CombinedBinHAndClucV2 Strategy Analysis

Strategy #: #110 (110th of 465 strategies) Strategy Type: Multi-Timeframe Bollinger Band Combination Strategy + Three-Layer Signal Filtering Main Timeframe: 5 Minutes (5m) Auxiliary Timeframe: 1 Hour (1h)

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I. Strategy Overview

CombinedBinHAndClucV2 is an enhanced version of the classic dual-strategy combination CombinedBinHAndCluc, developed by iterativ. This strategy introduces multi-timeframe analysis and trend filtering mechanisms on top of the original version. It uses 1-hour SSL channels to judge the market's big trend and executes trades at the 5-minute level, with three-layer signal verification via MFI money flow and StochRSI momentum indicators, significantly improving signal reliability.

Core Features

Feature	Description
Buy Conditions	3 layers: Big trend (SSL) + Momentum (MFI/StochRSI) + Pattern (BinHV45/ClucMay72018)
Sell Conditions	1 basic sell signal + staged ROI take-profit
Protection Mechanism	StoplossGuard (max 2 trades per pair in 24 candles, 12-candle cooldown)
Timeframe	Main 5m + Auxiliary 1h
Stop-Loss	-5% (tighter than original -10%)
Dependencies	TA-Lib, numpy, qtpylib, technical

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II. Strategy Configuration Analysis

2.1 Basic Risk Parameters

# Staged ROI Take-Profit Table
minimal_roi = {
    "0": 0.10,      # Immediate exit: 10% profit
    "30": 0.05,     # After 30 minutes: 5% profit
    "60": 0.02,     # After 60 minutes: 2% profit
    "120": 0.01,    # After 120 minutes: 1% profit
}

# Stop-Loss Settings
stoploss = -0.05   # -5% hard stop-loss (tighter than original -10%)

# Trading Timeframe
timeframe = '5m'              # Main timeframe: 5 Minutes
informative_timeframe = '1h'  # Auxiliary timeframe: 1 Hour

# Sell Signal Configuration
use_exit_signal = True
exit_profit_only = True
ignore_roi_if_entry_signal = True  # New buy signal can override ROI

Design Philosophy:

• Aggressive ROI: 0% threshold means 10% take-profit immediately, 5% after 30 minutes — suitable for fast short-term profits.
• Tight Stop-Loss: -5% stop-loss tighter than original -10%, reducing per-trade maximum loss risk.
• Multi-Timeframe: 1h judges trends, 5m executes trades, filtering counter-trend signals.
• Signal Priority: ignore_roi_if_entry_signal = True allows new buy signals to override ROI exits.

2.2 Trading Protection Mechanism

protections = [
    {
        "method": "StoplossGuard",
        "lookback_period_candles": 24,      # Look back 24 candles
        "trade_limit": 2,                   # Max 2 trades
        "stop_duration_candles": 12,        # Cool down 12 candles
        "only_per_pair": True               # Calculate per pair separately
    }
]

Protection Logic:

• Max 2 trades per pair within 24 candles (2 hours).
• After triggering limits, must wait 12 candles (1 hour) cooldown.
• Prevents frequent openings leading to fee erosion and overtrading.

2.3 Trading Pair Suggestions

# Suggested trading pairs
# - Mainstream coins: BTC/USDT, ETH/USDT
# - High-volatility coins: SOL/USDT, ADA/USDT, AVAX/USDT
# - Avoid low-volatility coins

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III. Entry Conditions Details

V2's entry conditions use three-layer filtering — all must be satisfied to trigger a buy signal. This significantly improves signal quality but also reduces signal frequency.

3.1 Layer 1: Big Trend Filtering (1h SSL Channel)

SSL Channel Indicator: Dynamic support/resistance band adjusted by ATR

# Calculate SSL Channel
ssl_down, ssl_up = SSLChannels(dataframe, length=25)
dataframe['ssl_high'] = (ssl_up > ssl_down).astype('int') * 3

# Trend Judgment Condition
(dataframe['ssl_high'] > 0)  # SSL channel upward, indicating uptrend

Logic Interpretation:

• SSL channel upward: Price in 1h-level uptrend.
• Only consider buying under the premise of following the big trend.
• Filters counter-trend trades, reducing being trapped risk.

3.2 Layer 2: Momentum Filtering (MFI + StochRSI)

# MFI (Money Flow Indicator)
dataframe['mfi'] = ta.MFI(dataframe, timeperiod=30)

# StochRSI (Stochastic RSI)
stoch = ta.STOCHRSI(dataframe, 30, 35, 2, 2)
dataframe['srsi_fk'] = stoch['fastk']   # K value
dataframe['srsi_fd'] = stoch['fastd']   # D value

# Momentum Condition: Both MFI and K value rising
(dataframe['mfi'].shift().rolling(3).mean() > dataframe['mfi']) &
(dataframe['srsi_fk'].shift().rolling(3).mean() > dataframe['srsi_fk'])

Logic Interpretation:

• MFI Rising: Capital inflow increasing, buying pressure strengthening.
• StochRSI K Value Rising: Short-term momentum turning stronger.
• 3-Period Moving Average Smoothing: Avoids single-period noise interference.

3.3 Layer 3: Pattern Filtering (BinHV45 OR ClucMay72018)

Layer 3 uses "OR gate" logic — satisfying either pattern is sufficient.

3.3.1 BinHV45 Mode

Volatility Breakout Pattern: Captures rebound opportunities after price rapidly breaks BB lower band

(
    dataframe['lower'].shift().gt(0) &                    # BB exists
    dataframe['bbdelta'].gt(dataframe['close'] * 0.008) & # Width > 0.8%
    dataframe['closedelta'].gt(dataframe['close'] * 0.0175) & # Fluctuation > 1.75%
    dataframe['tail'].lt(dataframe['bbdelta'] * 0.25) &  # Wicking < 25%
    dataframe['close'].lt(dataframe['lower'].shift()) &  # Breaks lower band
    dataframe['close'].le(dataframe['close'].shift())     # Close weakens
)

Condition	Parameter	Description
BB exists	lower > 0	Previous BB lower band valid
Width threshold	bbdelta > close × 0.8%	BB opening sufficient
Fluctuation threshold	closedelta > close × 1.75%	Price fluctuation sufficient
Lower wick limit	tail < bbdelta × 25%	Short lower wick, support after decline
Breaks lower band	close < lower.shift()	Price breaks BB lower band
Close weakens	close ≤ close.shift()	Current close below previous candle

3.3.2 ClucMay72018 Mode

Shrinking Volume Rebound Pattern: Buys on dips when volume shrinks

(
    (dataframe['close'] < dataframe['ema_slow']) &        # Below EMA50
    (dataframe['close'] < 0.985 * dataframe['bb_lowerband']) & # Breaks lower band
    (dataframe['volume'] < dataframe['volume_mean_slow'].shift(1) * 20) # Shrinking volume
)

Condition	Parameter	Description
Below EMA	close < EMA50	Price in weak position below long-term MA
Breaks lower band	close < 98.5% × lower	Price breaks BB lower band
Volume shrinks	volume < 20 × avg	Current volume extremely low, selling pressure exhausted

3.4 Entry Conditions Summary

Filter Layer	Condition Name	Core Logic	Timeframe
Layer 1	SSL Channel	Uptrend confirmation	1h
Layer 2	MFI	Capital inflow confirmation	5m
Layer 2	StochRSI	Momentum strengthening confirmation	5m
Layer 3	BinHV45	Volatility breakout pattern	5m
Layer 3	ClucMay72018	Shrinking volume rebound pattern	5m

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IV. Exit Conditions Details

4.1 Technical Sell: BB Upper Band Breakdown

Trigger Condition:

qtpylib.crossed_below(dataframe['close'], dataframe['bb_upperband'])

Logic Interpretation:

• Triggers sell when price crosses below BB upper band.
• Indicates price may transition from uptrend to pullback.
• Symmetric with the lower band breakout at entry.

4.2 ROI Staged Take-Profit

Holding Time	Take-Profit Threshold	Design Logic
0 minutes (immediate)	10%	Capture instant large swings
30 minutes	5%	Mid-wave target
60 minutes	2%	Prevent profit retreat
120 minutes	1%	Prevent holding indefinitely

4.3 Stop-Loss Exit

Trigger Condition: Forced liquidation when loss reaches 5%.

Logic Interpretation:

• -5% stop-loss tighter than original -10%.
• Paired with multi-timeframe filtering, wrong trades should be fewer.
• Per-trade maximum loss controllable.

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V. Technical Indicator System

5.1 Auxiliary Timeframe Indicators (1h)

Indicator	Calculation Method	Purpose
SSL Channel	ATR-adjusted MA channel (period 25)	Trend judgment
MFI	30-period money flow indicator	Capital flow verification
StochRSI	Stochastic RSI (30, 35, 2, 2)	Momentum conversion verification

5.2 Main Timeframe Indicators (5m)

Indicator	Calculation Method	Purpose
BB (40,2)	Bollinger Bands	BinHV45 pattern judgment
BB (20,2)	Bollinger Bands	ClucMay72018 pattern
EMA50	50-period exponential moving average	Trend verification
Volume Average	30-period average volume	Shrinking volume verification

5.3 Custom Calculated Indicators

Indicator	Formula	Purpose
bbdelta	|middle - lower|	BB width
closedelta	|close - previous close|	Price fluctuation magnitude
tail	|close - low|	Lower wick length
ssl_high	SSL channel direction tag	Trend state

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VI. Risk Management Features

6.1 Stop-Loss Strategy

Stop-Loss Type	Threshold	Description
Hard Stop-Loss	-5%	Forced liquidation at 5% loss

Comparison with Original:

• Original CombinedBinHAndCluc: -10%
• V2 Version: -5%
• Tightened by half, reflecting confidence in three-layer filtering signals.

6.2 Take-Profit Strategy

Take-Profit Type	Threshold	Description
Instant Take-Profit	10%	Immediate exit
Staged ROI	1%-5%	Timed exit

Design Features:

• Instant take-profit threshold higher (original 5% → V2 10%).
• Staged take-profit balances fast profit capture with holding duration.

6.3 Trading Protection

Protection Mechanism	Parameters	Description
StoplossGuard	24/2/12	Trade frequency limit

Protection Effect:

• Max 2 trades per pair within 2 hours.
• 1-hour cooldown.
• Effectively prevents overtrading and emotional operations.

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VII. Strategy Pros & Cons

Pros

1. Multi-Timeframe Analysis: 1h trend filtering + 5m signal execution, avoids counter-trend trades.
2. Three-Layer Signal Filtering: Trend + momentum + pattern, significantly improves buy signal quality.
3. Dynamic Trend Recognition: SSL channel automatically identifies market direction.
4. Capital Flow Verification: MFI confirms capital inflow, avoids false breakouts.
5. Trading Protection: Prevents overtrading and emotional decisions from fee erosion.
6. Tight Stop-Loss: -5% stop-loss reduces per-trade risk.
7. Staged Take-Profit: Multi-layer profit protection.

Cons

1. Scarce Signals: Three-layer filtering overlay may significantly reduce buy frequency.
2. Timeframe Dependency: 1h trend judgment may lag.
3. Parameter Coupling: Layers' parameters interact, making optimization difficult.
4. Simple Exit Logic: Only relies on upper band breakout, lacks trailing stop.
5. No Dynamic Stop-Loss: May miss trending opportunities.

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VIII. Applicable Scenarios

Market Environment	Recommended Configuration	Description
Trending Uptrend	max_open_trades=2-3	SSL channel upward, high signal quality
Volatile Market	Use cautiously	SSL frequently flips, signal unstable
Mainstream Coins	BTC/ETH/SOL	Good liquidity, controllable slippage
High-Volatility Coins	Participate moderately	BB opening wide, patterns clearer

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IX. Applicable Market Environment Details

CombinedBinHAndClucV2 is positioned as a trend pullback-type multi-timeframe combination strategy in the Freqtrade ecosystem. Based on its code architecture and three-layer filtering, it is best suited for clear uptrend pullback opportunities and may perform poorly in volatile or declining environments.

9.1 Core Strategy Logic

• Trend is King: SSL channel judges 1h-level big trend, only trades following the major direction.
• Capital Verification: MFI confirms capital inflow, avoids non-fundamental rebounds.
• Momentum Confirmation: StochRSI verifies short-term momentum, avoids chasing highs.
• Pattern Entry: BinHV45 or ClucMay72018 pattern confirms entry point.

9.2 Performance in Different Market Environments

Market Type	Rating	Analysis
Trending Uptrend	⭐⭐⭐⭐⭐	SSL channel upward, three-layer filtering highest signal quality
Volatile Market	⭐⭐☆☆☆	SSL frequently flips, signals unstable, may miss opportunities
Sustained Decline	⭐☆☆☆☆	SSL channel downward, buy signals completely filtered
Extreme Volatility	⭐⭐⭐☆☆	MFI and StochRSI may generate false signals

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X. Summary

CombinedBinHAndClucV2 is a multi-timeframe trend pullback strategy for moderately experienced traders. Its core value:

1. Multi-Dimensional Signal Verification: Through 1h SSL trend + 5m MFI/StochRSI momentum + pattern three-layer filtering, significantly improves buy signal quality.
2. Tight Risk Control: -5% stop-loss paired with staged ROI, balancing risk and return.
3. Trading Protection: StoplossGuard prevents overtrading.

For quantitative traders, this strategy suits users who understand multi-timeframe analysis, can accept lower signal frequency, and pursue signal reliability. Not recommended for high-frequency traders or users who like frequent operations. Conduct sufficient backtesting and paper trading verification before live trading.