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SKE-LabsSKE-Labs/agent-trading-skills/skills/technical-strategies/moving-average-crossover/SKILL.md

moving-average-crossover

Skill17 starsChanged 4 months agoApache-2.0View on GitHub

Trade EMA/SMA crossover systems for trend following. Use when identifying trend changes, timing entries with momentum, or building systematic trading rules.

1 other project uses a version of this, 1 of them edited.

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We split this skill into the rules it gives an agent

5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Wait for crossover, then wait for pullback to fast MA

    line 44
  2. Distinctive:

    All 3 aligned = ordered-average state.

    line 48
  3. Distinctive:

    Treat the setup as a testable hypothesis, not a prediction.

    line 89
  4. Distinctive:

    Use a regime filter only if it adds held-out net value.

    line 97
  5. Distinctive:

    Test additional features incrementally and control parameter/data-snooping risk.

    line 101

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Moving Average Crossover Trading

MA crossovers provide systematic signals for trend identification and entry timing.

Candidate Combinations

Fast MASlow MAUse Case
5 EMA13 EMAFast conventional pair
9 EMA21 EMAMedium-fast conventional pair
20 SMA50 SMAMedium conventional pair
50 SMA200 SMASlow conventional pair

These are starting specifications, not style-specific best settings. Record every pair tried and compare against buy-and-hold/cash or an appropriate directional baseline.

Signals

Golden Cross (Bullish)

  • Fast MA crosses above slow MA
  • Record price versus both averages as a candidate filter

Death Cross (Bearish)

  • Fast MA crosses below slow MA
  • Record price versus both averages as a candidate filter

Strategies

Basic Crossover

  • Enter on cross in direction, exit on opposite cross
  • Simple but prone to whipsaws in ranges

Price + MA Confirmation

  • Wait for crossover, then wait for pullback to fast MA
  • Enter on an objectively defined pullback trigger; test whether it changes whipsaw rate and net expectancy

Triple MA System (5-8-13)

  • All 3 aligned = ordered-average state; not independent confirmation
  • Entry: 5 crosses 8, both above 13
  • Exit: 5 crosses below 8

MA as Dynamic S/R

  • In uptrend: MA acts as support (buy bounces)
  • In downtrend: MA acts as resistance (sell rallies)

Workflow

  1. Get each chosen average explicitly:
    get_indicators(indicator_code="ema_<fast>", symbol=<symbol>, exchange=<exchange>, interval=<interval>, count=<enough>)
    get_indicators(indicator_code="ema_<slow>", symbol=<symbol>, exchange=<exchange>, interval=<interval>, count=<enough>)
  2. Identify cross direction and confirm with price position relative to MAs
  3. Get candle data for entry timing:
    get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval=<interval>, date=<date>)
  4. Enter on pullback to fast MA (conservative) or on cross (aggressive)
  5. Stop loss beyond recent swing or slow MA. Exit on opposite cross or target.
  6. Mark on chart:
    draw_chart_analysis(action="create", drawing={
        "type": "trend",
        "points": [
            {"time": <cross_time>, "price": <cross_price>},
            {"time": <current_time>, "price": <current_ma>}
        ],
        "options": {"text": "Golden Cross (9/21 EMA)"}
    })

Evidence and Validation

  • Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
  • Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
  • Include spread, fees, slippage, borrow or funding, partial fills, and latency. Reject the setup when net expectancy is not positive or depends on one narrow parameter.
  • Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
  • Research basis: The technical-analysis evidence review finds mixed market- and era-dependent profitability and highlights transaction costs and data snooping.

Key Rules

  • Use a regime filter only if it adds held-out net value; ADX does not confirm trend by itself.
  • A crossover rule must specify closed-bar timing, order timing, stop, exit, and warm-up.
  • Faster averages react sooner and trade more often; reliability is empirical after costs.
  • EMA weights recent data more heavily; SMA weights its window equally.
  • Test additional features incrementally and control parameter/data-snooping risk.

Related Skills

  • market-regime-detection — MA crossovers only work in trending regimes; check ADX before trading
  • macd-trading — MACD is derived from EMAs and provides complementary momentum confirmation

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