Trend Following Strategy with ADX

Discover a trend following strategy for BTC/USDT, refined from an AI-generated algorithm. This strategy utilizes ADX and multiple timeframes (1h, 4h, 6h) to ide

Published · Updated · Methodology: Technical Indicators

Part of: Moving Average Strategies

  • Methodology: Technical Indicators
  • Content type: strategy
  • Timeframes: 1 hour (initial trading timeframe), 4 hours (initial big trend analysis, then trading timeframe), 6 hours (final big trend analysis)
  • Markets: BTC/USDT

Indicators used

  • Baseline indicator (unspecified, likely Moving Average)
  • Confirmation indicator (unspecified)
  • ADX

Source video

Decoded from: ChatGPT o1: Python Strategy Makes 432% by Algo-trading with Saleh — watch the original

Key timestamps:

  • 0:44 - Prompt for strategy generation
  • 2:00 - Initial strategy code review
  • 3:00 - Backtesting setup
  • 4:00 - Fixing errors in code
  • 5:40 - Adding short entry conditions
  • 6:30 - Modifying timeframes
  • 7:30 - Adjusting ADX threshold
  • 8:00 - Position sizing and leverage adjustment

Strategy overview

A moving average smooths raw price into a single line that reveals the direction of the prevailing trend — the base concept this page's hub covers in full. What sets this entry apart is where that moving average sits: not as the whole system, but as the *baseline* trend layer inside a multi-timeframe, trend-following setup that also leans on a separate confirmation indicator and on ADX to judge whether a trend is actually strong enough to act on.

The bigger hook is how the strategy was built. It was decoded from Algo-trading with Saleh's video "ChatGPT o1: Python Strategy Makes 432%", in which the creator prompts OpenAI's o1 reasoning model to generate the strategy as Python code, then reviews it, backtests it, and works through the errors, short entries, and timeframe changes on screen. That framing is the point: this is less a finished, hand-crafted system than a look at using an AI model to draft trading logic and iterate on it — with the moving-average baseline read across a higher timeframe for the dominant trend and a lower one for timing entries. The 432% figure comes straight from the video's title and refers to a backtest the creator shows; treat it as an attributed claim, not a verified or repeatable result.

This page pairs the moving-average concept with the source video rather than exporting a line-by-line rule set. Where a strength filter like ADX and a smoothing baseline are combined, the specific settings decide whether the approach holds up — and here those settings emerged through the AI-assisted iteration shown in the video rather than from a fixed, published recipe.

Topics

adx strategy · trend following strategy · bitcoin trading strategy · btc usdt strategy · 1 hour trading strategy · 4 hour trading strategy · 6 hour trading strategy · technical indicators strategy · pine script · trading strategy · tradingview strategy · crypto trading strategy · ai trading strategy · timeframe analysis · adx trend following

Frequently asked questions

What is ADX and how does a trend-following strategy use it?

ADX (Average Directional Index) measures how strong a trend is, regardless of whether price is rising or falling. In a trend-following strategy it acts as a gate: a moving average and a confirmation signal set the direction, while ADX helps filter out weak, choppy conditions so the system only commits when a trend has real strength behind it.

How was this strategy created?

It was decoded from a video in which the creator prompts ChatGPT's o1 reasoning model to write the strategy as Python code, then backtests and debugs it iteratively. The rules originate from AI-generated code the creator refines on screen, rather than from a traditional hand-coded system.

Does this strategy really return 432%?

The 432% figure comes from the video's title and refers to a backtest the creator demonstrates. It is a claim from the source — not a verified, audited, or guaranteed result — and backtested returns do not carry over to live trading. Read it as the video's headline and evaluate the logic on your own data.

How can I study a strategy like this before trading it?

Backtest it on historical data across the timeframes it uses, and observe how it behaves when trends are weak versus strong. Strategy Decoder extracts the structure of strategies like this one from their video sources so you can review the concept and evaluate it for yourself.

About this strategy page

This trading strategy was decoded by Strategy Decoder's AI from a public YouTube trading video and turned into a structured, reviewable specification. In the interactive app this page shows the full entry and exit logic, risk management settings, the indicators involved with their parameters, AlgoWizard-compatible logic and a Pine Script export ready for TradingView backtesting — plus an automated backtest verdict when one has been computed for this strategy.

Strategy Decoder catalogs 2,229 decoded strategies. Each one is extracted with confidence scoring, cross-linked to the indicators it uses, and kept up to date as new videos are processed daily. Load this page with JavaScript enabled to use the interactive tools, or start from the strategy explorer to filter by methodology, market and timeframe.

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