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How to use these examples

These examples are intentionally simple. They are designed to:
  • produce trades
  • be easy to understand
  • behave predictably in backtests
You can copy them directly, modify them, or use them as inspiration.
A beginner strategy is not a bad strategy. Simple ideas are easier to evaluate and improve.

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Example 1: Basic RSI reversal

Trading idea: 
Create an ETH/USDT strategy on the 1h timeframe.
Go long when RSI(14) drops below 30.
Exit with a 5% take profit and a 1% stop loss.
Why this works as a first example:
  • clear market and timeframe
  • single indicator
  • deterministic entry
  • fixed risk
This strategy helps you understand:
  • oversold logic
  • trade frequency
  • basic risk/reward behavior

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Example 2: Moving average crossover

Trading idea: 
Trade BTC/USDT on the 4h timeframe.
Go long when EMA(20) crosses above EMA(50).
Exit when EMA(20) crosses below EMA(50).
Why this works:
  • classic trend-following logic
  • entry and exit symmetry
  • no fixed TP/SL required
Good for learning:
  • crossover behavior
  • trend duration
  • drawdowns during ranges

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Example 3: Fixed TP/SL with momentum confirmation

Trading idea: 
Trade ETH on 1h.
Go long when RSI(14) is above 55.
Use a take profit of 6% and a stop loss of 1.5%.
Why this works:
  • momentum confirmation is explicit
  • exits are deterministic
  • produces frequent trades
Useful for understanding:
  • win rate vs average win/loss
  • impact of fixed exits

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Example 4: Long and short symmetry

Trading idea: 
Trade BTC/USDT on the 1h timeframe.
Go long when EMA(20) crosses above EMA(50).
Go short when EMA(20) crosses below EMA(50).
Use a 4% take profit and a 1% stop loss.
Why this works:
  • demonstrates bidirectional logic
  • same rules for long and short
  • easy to compare performance
Great for:
  • understanding short trades
  • market regime differences

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Example 5: Time-filtered trading

Trading idea: 
Trade ETH on 1h.
Go long when RSI(14) crosses above 50.
Trade only on Monday, Wednesday, Thursday, and Friday.
Exit with a 5% take profit and a 1% stop loss.
Why this works:
  • introduces filters without complexity
  • shows how schedules affect trade count

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Common beginner mistakes

Start with one indicator. Add confirmations only after you understand baseline behavior.
Always define exits. If you forget, ATI will stop and ask.
Look at behavior first, profit later.

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How to build on these examples

Once you’re comfortable:
  • change timeframes
  • adjust parameters slightly
  • add one filter at a time
  • compare results side by side

Iteration & optimization

Learn how to improve strategies without overfitting.

How to write a trading idea

The mental model behind clear ideas.

Natural language vs structured input

Learn when to stay intuitive and when to be precise.

What Trinigence fills automatically

Understand what AI handles for you.

Strategy structure overview

See how these ideas are formalized.
If a beginner strategy behaves “badly”, that’s still valuable information. Simple strategies teach faster than complex ones.