell label. Again, this is purely to force a “predicted” signal during replay.
3. Perfect Replay Illusion:
When you playback this chart from an earlier date, these labels will magically appear at just the right moment. But in reality, the script is just waiting for exact, pre-written conditions. There’s no genuine prediction — only an after-the-fact cheat.
How to Spot These Scams: A Simple Checklist
1. Check the Returns
If the returns are thousands or millions of percent, be skeptical. Ask yourself if even the most successful investors achieve anything close.
2. Look for Overfitting
Multiple timeframe checks, references to “lookahead” in code, and perfect buy/sell points usually mean the script is using future data.
3. Ask for Transparency
- Is the script public on TradingView?
- Has it been reviewed by credible sources or the TradingView team?
4. Test on Different Markets
Overfitted indicators often fail on other assets, different timeframes, or different market conditions.
5. Use Common Sense
If it’s too good to be true, it probably is.
What We’re Building at TradeDots
Here at TradeDots, we develop reliable, non-overfitted, non-repainting indicators and trading tools. We focus on statistical models that react in real time to price action without cheating.
Our Key Differentiators
- Real-Time, Not Perfect: We accept there’s no such thing as a 100% win rate, but we build tools that help traders spot opportunities faster.
- Robust Codebase: We have over 5 premium indicators with ~10,000 lines of code combined — much more sophisticated than simplistic shortcuts.
- Transparency: Many of our indicators are free and open-source. You can see exactly how they work.
- NVIDIA Inception Program: As a member of NVIDIA’s startup ecosystem, we’re harnessing cutting-edge technology for quantitative finance.
Try Our Premium Indicators Free for 7 Days
We offer a 7-day free trial for new users. If you have questions about trading, indicators, or the markets, feel free to reach out to our team at any time.
Final Thoughts
Remember:
- Backtests Don’t Guarantee Future Profits — Real markets rarely behave exactly like historical data.
- Overfitting Hurts — It may look impressive on paper, but it falls apart in real trading.
- Do Your Research — Check if the code is verified, tested across multiple markets, and open-source if possible.
Stay sharp, stay informed, and don’t let flashy returns cloud your judgment. Follow us for more trading and finance insights — and thank you for reading!
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Disclaimer: This article is for informational purposes only and does not constitute financial advice. Investing involves risks, and it’s important to conduct your own research or consult with a financial professional before making investment decisions.
