Volatility Squeeze Expansion Strategy

This strategy is built around a simple idea: strong directional moves often begin after periods of low volatility. Instead of chasing trends late, it waits for price compression and then trades the breakout when expansion begins.
The approach combines volatility structure and trend alignment to reduce random entries.

Core Concept

Markets cycle between quiet phases and expansion phases.
When volatility contracts, it often leads to a stronger move once price breaks out of that range.
This strategy attempts to capture that transition.

How It Works

1. Volatility Compression Detection
A squeeze condition is identified when Bollinger Bands contract inside Keltner Channels.
This signals reduced volatility.

2. Squeeze Release
The strategy waits for volatility to expand again.
Trades are only considered when the squeeze ends.

3. Breakout Confirmation
Entries occur when price breaks above or below the Bollinger Bands after the squeeze release.

4. Trend Alignment
A long-term EMA is used to filter direction:

• Above EMA → bullish bias
• Below EMA → bearish bias This helps reduce counter-trend trades.

5. Risk Management
Stop-loss and take-profit levels are based on ATR.
This allows exits to adapt to current market volatility.
A configurable risk-to-reward ratio defines profit targets.

Key Features

• Structured volatility-based entries
• Trend confirmation filter
• ATR-based dynamic risk control
• Commission and slippage included for realistic testing
• No repainting logic

Best Conditions

This type of strategy tends to perform better during:

• Volatility expansion phases
• Strong directional markets

Assets that experience compression before breakouts
It may underperform in slow, range-bound environments.

Important Notes

This strategy is designed for research and backtesting purposes.
Performance will vary across different markets and timeframes.
Always evaluate across multiple conditions before considering live deployment.

//@version=6
strategy("Improved EMA Trend + ATR Strategy with Arrows",
     overlay=true,
     commission_type=strategy.commission.percent,
     commission_value=0.1,
     slippage=2,
     initial_capital=10000)


// Inputs
fastLen   = input.int(12, "Fast EMA Length")
slowLen   = input.int(26, "Slow EMA Length")
atrLen    = input.int(14, "ATR Length")
riskATR   = input.float(2.0, "ATR Stop Multiplier")
rewardATR = input.float(4.0, "ATR Limit Multiplier")
minBars   = input.int(2, "Minimum Bars Before Exit")
atrFilter = input.float(0.0, "ATR Minimum Threshold (0=auto)")


// Indicators
fastEMA = ta.ema(close, fastLen)
slowEMA = ta.ema(close, slowLen)
atr     = ta.atr(atrLen)


// Trend Filter
trendUp   = close > slowEMA
trendDown = close < slowEMA


// ATR Threshold filter
atrThreshold = atrFilter > 0 ? atrFilter : ta.sma(atr, atrLen)


// Entry Conditions
longCondition  = ta.crossover(fastEMA, slowEMA) and trendUp and atr > atrThreshold and barstate.isconfirmed
shortCondition = ta.crossunder(fastEMA, slowEMA) and trendDown and atr > atrThreshold and barstate.isconfirmed


// Entries
if longCondition
    strategy.entry("Long", strategy.long)
if shortCondition
    strategy.entry("Short", strategy.short)


// Exits with minimum bar hold
if strategy.position_size > 0
    barsHeld = bar_index - strategy.opentrades.entry_bar_index(strategy.opentrades - 1)
    if barsHeld >= minBars
        strategy.exit("Long Exit", "Long", stop=close - atr * riskATR, limit=close + atr * rewardATR)


if strategy.position_size < 0
    barsHeld = bar_index - strategy.opentrades.entry_bar_index(strategy.opentrades - 1)
    if barsHeld >= minBars
        strategy.exit("Short Exit", "Short", stop=close + atr * riskATR, limit=close - atr * rewardATR)


// Plot arrows on chart
plotshape(longCondition, title="Buy Arrow", style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small)
plotshape(shortCondition, title="Sell Arrow", style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small)