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Cluc7werk Strategy In-Depth Analysis

Strategy ID: #90 (10th in Batch 9) Strategy Type: Bollinger Bands + Fisher RSI Filter + Dual Mode Confirmation Timeframe: 1 Minute (1m)

I. Strategy Overview​

Cluc7werk is an ultra short-cycle trading strategy based on Bollinger Bands and Fisher RSI indicators. The strategy's core feature is using Fisher RSI transformation for oversold filtering, combined with a dual-mode buy mechanism (Bollinger Band rebound + EMA volume-shrinking pullback). Compared to Cluc5werk, Cluc7werk simplifies multi-timeframe analysis and focuses on 1-minute intraday trading.

Key Features​

FeatureDescription
Buy Conditions2 modes (Bollinger Band rebound + EMA volume-shrinking pullback) + Fisher RSI filter
Buy ConfirmationSingle signal trigger (no consecutive confirmation)
Sell ConditionsPrice touches Bollinger middle band + EMA downward + Fisher RSI overbought
ProtectionFisher RSI filter + Hard stop-loss + Trailing stop
Timeframe1 Minute
DependenciesTA-Lib, qtpylib, numpy
Special FeaturesInverse Fisher RSI transformation, Dual-mode buy

II. Strategy Configuration Analysis​

2.1 Core Risk Parameters​

# ROI Exit Table
minimal_roi = {
    "0": 0.10,       # Immediate exit: 10% profit
    "60": 0.07,      # After 60 minutes: 7% profit
    "120": 0.05,     # After 120 minutes: 5% profit
    "240": 0.03      # After 240 minutes: 3% profit
}

# Position Management
max_open_trades = 5  # Maximum 5 simultaneous trading pairs

# Stop-Loss Setting
stoploss = -0.10     # -10% hard stop-loss

# Trailing Stop Configuration
trailing_stop = True
trailing_stop_positive = 0.01007     # Activates at 1% profit
trailing_stop_positive_offset = 0.01258  # Triggers at 1.26% profit
trailing_only_offset_is_reached = False

# Exit Signal Configuration
use_sell_signal = True
sell_profit_only = True
sell_profit_offset = 0.01
ignore_roi_if_buy_signal = True

Design Philosophy:

  • ROI Table: Uses aggressive profit target; 10% immediately upon entry, gradually lowering as time extends — contrasts with Cluc5werk's conservative style
  • Stop-Loss -10%: More compact than Cluc5werk's -22.4%; reflects stricter risk control
  • Trailing Stop: Activates at 1% profit; final stop-loss moves to 1.26% profit position; low activation threshold
  • Maximum 5 Positions: Allows holding 5 different trading pairs simultaneously; risk diversification

2.2 Buy Parameter Configuration​

buy_params = {
    'bbdelta-close': 0.00732,      # Bollinger delta as % of close price
    'bbdelta-tail': 0.94138,       # tail to bbdelta ratio
    'close-bblower': 0.0199,       # Close to Bollinger lower band ratio
    'closedelta-close': 0.01825,   # Close delta as % of close price
    'fisher': -0.22987,            # Fisher RSI threshold (buy)
    'volume': 16                   # Volume multiple
}

2.3 Sell Parameter Configuration​

sell_params = {
    'sell-bbmiddle-close': 0.99184,  # Close price as % of Bollinger middle band
    'sell-fisher': 0.26832            # Fisher RSI threshold (sell)
}

III. Entry Conditions Details​

3.1 Core Filter Condition (Must Satisfy)​

Fisher RSI Transformation:

# Calculation
rsi = ta.RSI(dataframe, timeperiod=9)
rsi_transformed = 0.1 * (rsi - 50)
dataframe['fisher-rsi'] = (np.exp(2 * rsi_transformed) - 1) / (np.exp(2 * rsi_transformed) + 1)

# Filter condition
dataframe['fisher-rsi'].lt(params['fisher'])  # fisher-rsi < -0.22987
  • Fisher RSI is an Inverse Fisher transformation of traditional RSI, mapping RSI values from [0, 100] to [-1, 1]
  • fisher-rsi < -0.22987 indicates RSI below ~38 (oversold zone)
  • This is the strategy's first layer of protection; only considers buying in oversold zones

3.2 Mode 1: Bollinger Band Rebound Buy​

# Condition A: Bollinger Band rebound pattern
(
    dataframe['bb1-delta'].gt(dataframe['close'] * params['bbdelta-close']) &
    dataframe['closedelta'].gt(dataframe['close'] * params['closedelta-close']) &
    dataframe['tail'].lt(dataframe['bb1-delta'] * params['bbdelta-tail']) &
    dataframe['close'].lt(dataframe['lower-bb1'].shift()) &
    dataframe['close'].le(dataframe['close'].shift())
)

Conditions:

  1. bb1-delta > close × 0.00732: Distance between BB middle and lower > 0.732% of close; BB has meaningful width
  2. closedelta > close × 0.01825: Close price has significant rise vs previous candle (1.825%); relatively high threshold
  3. tail < bb1-delta × 0.94138: Lower shadow < 94.138% of BB bandwidth; lower shadow relatively tight
  4. close < lower-bb1.shift(): Close below previous candle's BB lower band; forms "breakdown" pattern
  5. close ≤ close.shift(): Close not higher than previous candle; confirms weak price action

Pattern Interpretation: Captures "false breakout" rebound. Price briefly breaks BB lower band then quickly rebounds; forms hammer-like pattern. The higher closedelta requirement (1.825%) means it needs relatively obvious upward momentum.

3.3 Mode 2: EMA Volume-Shrinking Pullback Buy​

# Condition B: EMA volume-shrinking pullback pattern
(
    (dataframe['close'] < dataframe['ema_slow']) &
    (dataframe['close'] < params['close-bblower'] * dataframe['lower-bb2']) &
    (dataframe['volume'] < (dataframe['volume_mean_slow'].shift(1) * params['volume']))
)

Conditions:

  1. close < ema_slow: Close below 48-period EMA; below long-term MA
  2. close < lower-bb2 × 0.0199: Close below BB lower band by 1.99%; price breaks BB
  3. volume < volume_mean_slow.shift(1) × 16: Volume below previous 24-period average × 16 (volume shrinkage)

Pattern Interpretation: Captures panic drop oversold rebound. Price below EMA and breaks BB, with shrinking volume — indicating selling pressure exhaustion.

3.4 Buy Signal Trigger Mechanism​

# Buy signal: satisfies Fisher RSI filter + either mode
dataframe.loc[
    (dataframe['fisher-rsi'].lt(params['fisher'])) &
    (
        Mode A conditions | Mode B conditions
    ),
    'buy'
] = 1

Design Intent: Compared to Cluc5werk's dual confirmation (two consecutive candles), Cluc7werk simplifies the confirmation mechanism — single satisfying condition triggers buy. This makes entry more sensitive but may increase false signal risk.

IV. Exit Logic Details​

4.1 Sell Conditions​

dataframe.loc[
    ((dataframe['close'] * params['sell-bbmiddle-close']) > dataframe['mid-bb2']) &
    dataframe['ema_fast'].gt(dataframe['close']) &
    dataframe['fisher-rsi'].gt(params['sell-fisher']) &
    dataframe['volume'].gt(0)
    ,
    'sell'
] = 1

Conditions:

  1. Price touching Bollinger middle band: close × 0.99184 > mid-bb2; close reaches 99.184%+ of BB middle band; near middle band
  2. Short-term MA downward: ema_fast > close; 6-period EMA above current price; short-term trend weakening
  3. Fisher RSI overbought: fisher-rsi > 0.26832; corresponds to RSI above ~63; entering overbought zone
  4. Valid volume: Volume > 0

Pattern Interpretation: Sell combines price position (touching BB middle), technical indicator (MA turning + overbought), and volume confirmation. This multi-confirmation ensures exit when price starts weakening.

V. Technical Indicator System​

5.1 Bollinger Band Indicators​

Indicator NameCalculationParameterPurpose
lower-bb1TA-Lib BBANDS40 periodsBuy: price vs lower band
bb1-delta|mid-bb1 - lower-bb1|-Buy: BB bandwidth filter
lower-bb2qtpylib BBANDS20 periodsBuy: price vs lower band
mid-bb2qtpylib BBANDS20 periodsSell: price vs middle band

5.2 Moving Average Indicators​

Indicator NameCalculationParameterPurpose
ema_fastTA-Lib EMA6 periodsSell: short-term trend judgment
ema_slowTA-Lib EMA48 periodsBuy: long-term trend judgment
volume_mean_slowRolling mean24 periodsBuy: volume filter

5.3 Momentum Indicators​

Indicator NameCalculationParameterPurpose
rsiTA-Lib RSI9 periodsFisher RSI calculation base
fisher-rsiInverse Fisher transform-Buy/sell filter
closedelta|close - close.shift()|-Buy: price volatility strength
tail|close - low|-Buy: lower shadow length

5.4 Indicator Relationship Diagram​

┌─────────────────────────────────────────┐
│  Fisher RSI < -0.22987 (oversold filter)│
│  = RSI < ~38                            │
└─────────────────────────────────────────┘
                    ↓
┌─────────────────────────────────────────┐
│  Mode A: Bollinger Band rebound          │
│  - bb1-delta > close × 0.732%           │
│  - closedelta > close × 1.825%          │
│  - tail < bb1-delta × 94.138%           │
│  - close < lower-bb1.shift()            │
│  - close ≤ close.shift()                │
│                                          │
│  Mode B: EMA volume-shrinking pullback   │
│  - close < ema_slow (48 EMA)            │
│  - close < lower-bb2 × 1.99%            │
│  - volume < avg × 16                    │
└─────────────────────────────────────────┘
                    ↓
┌─────────────────────────────────────────┐
│  Buy: Single signal trigger             │
└─────────────────────────────────────────┘
                    ↓
┌─────────────────────────────────────────┐
│  Sell: Triple confirmation               │
│  - close > mid-bb2 × 99.184%           │
│  - ema_fast > close (6 EMA downward)    │
│  - fisher-rsi > 0.26832 (overbought)    │
└─────────────────────────────────────────┘

VI. Risk Management Features​

6.1 Multi-Layer Protection​

  1. Fisher RSI Filter Layer: Ensures buying only in oversold zones (RSI < 38)
  2. Dual-Mode Buy Layer: Two complementary buy modes cover different scenarios
  3. Hard Stop-Loss Layer: -10% stop-loss; more compact than Cluc5werk
  4. Trailing Stop Layer: Activates at 1% profit; protects floating profits

6.2 Profit-Taking Strategy​

  • ROI Progressive Exit: Gradually lowers profit targets as holding extends (10% → 7% → 5% → 3%)
  • Trailing Stop Protection: Retains more profit when trend continues
  • Multi-Condition Exit: Price touching BB middle + MA turning + overbought confirmation

6.3 Risk-Return Characteristics​

ParameterValueDescription
Maximum positions5 trading pairsDiversify risk
Profit targets10% / 7% / 5% / 3%Aggressive targets
Stop-loss-10%Compact stop-loss
Trailing stop activation1% profitLow threshold activation
Average holding timeEstimated 1-4 hoursUltra short-cycle trading

6.4 Risk Management Comparison with Cluc5werk​

FeatureCluc5werkCluc7werk
Stop-loss-22.4%-10%
First target profit2.13%10%
Trailing stop activation18.6%1%
Trend filter1-hour ROCRFisher RSI
Buy confirmation2 consecutive candlesSingle signal

VII. Strategy Pros & Cons​

7.1 Advantages​

  1. Aggressive Profit Target: 10% first target far exceeds most strategies
  2. Fisher RSI Filter: Compared to simple RSI, Inverse Fisher transformation provides better overbought/oversold signals
  3. Dual-Mode Buy: Two complementary buy modes cover different scenarios
  4. Compact Stop-Loss: -10% stop-loss more conservative than Cluc5werk
  5. Low-Threshold Trailing Stop: Activates at 1%; timely profit protection
  6. No Multi-Timeframe Dependency: Simplified analysis; only needs 1-minute data

7.2 Limitations​

  1. Too Short Timeframe: 1-minute timeframe susceptible to market noise
  2. Single Confirmation Risk: Single signal may increase false signal probability vs consecutive confirmation
  3. Aggressive Target Hard to Achieve: 10% target may be difficult in single trades
  4. Liquidity Requirement: Needs high-volume trading pairs for normal operation
  5. High Volatility Dependency: Needs sufficient market volatility to trigger buy conditions

VIII. Applicable Scenarios​

  • High-volatility coins: ALT, SHIB, newly listed tokens
  • Quick rebound行情: Strategy excels at capturing oversold quick rebounds
  • Markets with sufficient liquidity: High-volume pairs to avoid slippage
  • High-return pursuing investors: 10% target suits aggressive traders
  • Low-volatility coins: Insufficient volatility to trigger buy conditions
  • Ranging markets: Fisher RSI filter may be too strict
  • Illiquid trading pairs: Slippage reduces actual returns
  • Conservative investors: 10% target may be too aggressive

8.3 Variant Suggestions​

Based on Cluc7werk, consider these adjustments:

Adjustment DirectionSuggestion
ConservativeRaise stop-loss to -15%; lower first target to 5%
BalancedAdd two-consecutive-candle confirmation
Trend-followingAdd 1-hour ROCR trend filter

IX. Applicable Market Environment Details​

9.1 Best Market Environments​

  1. High volatility: Price frequently fluctuates significantly; triggers Bollinger Band breakouts
  2. Quick drop and rebound: Fisher RSI < -0.22987 captures oversold opportunities
  3. Sufficient liquidity: Good trading depth; tight bid-ask spread

9.2 Average Performance Markets​

  1. Ranging oscillation: Fisher RSI filter filters out most signals
  2. Slow decline: Continuous drops may not trigger rebound mode
  3. Low volatility: Bollinger Bands narrow; difficult to trigger buy conditions

9.3 Market Environment Identification​

Recommendations for judging market environment:

  • Fisher RSI value: Below -0.3, closely watch for buy opportunities
  • Bollinger Band width: Increase trading frequency when expanding
  • Volume: Higher market activity when volume increases

X. Important Notes: The Cost of Complexity​

10.1 Aggressive Target Risks​

Cluc7werk sets a 10% first target profit; very aggressive. In actual trading:

  1. Slippage impact: Actual execution price may deviate from signal price
  2. Liquidity risk: Large orders may not fill at target price
  3. Market impact: Buying may push price up; reduces actual profit

10.2 Parameter Stability Recommendations​

  • Use default parameters: Do not arbitrarily modify optimized parameters
  • Validate across time periods: Backtest across different time periods
  • Small-capital live testing: Sufficient paper trading before real capital
  • Close monitoring: Higher profit targets require more frequent market monitoring

10.3 Monitoring Focus​

  1. Fill rate: Whether target orders are filling
  2. Holding time: Whether reaching target in reasonable time
  3. Signal frequency: Too few or too many signals both indicate problems
  4. Drawdown: Whether overall account drawdown is within acceptable range

XI. Summary​

Cluc7werk is a aggressively designed ultra short-cycle trading strategy, integrating Fisher RSI transformation, Bollinger Band pattern recognition, and dual-mode buy mechanism. Its core characteristics are high profit target (10%) and compact stop-loss (-10%).

Key Features:

  • Uses Fisher RSI for oversold filtering; ensures buy safety
  • Two complementary buy modes (Bollinger Band rebound + EMA volume-shrinking pullback)
  • Single signal trigger; more sensitive entry
  • Aggressive profit target setting (10% first target)

Usage Recommendations:

  • Recommended for experienced traders; beginners should be cautious
  • Prioritize high-liquidity trading pairs
  • Keep parameters unchanged; avoid over-optimization
  • Monitor signal quality combined with market environment
  • Practice sound risk management; do not exceed comfortable position sizes

Risk Warning:

  • 10% profit target may be difficult to achieve in single trades
  • 1-minute timeframe susceptible to noise
  • Single confirmation may increase false signal probability

The strategy's backtest performance needs further verification; investors should recognize the inherent risks of ultra short-cycle strategies and conduct sufficient live testing before applying real capital.