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SampleStrategyV2 Strategy Analysis

Strategy Number: #372 (372nd of 465 strategies)
Strategy Type: RSI Trend Following + Heikin Ashi Trend Confirmation
Timeframe: 5 minutes (5m) + 1 hour (1h) informative layer

I. Strategy Overview​

SampleStrategyV2 is a concise example strategy provided by Freqtrade officially, demonstrating the basic framework of strategy development and the application of common technical indicators. This strategy uses RSI overbought/oversold signals combined with TEMA (Triple Exponential Moving Average) and Bollinger Bands for trend following, and introduces Heikin Ashi smoothing technology for trend confirmation.

Core Features​

FeatureDescription
Buy Conditions1 composite buy signal
Sell Conditions1 composite sell signal
Protection MechanismBasic stop loss + trailing stop
TimeframeMain timeframe 5m + informative timeframe 1h
Dependenciestalib, qtpylib, pandas
Hyperopt Parametersbuy_rsi, buy_trend_length, sell_rsi

II. Strategy Configuration Analysis​

2.1 Basic Risk Parameters​

# ROI exit table
minimal_roi = {
    "60": 0.01,   # Exit at 1% profit after 60 minutes
    "30": 0.02,   # Exit at 2% profit after 30 minutes
    "0": 0.04     # Exit at 4% profit immediately
}

# Stop loss setting
stoploss = -0.20   # Fixed stop loss at 20%

# Trailing stop
trailing_stop = True
trailing_only_offset_is_reached = True
trailing_stop_positive = 0.005     # Start trailing at 0.5% profit
trailing_stop_positive_offset = 0.01  # Begin trailing at 1% profit

Design Rationale:

  • ROI table adopts progressive design: higher short-term targets, lower long-term targets
  • 20% fixed stop loss is relatively loose, suitable for volatile markets
  • Trailing stop activates after reaching 1% profit, protecting small gains

2.2 Order Type Configuration​

order_types = {
    'buy': 'limit',
    'sell': 'limit',
    'stoploss': 'market',
    'stoploss_on_exchange': False
}

order_time_in_force = {
    'buy': 'gtc',
    'sell': 'gtc'
}

Buy and sell use limit orders, stop loss uses market orders to ensure execution.

III. Buy Condition Detailed Analysis​

3.1 Buy Signal Logic​

The strategy uses a single composite buy condition, requiring multiple sub-conditions to be met simultaneously:

# Buy signal
(
    # Main signal: RSI crosses above buy_rsi threshold from below
    (qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) &
    
    # Trend confirmation: Heikin Ashi trend direction upward
    (dataframe['trend_dir'] > 0) &
    
    # Price position: TEMA below Bollinger Band middle band
    (dataframe['tema'] <= dataframe['bb_middleband']) &
    
    # Momentum confirmation: TEMA is rising
    (dataframe['tema'] > dataframe['tema'].shift(1)) &
    
    # Volume verification: volume not zero
    (dataframe['volume'] > 0)
)

3.2 Condition Breakdown​

Sub-conditionDescriptionTechnical Meaning
RSI CrossRSI crosses above 30 from belowOversold rebound signal
Trend Upwardtrend_dir > 0Heikin Ashi trend is rising
TEMA<BB MiddleTEMA position is lowPrice at relatively low level
TEMA RisingTEMA is going upMomentum starting to strengthen
Volume>0Basic verificationMarket has activity

3.3 Hyperopt Parameters​

buy_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True)
buy_trend_length = IntParameter(low=50, high=288, default=288, space='buy', optimize=True, load=True)
  • buy_rsi: RSI cross threshold, range 1-50, default 30
  • buy_trend_length: Heikin Ashi trend calculation period, range 50-288, default 288

IV. Sell Logic Detailed Analysis​

4.1 Sell Signal Logic​

# Sell signal
(
    # Main signal: RSI crosses above sell_rsi threshold from below
    (qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) &
    
    # Price position: TEMA above Bollinger Band middle band
    (dataframe['tema'] > dataframe['bb_middleband']) &
    
    # Momentum confirmation: TEMA is falling
    (dataframe['tema'] < dataframe['tema'].shift(1)) &
    
    # Volume verification: volume not zero
    (dataframe['volume'] > 0)
)

4.2 Condition Breakdown​

Sub-conditionDescriptionTechnical Meaning
RSI CrossRSI crosses above 70 from belowOverbought signal
TEMA>BB MiddleTEMA position is highPrice at relatively high level
TEMA FallingTEMA is going downMomentum starting to weaken
Volume>0Basic verificationMarket has activity

4.3 Hyperopt Parameters​

sell_rsi = IntParameter(low=50, high=100, default=70, space='sell', optimize=True, load=True)
  • sell_rsi: RSI cross threshold, range 50-100, default 70

V. Technical Indicator System​

5.1 Core Indicators​

Indicator CategorySpecific IndicatorsPurpose
Momentum TypeRSI(14)Overbought/oversold judgment
Momentum TypeADXTrend strength
Momentum TypeMFIMoney flow
Momentum TypeMACDTrend direction
Momentum TypeStochastic FastFast stochastic indicator
Volatility TypeBB(20) - STD2Price volatility boundary
Trend TypeTEMA(9)Triple Exponential Moving Average
Trend TypeSARParabolic SAR
Smoothing TypeHeikin AshiPrice smoothing
Cycle TypeHT_SINEHilbert Transform Sine Wave
Volatility TypeATRAverage True Range

5.2 Heikin Ashi Trend Calculation​

# Heikin Ashi smoothing
heikinashi = qtpylib.heikinashi(dataframe)
dataframe['ha_open'] = heikinashi['open']
dataframe['ha_close'] = heikinashi['close']
dataframe['ha_high'] = heikinashi['high']
dataframe['ha_low'] = heikinashi['low']

# Trend direction calculation
dataframe['ha_open_sma288'] = ta.SMA(dataframe['ha_open'], timeperiod=self.buy_trend_length.value)
dataframe['ha_close_sma288'] = ta.SMA(dataframe['ha_close'], timeperiod=self.buy_trend_length.value)
dataframe['trend_dir'] = ta.SMA(ta.SMA(dataframe['ha_close_sma288'] - dataframe['ha_open_sma288'], timeperiod=5), timeperiod=5)

5.3 Informative Timeframe Indicators (1h)​

The strategy uses 1h as the informative layer:

informative = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe='1h')
macd = ta.MACD(informative)
informative['macd'] = macd['macd']
informative['macdsignal'] = macd['macdsignal']
informative['macdhist'] = macd['macdhist']

1h MACD is used for large-cycle trend judgment.

VI. Risk Management Features​

6.1 Basic Stop Loss​

stoploss = -0.20  # 20% stop loss

Relatively loose stop loss setting, suitable for volatile cryptocurrency markets.

6.2 Trailing Stop​

trailing_stop = True
trailing_only_offset_is_reached = True
trailing_stop_positive = 0.005     # Activate trailing at 0.5% profit
trailing_stop_positive_offset = 0.01  # Begin trailing at 1% profit

Trailing stop design:

  • Trailing mechanism activates after reaching 1% profit
  • Sell triggers on 0.5% pullback from high
  • Locks in small profits

6.3 ROI Protection​

Time        Profit Target
─────────────────────────
0 min       4%
30 min      2%
60 min      1%

Longer holding time means lower profit target, preventing profit giveback.

VII. Strategy Advantages and Limitations​

✅ Advantages​

  1. Clear Structure: Concise code, easy to understand and modify
  2. Hyperopt Support: 3 optimizable parameters, easy strategy tuning
  3. Official Example: Provided by Freqtrade, standardized framework
  4. Heikin Ashi Smoothing: Reduces noise signals, improves trend identification accuracy
  5. Multi-indicator Combination: RSI+TEMA+BB+HA multi-dimensional verification

⚠️ Limitations​

  1. Single Buy Condition: Only one buy signal, low signal density
  2. Wide Stop Loss: 20% stop loss may incur larger losses
  3. Lack of Protection Mechanisms: No EMA filtering, pump protection, etc.
  4. Example Positioning: Primarily for learning, live trading effectiveness needs verification

VIII. Applicable Scenario Recommendations​

Market EnvironmentRecommended ConfigurationDescription
Trend MarketDefault configurationRSI oversold rebound captures trend entry
Volatile MarketLower buy_rsiWait for deeper oversold
Calm MarketRaise sell_rsiExtend holding time

IX. Applicable Market Environment Details​

SampleStrategyV2 is an entry-level trend following strategy. Based on its concise design, it is most suitable for markets with clear trends, while signals may be sparse in oscillating markets.

9.1 Strategy Core Logic​

  • RSI Oversold Rebound: Wait for RSI to cross 30 to trigger buy
  • TEMA Position Verification: Ensure price is at relatively low level
  • Heikin Ashi Trend: Use smoothed price to confirm trend direction
  • Multiple Verification: Buy requires multiple conditions to be met simultaneously

9.2 Performance in Different Market Environments​

Market TypePerformance RatingReason Analysis
📈 Uptrend⭐⭐⭐⭐☆Oversold pullback entry effective, trend confirmation accurate
🔄 Oscillating Market⭐⭐☆☆☆Single condition, sparse signals
📉 Downtrend⭐☆☆☆☆20% stop loss may be too large
⚡ Fast Volatility⭐⭐☆☆☆HA smoothing may lag

9.3 Key Configuration Recommendations​

Configuration ItemRecommended ValueDescription
buy_rsi25-35Adjust based on market volatility
sell_rsi65-75Adjust based on trend strength
buy_trend_length200-288Longer period is more stable

X. Important Note: Learning vs Live Trading Difference​

10.1 Learning Cost​

Strategy code is concise, suitable for learning:

  • Understand Freqtrade strategy framework
  • Master common technical indicator applications
  • Learn Heikin Ashi smoothing technology
  • Understand Hyperopt parameter optimization

10.2 Hardware Requirements​

startup_candle_count: int = 1000

Needs 1000 candles of startup data, moderate computational resource requirements:

Number of Trading PairsMinimum MemoryRecommended Memory
20-402GB4GB
40-804GB8GB

10.3 Backtest vs Real Trading Difference​

As an example strategy, backtest performance may be unstable:

  • Few parameters, easy to optimize
  • But lacks protection mechanisms, high live trading risk
  • Recommend dry-run testing before considering live trading

10.4 Manual Trader Advice​

Conditions are relatively simple, manual traders can reference:

  • Watch for RSI crossing 30 signal
  • Check TEMA position and direction
  • Use Heikin Ashi to determine trend

XI. Conclusion​

SampleStrategyV2 is a clear entry-level example strategy. Its core value lies in:

  1. Teaching Demonstration: Shows standard usage of Freqtrade strategy framework
  2. Concise Structure: Easy to understand and secondary development
  3. Hyperopt Friendly: 3 optimizable parameters for easy tuning

For quantitative traders, this strategy is suitable for learning and secondary development. You can add more buy conditions and protection mechanisms on this basis to gradually build a more complete strategy system.