SMAOffsetProtectOptV1Mod2 Strategy Analysis

Strategy Number: #364 (364th of 465 strategies)
Strategy Type: SMA Offset + EWO Protection + RSI Filter + Antipump Protection Trend Following Strategy
Timeframe: 5 minutes (5m)

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I. Strategy Overview

SMAOffsetProtectOptV1Mod2 is an upgraded version of SMAOffsetProtectOptV1Mod, adding an "Antipump Protection" mechanism on top of the original foundation. By calculating price momentum strength (pump_strength), the strategy can identify and avoid buying after abnormal price pumps, thereby reducing the risk of being trapped. It also includes a sub-strategy SMAOffsetProtectOptV1Mod2_antipump, which can independently enable full antipump functionality.

Core Features

Feature	Description
Buy Conditions	2 independent buy signals + optional antipump protection
Sell Conditions	1 base sell signal + four-tier ROI take-profit + trailing stop
Protection Mechanism	EWO high/low threshold protection + RSI filter + antipump protection
Timeframe	Main timeframe 5m + informative timeframe 1h
Dependencies	talib, numpy, pandas, technical (ftt), qtpylib
Sub-strategy	SMAOffsetProtectOptV1Mod2_antipump

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II. Strategy Configuration Analysis

2.1 Basic Risk Parameters

# ROI exit table (four-tier declining)
minimal_roi = {
    "0": 0.028,    # Immediate: 2.8%
    "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 settings
stoploss = -0.10  # Fixed stop loss 10%

# Trailing stop
trailing_stop = True
trailing_stop_positive = 0.001      # Activate trailing after 0.1% profit
trailing_stop_positive_offset = 0.01  # Start trailing at 1% profit
trailing_only_offset_is_reached = True  # Only enable after offset is reached

Design Philosophy:

• ROI uses a four-tier stepped declining design, more refined than Mod1
• Trailing stop settings are the same as Mod1, conservative but protective
• Fixed 10% stop loss provides the last line of defense

2.2 Order Type Configuration

use_sell_signal = True        # Enable sell signal
sell_profit_only = True       # Only use sell signal when profitable
sell_profit_offset = 0.01     # Minimum profit requirement for sell signal: 1%
ignore_roi_if_buy_signal = False  # Do not ignore ROI

2.3 Comparison with Mod1

Feature	Mod1	Mod2
ROI Tiers	3 tiers	4 tiers
Antipump Protection	None	Yes (pump_strength)
Additional Indicators	None	ZEMA 30/200
Sub-strategy	None	antipump subclass
startup_candle_count	30	200

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III. Buy Conditions Detailed

3.1 Optimizable Parameters

Parameter Type	Parameter Name	Default	Optimization Range	Description
Buy	base_nb_candles_buy	16	5-80	EMA period
Buy	low_offset	0.973	0.9-0.99	Price offset coefficient
Buy	ewo_high	5.672	2.0-12.0	EWO high threshold
Buy	ewo_low	-19.931	-20.0 to -8.0	EWO low threshold
Buy	rsi_buy	59	30-70	RSI buy threshold
Buy	antipump_threshold	0.25	0-0.4	Antipump threshold
Sell	base_nb_candles_sell	20	5-80	Sell EMA period
Sell	high_offset	1.010	0.99-1.1	Sell price offset

3.2 Buy Conditions Detailed

Condition #1: Trend Confirmation Buy

# Logic
- Price below EMA * low_offset (pullback buy)
- EWO > ewo_high (strong trend confirmation)
- RSI < rsi_buy (not overbought)
- Volume > 0 (validity check)

Core Logic: Exactly the same as Mod1, waiting for pullback buying opportunities after trend confirmation.

Condition #2: Deep Oversold Buy

# Logic
- Price below EMA * low_offset (pullback buy)
- EWO < ewo_low (deeply negative)
- Volume > 0 (validity check)

Core Logic: Exactly the same as Mod1, capturing rebound opportunities after extreme oversold conditions.

3.3 Antipump Protection Mechanism (antipump)

The core new functionality in Mod2, calculation logic as follows:

# Calculate price momentum strength
zema_30 = ftt.zema(dataframe, period=30)
zema_200 = ftt.zema(dataframe, period=200)
pump_strength = (zema_30 - zema_200) / zema_30

Antipump Logic (only effective in antipump sub-strategy):

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

Interpretation:

• When pump_strength > antipump_threshold, buying is prohibited
• Default threshold is 0.25, meaning when short-term ZEMA is 25% higher than long-term ZEMA, it's considered abnormal
• Avoids chasing highs after a pump

3.4 Buy Condition Classification

Condition Group	Condition Number	Core Logic	Antipump Protection
Trend Following	Condition #1	High EWO + RSI filter	Effective in sub-strategy
Contrarian Bottom Fishing	Condition #2	Low EWO + no RSI limit	Effective in sub-strategy

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IV. Sell Logic Detailed

4.1 Four-Tier Take Profit System

The strategy uses a four-tier ROI take-profit mechanism (one more tier than Mod1):

Holding Time    Target Profit    Description
────────────────────────────────
Immediate       2.8%             Highest profit target
10 candles     1.8%             Short-term profit target
30 candles     1.0%             Medium-term profit target
40 candles     0.5%             Lowest profit target

Design Philosophy:

• One more "10 candles" intermediate tier than Mod1
• More refined profit management, avoiding premature selling or excessive waiting

4.2 Trailing Stop Mechanism

Parameter	Value	Description
trailing_stop	True	Enable trailing stop
trailing_stop_positive	0.1%	Trailing distance
trailing_stop_positive_offset	1%	Activation threshold
trailing_only_offset_is_reached	True	Only enable after threshold reached

4.3 Base Sell Signal (1)

# Sell signal 1: EMA offset sell
- Price > EMA(base_nb_candles_sell) * high_offset
- Volume > 0

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V. Technical Indicator System

5.1 Core Indicators

Indicator Category	Specific Indicator	Purpose
Trend	EMA (base_nb_candles_buy)	Buy baseline
Trend	EMA (base_nb_candles_sell)	Sell baseline
Trend	ZEMA 30	Short-term momentum (antipump)
Trend	ZEMA 200	Long-term trend (antipump)
Oscillator	EWO (50, 200)	Trend strength assessment
Oscillator	RSI (14)	Overbought/oversold filter
Risk	pump_strength	Pump strength detection

5.2 ZEMA (Zero Lag EMA) Detailed

Mod2 introduces ZLEMA (Zero Lag EMA) to calculate pump_strength:

zema_30 = ftt.zema(dataframe, period=30)   # Short-term zero-lag EMA
zema_200 = ftt.zema(dataframe, period=200)  # Long-term zero-lag EMA
pump_strength = (zema_30 - zema_200) / zema_30

Advantages:

• ZLEMA reduces lag compared to traditional EMA
• Faster response to price changes
• More accurate identification of short-term pump behavior

5.3 pump_strength Interpretation

pump_strength Value	Market State	Strategy Suggestion
< 0	Short-term below long-term	Downtrend or pullback
0 - 0.1	Normal uptrend	Normal trading
0.1 - 0.25	Strong uptrend	Watch for risk
> 0.25	Abnormal pump	Prohibit buying (antipump)

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VI. Risk Management Features

6.1 EWO Protection Mechanism

Same EWO protection as Mod1:

Protection Type	Parameter Description	Default
EWO high threshold	Strong trend confirmation	5.672
EWO low threshold	Extreme oversold identification	-19.931

6.2 Antipump Protection Mechanism (New)

antipump_threshold = DecimalParameter(0, 0.4, default=0.25)

Design Philosophy:

• Identifies abnormal short-term price increases
• Avoids chasing highs after pumps and getting trapped
• Only effective in SMAOffsetProtectOptV1Mod2_antipump sub-strategy

6.3 RSI Filter Mechanism

Same RSI filtering as Mod1:

• RSI < rsi_buy ensures not buying in overbought territory
• Only applied to trend confirmation buys (Condition #1)

6.4 Volume Verification

All buy and sell conditions require volume > 0.

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VII. Strategy Advantages and Limitations

✅ Advantages

1. Antipump Protection: New pump_strength indicator, avoids chasing highs and getting trapped
2. More Refined ROI: Four tiers, more flexible profit management
3. Sub-strategy Design: Can choose to enable/disable antipump functionality
4. Zero Lag Indicator: ZEMA responds faster than EMA

⚠️ Limitations

1. Increased Complexity: Added ZEMA and pump_strength calculations compared to Mod1
2. More Parameters: Parameters to optimize increased from 7 to 8
3. Antipump May Filter Opportunities: True strong breakouts may also be mistakenly judged as pumps
4. startup_candle_count increased to 200: Requires more historical data

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VIII. Applicable Scenario Recommendations

Market Environment	Recommended Configuration	Description
Normal Trend	Mod2 base version	No need for antipump protection
Abnormal Volatility	antipump sub-strategy	Enable antipump protection
High-risk Pairs	antipump + low threshold	Stricter protection
Low-volatility Pairs	Base version or high threshold	Avoid over-filtering

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IX. Applicable Market Environment Detailed

SMAOffsetProtectOptV1Mod2 is an upgraded version of SMAOffsetProtectOptV1Mod, adding an antipump protection mechanism. It performs best in markets with clear trends but occasional pumps, while performing poorly in continuously pumping or continuously falling markets.

9.1 Core Strategy Logic

• Trend Pullback Buy: Wait for price to pull back below EMA before buying
• Dual Protection: EWO confirms trend + RSI filters overbought
• Antipump Protection: Identify abnormal pumps through pump_strength
• Trailing Take Profit: Activate trailing stop after 1% profit

9.2 Performance in Different Market Environments

Market Type	Performance Rating	Reason Analysis
📈 Normal Uptrend	⭐⭐⭐⭐⭐	Pullback buy + trailing take profit + antipump protection
🚀 Fast Pump	⭐⭐⭐⭐☆	antipump can avoid chasing highs (sub-strategy)
🔄 Ranging/Sideways	⭐⭐☆☆☆	EMA false breakout issues still exist
📉 Downtrend	⭐☆☆☆☆	Long-only, cannot profit

9.3 Key Configuration Recommendations

Configuration Item	Recommended Value	Description
antipump_threshold	0.2-0.3	Adjust based on pair volatility
base_nb_candles_buy	16-25	Use longer period for trending markets
trailing_stop_positive_offset	0.01-0.02	Adjust based on pair volatility

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X. Important Note: The Cost of Complexity

10.1 Learning Cost

This strategy has approximately 200 lines of code (including sub-strategy), medium-high complexity:

• Need to understand EWO indicator principles
• Need to understand EMA offset strategy logic
• Need to understand ZEMA and pump_strength
• Need to master HyperOpt parameter optimization

10.2 Hardware Requirements

Number of Trading Pairs	Minimum Memory	Recommended Memory
1-10 pairs	2GB	4GB
10-50 pairs	4GB	8GB
50+ pairs	8GB	16GB

Note: startup_candle_count = 200, much higher than Mod1's 30, requires more historical data.

10.3 Differences Between Backtesting and Live Trading

• Backtesting may perform too well due to parameter fitting
• Antipump parameters need adjustment for different pairs
• Live trading slippage and fees will reduce returns

10.4 Recommendations for Manual Traders

Manual traders can learn from:

• pump_strength indicator to identify pumps
• ZEMA responds faster to trends than EMA
• Combine with EWO for trend strength judgment

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XI. Summary

SMAOffsetProtectOptV1Mod2 is an evolved version of SMAOffsetProtectOptV1Mod, with core upgrades:

1. Antipump Protection: Identifies abnormal pumps through pump_strength, avoids chasing highs and getting trapped
2. More Refined ROI: Four-tier stepped take-profit, more flexible profit management
3. Sub-strategy Design: Can choose to enable antipump functionality, flexibly adapting to different markets

For quantitative traders, this is a strategy with added risk protection on top of Mod1, suitable for traders concerned about pump risks. However, pay attention to antipump parameter tuning to avoid over-filtering normal opportunities.

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