SMA_BBRSI Strategy Deep Dive

Strategy ID: #367 (367th of 465 strategies)
Strategy Type: Multi-Condition Trend Following + RSI Bollinger Bands + Custom Stop Loss
Timeframe: 5 minutes (5m) + 1-hour informational layer

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I. Strategy Overview

SMA_BBRSI is a composite quantitative trading strategy that integrates Simple Moving Average (SMA) offset, Elliott Wave Oscillator (EWO), RSI Bollinger Bands, and anti-pump mechanisms. Through the combination and validation of multiple technical indicators, the strategy captures trend reversal opportunities while utilizing multi-layered protection mechanisms to reduce risk exposure.

Core Features

Feature	Description
Buy Conditions	3 independent buy signals, individually optimizable via parameters
Sell Conditions	2 base sell signals + custom dynamic stop loss
Protection Mechanisms	3 protection parameter groups (LowProfitPairs, MaxDrawdown, Anti-pump threshold)
Timeframe	Main timeframe 5m + informational timeframe 1h
Dependencies	talib, numpy, pandas_ta, technical, qtpylib

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II. Strategy Configuration Analysis

2.1 Basic Risk Parameters

# ROI exit table
minimal_roi = {
    "0": 0.028,    # Immediate 2.8% profit target
    "10": 0.018,   # After 10 candles: 1.8%
    "30": 0.010,   # After 30 candles: 1.0%
    "40": 0.005    # After 40 candles: 0.5%
}

# Stop loss setting
stoploss = -0.10   # Fixed stop loss at -10%

# Trailing stop
trailing_stop = True
trailing_stop_positive = 0.001
trailing_stop_positive_offset = 0.01
trailing_only_offset_is_reached = True

Design Rationale:

• ROI uses a tiered declining structure to quickly lock in small profits
• Fixed stop loss at -10% provides baseline protection
• Trailing stop activates after 1% profit, allowing profits to run further

2.2 Order Type Configuration

# Order types (using default configuration)
order_time_in_force = {
    'buy': 'gtc',
    'sell': 'gtc',
}

2.3 Custom Dynamic Stop Loss System

The strategy implements a tiered dynamic stop loss mechanism:

# Dynamic stop loss parameters
pHSL = -0.178    # Hard stop loss profit threshold
pPF_1 = 0.01     # Profit threshold 1 (1%)
pSL_1 = 0.009    # Stop loss level 1 (0.9%)
pPF_2 = 0.048    # Profit threshold 2 (4.8%)
pSL_2 = 0.043    # Stop loss level 2 (4.3%)

Dynamic Stop Loss Logic:

• Profit < 1%: Use hard stop loss at -17.8%
• Profit between 1% - 4.8%: Linear interpolated stop loss (0.9% - 4.3%)
• Profit > 4.8%: Stop loss floats upward with profit

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III. Buy Conditions Detailed

3.1 Protection Mechanisms (3 Groups)

The strategy has built-in triple protection mechanisms:

Protection Type	Parameter Description	Default Value
Anti-pump	antipump_threshold	0.25
LowProfitPairs	Pause trading for 60 minutes after 5% loss	trade_limit=1
MaxDrawdown	Circuit breaker at 20% max drawdown	lookback=24 candles

3.2 Three Buy Conditions Detailed

Condition #1: EMA Offset + EWO High + RSI Low Combination

# Logic
- Close < EMA(buy_candles) × low_offset (price below MA * 0.973)
- EWO > ewo_high (5.672) (EWO indicator shows upward momentum)
- RSI < rsi_buy (59) (RSI not overbought)
- Volume > 0

Applicable Scenario: Pullback buying opportunities in an uptrend

Condition #2: EMA Offset + EWO Low Combination

# Logic
- Close < EMA(buy_candles) × low_offset (price below MA * 0.973)
- EWO < ewo_low (-19.931) (EWO shows oversold condition)
- Volume > 0

Applicable Scenario: Bottom-fishing opportunities after deep decline

Condition #3: RSI Bollinger Bands + EWO Validation Combination (Most Complex)

# Logic
- RSI < basis - (dev × for_sigma) (RSI below Bollinger lower band)
- EWO in reasonable range:
  - (EWO > ewo_high_bb AND EWO < 10) OR
  - (EWO >= 10 AND RSI < 40)
- RSI(4) < 25 (Short-term RSI oversold)
- CCI(fast) < 100 (CCI not overbought)
- moderi_96 == True (Long-term trend upward)
- Volume > 0

Applicable Scenario: Multi-indicator confluence oversold reversal signal

3.3 Three Buy Conditions Classification

Condition Group	Condition #	Core Logic
Trend Pullback	#1	EMA offset + EWO confirmation + RSI filter
Deep Bottom-Fishing	#2	EMA offset + EWO extreme negative
Oversold Confluence	#3	RSI Bollinger Bands + EWO + CCI + moderi multi-indicator validation

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IV. Sell Logic Detailed

4.1 Multi-Layer Take Profit System

The strategy uses a tiered take profit mechanism:

Profit Range      Stop Loss Threshold    Signal Name
───────────────────────────────────────────────────
< 1%             -17.8%                  Hard stop protection
1% ~ 4.8%        Dynamic interpolation   Tiered stop loss
> 4.8%           Floats with profit      Trailing stop

4.2 Two Sell Conditions

Sell Signal #1: EMA Offset Sell

# Condition
- Close > EMA(sell_candles) × high_offset (1.010)
- Volume > 0

Interpretation: Price rises above 1.01x of MA, take profit

Sell Signal #2: RSI Bollinger Upper Band Break + ATR Stop Loss

# Condition (satisfy any)
- RSI > basis + (dev × for_sigma_sell) AND moderi_96 == True
- Price falls below ATR_high (3.5x ATR dynamic stop loss)
- Volume > 0

Interpretation: Sell when RSI touches Bollinger upper band or price triggers ATR stop loss

4.3 Anti-Pump Mechanism

dont_buy_conditions.append(
    (dataframe['pump_strength'] > self.antipump_threshold.value)
)

When pump_strength exceeds the threshold, buying is forcefully prohibited to prevent chasing highs.

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V. Technical Indicator System

5.1 Core Indicators

Indicator Category	Specific Indicators	Purpose
Trend	EMA(16/20), ZEMA(30/200)	MA trend determination
Oscillators	RSI(14/4/30), StochRSI	Overbought/oversold determination
Volatility	ATR(14), Bollinger Bands	Volatility and channels
Momentum	EWO, CTI(20), CCI(240/20)	Momentum and trend strength
Custom	moderi_96, pump_strength	Long-term trend, anti-pump

5.2 Informational Timeframe Indicators (1h)

The strategy uses 1 hour as the informational layer, providing higher-dimensional trend confirmation:

• Long-term EMA trend confirmation
• Cross-timeframe moderi indicator
• Base data for pump strength calculation

5.3 Elliott Wave Oscillator (EWO)

def EWO(dataframe, ema_length=5, ema2_length=35):
    ema1 = ta.EMA(df, timeperiod=ema_length)
    ema2 = ta.EMA(df, timeperiod=ema2_length)
    emadif = (ema1 - ema2) / df['close'] * 100
    return emadif

EWO measures market momentum through the percentage difference between fast and slow EMAs.

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VI. Risk Management Features

6.1 Triple Protection Mechanism

Protection Type	Parameter	Function
LowProfitPairs	5% loss trigger	Pause trading pair after loss
MaxDrawdown	20% drawdown	Global circuit breaker protection
Anti-pump Threshold	0.25	Prohibit chasing highs

6.2 Custom Dynamic Stop Loss

The strategy implements progressive stop loss protection:

if (current_profit > PF_2):  # Profit > 4.8%
    sl_profit = SL_2 + (current_profit - PF_2)
elif (current_profit > PF_1):  # Profit between 1% - 4.8%
    sl_profit = SL_1 + ((current_profit - PF_1) * (SL_2 - SL_1) / (PF_2 - PF_1))
else:  # Profit < 1%
    sl_profit = HSL  # -17.8%

6.3 HyperOpt Optimization Parameters

The strategy provides rich optimizable parameters:

Parameter Category	Count	Examples
Buy Parameters	7	base_nb_candles_buy, ewo_high, rsi_buy, etc.
Sell Parameters	8	base_nb_candles_sell, high_offset, rsi_high, etc.
Dynamic Stop Loss Parameters	5	pHSL, pPF_1, pSL_1, pPF_2, pSL_2

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VII. Strategy Advantages and Limitations

✅ Advantages

1. Multi-dimensional Validation: Buy signals require confirmation from multiple indicators, reducing false signal probability
2. Anti-pump Mechanism: Built-in pump_strength indicator effectively avoids chasing-high risks
3. Dynamic Stop Loss: Tiered stop loss mechanism maximizes profits while protecting capital
4. HyperOpt Friendly: Many optimizable parameters, easy for backtesting and tuning

⚠️ Limitations

1. Too Many Parameters: Over 20 adjustable parameters, prone to overfitting historical data
2. Computationally Complex: Multiple indicator calculations require significant computing resources
3. 5-minute Timeframe: Sensitive to market noise, requires good market liquidity

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VIII. Applicable Scenario Recommendations

Market Environment	Recommended Configuration	Description
Oscillating Uptrend	Default parameters	Suitable for pullback buying strategy
Sideways Oscillation	Lower ewo_high	Capture oversold bounces
One-way Downtrend	Raise stoploss	Reduce stop loss trigger frequency
High Volatility	Lower antipump_threshold	Stricter anti-pump protection

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IX. Applicable Market Environment Detailed

SMA_BBRSI is a variant of the NostalgiaForX10 series. Based on its code architecture and long-term community live trading validation experience, it is best suited for oscillating uptrend trending markets, while performing poorly in extreme volatility or one-way crashes.

9.1 Strategy Core Logic

• EMA Offset Buying: Capture pullback opportunities in uptrends
• EWO Momentum Confirmation: Ensure sufficient momentum support when buying
• RSI Bollinger Bands: Use statistical channels to identify extreme prices

9.2 Performance in Different Market Environments

Market Type	Performance Rating	Reason Analysis
📈 Slow Bull Trend	⭐⭐⭐⭐⭐	EMA offset strategy naturally fits pullback buying
🔄 Sideways Oscillation	⭐⭐⭐⭐☆	RSI Bollinger Bands perform excellently in oscillation
📉 One-way Downtrend	⭐⭐☆☆☆	Stop loss may trigger frequently
⚡️ Extreme Volatility	⭐⭐☆☆☆	Anti-pump mechanism helps, but volatility itself is hard to handle

9.3 Key Configuration Recommendations

Configuration Item	Recommended Value	Description
timeframe	5m	Default value, suitable for most scenarios
stoploss	-0.10	Adjustable based on risk preference
antipump_threshold	0.15~0.25	Lower for high-volatility coins

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X. Important Reminder: The Cost of Complexity

10.1 Learning Cost

The strategy involves EWO, RSI Bollinger Bands, CTI, CCI and other technical indicators, requiring some quantitative trading foundation to deeply understand each parameter's function.

10.2 Hardware Requirements

Trading Pair Count	Minimum Memory	Recommended Memory
1-5 pairs	2GB	4GB
5-20 pairs	4GB	8GB
20+ pairs	8GB	16GB

10.3 Difference Between Backtesting and Live Trading

Parameters optimized via HyperOpt may perform excellently on historical data, but live trading may encounter:

• Slippage causing execution price deviation
• Market environment changes causing parameter failure
• Overfitting leading to poor adaptability to new market conditions

10.4 Manual Trader Recommendations

Manual execution of this strategy is not recommended because:

• Signal determination requires real-time calculation of multiple indicators
• Dynamic stop loss requires programmatic execution
• Anti-pump mechanism requires real-time monitoring

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XI. Summary

SMA_BBRSI is a technically dense multi-indicator composite strategy. Its core value lies in:

1. Multi-layer Validation: EMA, EWO, RSI, CCI and other indicators cross-validate
2. Dynamic Risk Control: Tiered stop loss + trailing stop + anti-pump triple protection
3. Optimizability: Rich HyperOpt parameters for strategy tuning

For quantitative traders, this is a strategy template worth in-depth study, but be aware of parameter overfitting risks. It's recommended to conduct thorough backtesting and paper trading validation before live trading.

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