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Scalp Strategy: The 1-Minute 1% Little Bee

Nickname: Mosquito Meat Harvester Occupation: Ultra-Short-Term Sniper Timeframe: 1 Minute (Fast enough, right?)

I. What is This Strategy?​

Simply put, Scalp is:

  • 1-minute chart watching, run at 1% profit
  • Use many small trades to cover occasional big losses
  • Author recommends running 60+ pairs simultaneously

Like a hardworking little bee, only collecting a little nectar each time, but visiting many flowers means lots of honey. 🐝

II. Core Configuration: Basically "Mosquito Meat is Still Meat"​

Take Profit Rule (ROI Table)​

Profit ≥ 1% → Take profit immediately

Translation: See 1% profit and run, won't wait another second. Like picking up coins, grab and go.

Stop Loss Rule​

Loss ≥ 4% → Admit defeat!

Translation: Stop loss is 4 times the take profit! Like betting $1 to win $4, but losing costs $16. Need super high win rate to make money. 😅

III. 1 Buy Condition: Simple and Brutal​

This strategy has just one buy condition, super simple:

🎯 The Only Buy Signal​

Core Logic: Oversold + Trend + Reversal Confirmation

Plain English:

"Price opens below EMA, and ADX shows there's a trend (not random oscillation), Stochastic is already oversold, then K line crosses above D line, that's when I rush in!"

Classic Lines:

ConditionCodePlain English Translation
Condition 1open < ema_low"Open price below EMA, meaning it's dropping"
Condition 2adx > 30"ADX above 30, there's a trend, not random oscillation"
Condition 3fastk < 30"K value below 30, oversold"
Condition 4fastd < 30"D value also below 30, confirming oversold"
Condition 5fastk crosses above fastd"K line crosses above D line, reversal signal!"

Simply Put: Dropped enough + Has trend + Starting to bounce = Buy!

IV. Sell Logic: Two Ways to Escape​

4.1 Target Take Profit​

Profit reaches 1% → Run!

Plain English: Make 1% and leave, no greed.

4.2 Active Sell Signals​

There are two situations that trigger active selling:

SignalConditionPlain English
EMA Take Profitopen >= ema_high"Price ran above EMA, time to go"
Overbought Exitfastk crosses above 70"K value above 70, overbought, run fast"
Overbought Exitfastd crosses above 70"D value also above 70, confirming overbought, run"

Plain English:

  • Price bounces to above EMA → Made enough, withdraw!
  • Stochastic overbought → At the top, withdraw!

V. Indicator System: Pitifully Simple​

5.1 EMA Three Brothers​

ema_high = EMA(5) of high price
ema_close = EMA(5) of close price
ema_low = EMA(5) of low price

Plain English: Use 5-period EMA to track high, close, and low prices separately, forming a "channel."

5.2 ADX Trend Strength​

ADX > 30 → Has trend
ADX < 20 → No trend (oscillation)

Plain English: ADX is used to judge if there's a trend. Below 30, the strategy won't buy at all.

5.3 Stochastic Fast (Quick Stochastic)​

K Period: 5
K Smoothing: 3
D Smoothing: 3

Plain English: Use the fast version of Stochastic, responds faster, suitable for 1-minute ultra-short-term.

5.4 Bollinger Bands (For Plotting Only)​

# This is for plotting, strategy logic doesn't use it!
bollinger = qtpylib.bollinger_bands(dataframe['close'], window=20, stds=2)

Complaint: The code calculates this, but buy and sell logic doesn't use it at all. Maybe the author forgot to delete it? 😅

VI. This Strategy's "Personality Traits"​

✅ Pros (Compliment Section)​

  1. Simple and Easy to Understand: Just one buy condition, elementary school students can understand
  2. Fast Execution: 1-minute cycle, quick in and out
  3. Clear Target: 1% take profit, no hesitation
  4. Streamlined Indicators: Just 3 core indicators, not flashy
  5. Suitable for Automation: Clear rules, programs execute without pressure

⚠️ Cons (Complaint Section)​

  1. Terrible Risk-Reward Ratio: 4% stop loss, 1% take profit, need to win 4 times to cover 1 loss
  2. No Protection Mechanisms: Nothing in the code, have to configure yourself
  3. Fees Eat You Alive: High-frequency trading fees accumulate to scary amounts
  4. Needs Tons of Trading Pairs: Author recommends 60+, high VPS cost
  5. Network Latency Sensitive: 1-minute cycle, delay a bit and signal is wasted

VII. Applicable Scenarios: When to Use It?​

Market EnvironmentRecommended ActionReason
📈 UptrendSuitableMany pullback oversold bounce opportunities
🔄 Oscillating MarketNot suitableADX < 30, strategy won't enter
📉 DowntrendUse with cautionBounces might be weak, easy to stop out
⚡ High VolatilitySuper suitableOversold bounce opportunities galore

VIII. Summary: How's This Strategy Really?​

One-Sentence Review​

"A simple and brutal ultra-short-term strategy, clear logic but terrible risk-reward ratio, needs high win rate and large trading volume to support."

Who Should Use It?​

  • ✅ People with low-fee channels (VIP, rebates, etc.)
  • ✅ People who can run 60+ trading pairs (need good VPS)
  • ✅ People with low network latency (close to exchange)
  • ✅ People who accept high-frequency trading fees

Who Shouldn't Use It?​

  • ❌ People with small capital (can't diversify risk)
  • ❌ People with low-spec VPS (can't run 60+ pairs)
  • ❌ People with high network latency (signals will fail)
  • ❌ People who don't like high-frequency trading

My Recommendations​

  1. Must configure protection mechanisms: This strategy has zero protection in the code!
  2. Fees must be low: With 0.1% fees, 1% profit gets eaten by 20%
  3. Win rate must be high: Stop loss is 4x take profit, below 80% win rate will lose money
  4. Test with simulation first: Don't go live immediately, run dry_run first

IX. What Market Can This Strategy Make Money In?​

9.1 Core Logic: Use High Win Rate to Cover Terrible Odds​

Scalp's core is oversold bounce. Its money-making philosophy:

"Find oversold pits, wait for bounces, make 1% and run, lose 4% and accept it. Win by volume!"

  • Oversold Identification: Stochastic Fast K/D < 30
  • Trend Filter: ADX > 30 ensures there's direction
  • Quick Exit: 1% take profit, no greed

9.2 Performance in Different Markets (Plain English Version)​

Market TypePerformance RatingPlain English Explanation
📈 Uptrend⭐⭐⭐⭐☆"Lots of pullback oversold opportunities, bounces easy to succeed"
🔄 Oscillating Market⭐⭐⭐☆☆"ADX under 30 won't buy, misses oscillation opportunities"
📉 Downtrend⭐⭐☆☆☆"Bounces very weak, easy to get stopped out"
⚡ High Volatility⭐⭐⭐⭐⭐"Oversold bounce opportunities everywhere, home field!"

One-Sentence Summary: Eat meat in volatile trending markets, drink water in low-volatility oscillating markets.

X. Want to Run This Strategy? Check These Configurations First​

10.1 Trading Pair Configuration​

Config ItemRecommended ValueComplaint
Timeframe1mDon't change, this is the core
Simultaneous Positions≥ 60Less can't diversify risk
Stop Loss-0.03 ~ -0.04Original is 4%, can tighten appropriately
Trading FeeThe lower the betterHigh fees will eat profits

10.2 Must-Configure Protection Mechanisms​

This strategy has ZERO protection in the code! You must add it yourself in config.json:

{
  "protections": [
    {
      "method": "CooldownPeriod",
      "stop_duration": 5
    },
    {
      "method": "MaxDrawdown",
      "trade_limit": 20,
      "stop_duration": 60,
      "max_allowed_drawdown": 0.15
    },
    {
      "method": "StoplossGuard",
      "lookback_period": 60,
      "trade_limit": 3,
      "stop_duration": 30
    }
  ]
}

10.3 Hardware Requirements (Important!)​

This strategy needs 60+ pairs, high VPS requirements:

Number of PairsMinimum MemoryRecommended MemoryExperience
60 pairs4GB8GBBarely enough
100 pairs8GB16GBSmooth
150+ pairs16GB32GBDon't skimp

Warning: Using low-spec VPS with many pairs may cause calculation timeouts, missed signals! 😅

10.4 Fee Impact (Super Important!)​

Ultra-short-term strategies are SUPER sensitive to fees:

Assuming 0.1% fee (buy + sell = 0.2%):
- Take profit 1%, fees eat 0.2%, actual profit 0.8%
- Fees are 20% of profit!

If fee is 0.2% (buy + sell = 0.4%):
- Take profit 1%, fees eat 0.4%, actual profit 0.6%
- Fees are 40% of profit!

Recommendations:

  • Find low-fee exchanges (VIP, rebates)
  • Must add fees in backtesting
  • If fees are too high, this strategy might work for nothing

XI. Bonus: The Strategy Author's "Little Secrets"​

Looking carefully at the code, you'll find some interesting things:

  1. Bollinger Bands Calculated but Not Used:

    # Code calculates Bollinger Bands, but buy/sell doesn't use it at all
    bollinger = qtpylib.bollinger_bands(...)

    "Maybe copy-pasted and forgot to delete? Or left for future expansion?"

  2. Recommends 60+ Trading Pairs:

    "we recommend to have at least 60 parallel trades at any time"

    The author directly tells you: This strategy has high risk running alone, needs the law of large numbers!

  3. Stop Loss is 4x Take Profit:

    "should not be below 3% loss"

    The author knows the stop loss is big, but that's ultra-short-term for you, small take profit, big stop loss.

XII. The Very Last​

One-Sentence Review​

"Scalp is a simple and brutal ultra-short-term strategy, logic so clear even elementary students can understand, but terrible risk-reward ratio, needs high win rate and large trading volume to compensate."

Who Should Use It?​

  • ✅ People with low-fee channels
  • ✅ People who can run many trading pairs
  • ✅ People with low network latency
  • ✅ People who accept high-frequency trading fees
  • ✅ People whose backtesting win rate reaches 70%+

Who Shouldn't Use It?​

  • ❌ People with small capital
  • ❌ People with low-spec VPS
  • ❌ People with high network latency
  • ❌ People with high fees
  • ❌ People who don't like high-frequency trading

Manual Trader Recommendations​

If you manually trade referencing this strategy, focus on:

  1. Stochastic Fast < 30: Oversold zone
  2. ADX > 30: Has trend, not random oscillation
  3. K crosses above D: Reversal signal
  4. 1% Take Profit: Don't be greedy, leave when reached

XIII. ⚠️ Risk Re-emphasis (Must Read This Part)​

Backtesting is Beautiful, Live Trading Be Cautious​

Scalp strategy backtesting might look great: make 1% each time, accumulating nicely. But note:

High-frequency trading fees and slippage are hidden killers. Backtest 1% take profit, live might only make 0.6%.

Simply put: Theory is beautiful, reality is harsh.

Risk-Reward Ratio is a Big Pit​

This strategy's risk-reward ratio is 1:4:

  • Need to win 4 times to offset 1 loss
  • Need at least 80% win rate to break even
  • After considering fees, need even higher win rate

Hidden Risks of High-Frequency Trading​

In live trading, high-frequency trading may cause:

  • Slippage Accumulation: Each trade has slippage, accumulates to scary amounts at high frequency
  • Network Latency: 1-minute cycle, signals are fleeting
  • Exchange Rate Limiting: Too frequent may be restricted by exchange
  • Fee Erosion: High-frequency trading fees are the biggest enemy

My Advice (Real Talk)​

1. Must add protection mechanisms (not in original code!)
2. Must find low-fee channels
3. Must add fees in backtesting
4. Test with simulation for at least 1 month first
5. Confirm win rate can reach 70%+ before live trading
6. Start with very small live positions

Remember: Stop loss is 4x take profit, need to win 4 times to cover 1 loss. If win rate isn't high enough, this strategy is a money-losing machine! 🙏