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How to use these examples

These examples build on beginner concepts and introduce controlled complexity. They are designed to:
  • combine multiple conditions
  • introduce filters and confirmations
  • show more realistic strategy behavior
  • remain readable and debuggable
Intermediate strategies are about structure and discipline - not complexity for its own sake.

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Example 1: Trend + pullback confirmation

Trading idea: 
Trade ETH/USDT on the 1h timeframe.
Only trade in the direction of the 4h trend.
Go long when EMA(20) crosses above EMA(50) on 1h.
Exit with a 6% take profit and a 1.2% stop loss.
What this introduces:
  • multi-timeframe logic
  • trend filtering
  • reduced trade frequency

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Example 2: Momentum breakout with volume filter

Trading idea: 
Trade BTC/USDT on the 15m timeframe.
Go long when price breaks above the previous high.
Require volume to be above its 20-period average.
Exit with a 4% take profit and a 1% stop loss.
What this introduces:
  • breakout logic
  • confirmation filters
  • fewer false signals

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Example 3: Symmetric long & short with logic-based exits

Trading idea: 
Trade ETH/USDT on the 1h timeframe.
Go long when RSI(14) crosses above 55.
Go short when RSI(14) crosses below 45.
Exit long when RSI(14) crosses below 50.
Exit short when RSI(14) crosses above 50.
What this introduces:
  • logic-based exits
  • directional symmetry
  • indicator-driven lifecycle

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Example 4: Time-restricted trend strategy

Trading idea: 
Trade BTC/USDT on the 1h timeframe.
Go long when EMA(50) is above EMA(200).
Only trade during the London and New York sessions.
Use a 5% take profit and a 1% stop loss.
What this introduces:
  • session filters
  • exposure control
  • market behavior by time of day

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Example 5: Conservative confirmation stack

Trading idea: 
Trade ETH on 4h.
Go long when:
- EMA(20) is above EMA(50)
- RSI(14) is above 50
- MACD is above the signal line
Exit with a 7% take profit and a 2% stop loss.
Adding confirmations reduces false positives - but can also reduce opportunity.

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Common intermediate mistakes

If trades disappear, remove filters until baseline behavior is visible again.
Always know which timeframe controls entries vs filters.
One good backtest doesn’t mean robustness.

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How to evolve these strategies

Once you’re comfortable:
  • adjust thresholds slightly
  • test different timeframes
  • compare fixed vs logic-based exits
  • analyze drawdowns, not just profit

Improving a strategy

Learn how to iterate without over-optimizing.

Strategy structure overview

How these ideas are formalized internally.

Backtesting & metrics

How to interpret results properly.

Common missing details

Avoid silent strategy failures.

Beginner examples

Start from simpler ideas.
Intermediate strategies reward patience. Clarity beats complexity every time.