Scalping Strategy

Scalping Strategy

Target small, frequent profits from minimal price movements on 1m-5m timeframes.

Setup Conditions

Scalping Techniques

1. Momentum Scalping

Enter on strong momentum candles on 1m, ride for small gain, exit immediately on momentum loss.

get_indicators(indicator_code="rsi", symbol=<symbol>, exchange=<exchange>, interval="1m")
get_indicators(indicator_code="macd", symbol=<symbol>, exchange=<exchange>, interval="1m")

Define an objective closed-bar momentum trigger and exit. RSI/MACD are correlated price transforms; retain them only if they improve held-out net results over a price-only baseline.

2. Level Scalping

Quick bounces at key S/R levels with tight stops.

get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval="5m", date=<date>)

Identify levels on the context timeframe, define a numerical rejection on the execution timeframe, and place invalidation beyond the level plus expected stop slippage. Require the planned payoff to remain positive after costs.

3. Range Scalping

Buy support, sell resistance within a defined micro-range. Repeat until range breaks.

get_indicators(indicator_code="dmi", symbol=<symbol>, exchange=<exchange>, interval="5m")

Use a calibrated range classifier; ADX alone does not confirm a micro-range. Stop applying the rule when the closed-bar invalidation or liquidity gate fails.

Workflow

1. Confirm Direction on 5m

get_indicators(indicator_code="ema", symbol=<symbol>, exchange=<exchange>, interval="5m")
get_indicators(indicator_code="dmi", symbol=<symbol>, exchange=<exchange>, interval="5m")

Establish bias from higher timeframe before scalping on 1m.

2. Identify Setup on 1m

get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval="1m", date=<date>)
get_indicators(indicator_code="rsi", symbol=<symbol>, exchange=<exchange>, interval="1m")

Pick one technique (momentum, level, or range) based on current conditions.

3. Mark Key Levels

draw_chart_analysis(action="create", drawing={
    "type": "support",
    "points": [
        {"time": <touch_1>, "price": <level>},
        {"time": <touch_2>, "price": <level>}
    ],
    "options": {"text": "Scalp Level"}
})

4. Report to Orchestrator

Technique selected, timestamped quote, order type, expected fill, entry, invalidation, target, total cost estimate, capacity, and context-timeframe bias.

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: Barber et al. found aggregate day-trader performance was negative and persistent profitability rare, making net-of-cost evidence and strict loss limits essential.

Key Rules

• Exclude scheduled event windows unless a separately tested event strategy and mandate apply.
• Reject markets and order sizes that fail the spread, depth, fill-rate, latency, or cost gate.
• Exit on the predeclared invalidation; do not widen risk after entry.
• Enforce the mandate's session loss and order-rate limits; pause on feed, clock, or execution anomalies.
• Compare context-aligned and context-agnostic variants rather than assuming alignment adds edge.
• Do not deploy from win rate alone; require positive net expectancy and stable tail losses.

Related Skills

• range-trading -- range scalping is a micro-timeframe application of range principles
• momentum-trading -- momentum scalping borrows directional confirmation logic