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bbema: Simplest EMA Crossover + Bollinger Band Auxiliary

Nickname: Strategy World's "Elementary Student", Entry-Level Player, Chill Player
Profession: Minimalist who places orders when two moving averages cross
Timeframe: 1 hour (Long-term player)

1. What's This Thing?​

Simply put, bbema is:

  • A minimalist strategy with only 2 moving averages
  • A simple logic of golden cross buy, death cross sell
  • Bollinger Bands just decoration — calculated but not used
  • A chill player that runs at 20% profit
  • One of Freqtrade's official default strategies

Like a kid just learning to ride a bike — pedals with two legs and goes, no fancy moves 🚲

Why called bbema?

  • bb = Bollinger Bands
  • ema = Exponential Moving Average

Sounds advanced? Actually Bollinger Bands don't participate in trading signals at all, just "decoration" 😂

2. Core Config: Basically "Wait for Big Trend"​

Profit-Taking Rules (ROI Table)​

Hold → Run at 20% profit 🤑

Translation:

"I'm not greedy, run after doubling... oh wait, 20% is enough. But honestly, 20% for 1-hour level, a bit hard to trigger."

Stoploss Rules​

Loss 10% → Leave

Translation:

"I admit defeat at 10% drop, not playing with you anymore. This is standard stoploss line in crypto circle."

Order Types​

TypeSetting
EntryLimit order (save fees)
ExitLimit order (save fees)
StoplossMarket order (ensure execution)

3. 1 Entry Condition: EMA Golden Cross​

This strategy's entry condition simple to unbelievable — just one!

🎯 Category 1: Trend Confirmation (1 Condition)​

Core Logic: EMA10 crosses above EMA50

Plain English:

"10-period MA shoots up from below, exceeds 50-period MA — golden cross! BUY!"

Code looks like:

# Just this one line, really just this one line
qtpylib.crossed_above(dataframe["ema10"], dataframe["ema50"])

What's Golden Cross?

Imagine two lines racing:

  • EMA10 is sprinter (reacts fast, recent prices weighted more)
  • EMA50 is marathon runner (steady, changes slow)

When sprinter catches up from behind and overtakes marathon runner — this is golden cross!

Why use EMA not SMA?

EMA more sensitive to recent prices, reacts faster. Like you care more about today's mood than average mood of past month 😄

4. Protection: ...None!​

This strategy has no protection mechanisms at all!

Don't look, really none. Like a house with unlocked door — door wide open, anyone can enter 🏠

What's Protection Mechanism?

Complex strategies usually have these "fuses":

  • Confirmation conditions to prevent false breakouts
  • Filtering conditions to prevent ranging markets
  • Protection conditions to prevent sharp drops

bbema's attitude:

"Protection? What protection? Golden cross is signal, just do it!"

This is also why said suitable for beginners learning — code simple, logic clear, but live trading easily gets educated by market 🎓

5. Exit Logic: EMA Death Cross​

Exit logic completely symmetrical with entry — this is "long-short symmetrical design".

5.1 Base Exit Signal (1)​

Core Logic: EMA50 crosses above EMA10

Plain English:

"50-period MA falls from above, crosses through 10-period MA — death cross! SELL!"

Code looks like:

# Also one line, completely symmetrical with entry
qtpylib.crossed_above(dataframe["ema50"], dataframe["ema10"])

What's Death Cross?

Continue using race metaphor:

  • Sprinter (EMA10) gets tired while running
  • Marathon runner (EMA50) slowly catches up
  • When marathon runner overtakes sprinter — this is death cross!

Usually means: short-term momentum weakening, may fall.

5.2 Take-Profit/Stoploss​

Exit MethodTrigger ConditionPlain English
Take-ProfitProfit ≥ 20%"Made 20%, done!"
StoplossLoss ≥ 10%"Lost 10%, run!"
Death CrossEMA50 crosses above EMA10"Trend reversed, retreat!"

Problem: 20% take-profit too high!

For 1-hour level to rise 20%, how long to wait? Might wait until flowers wither 🌸

6. This Strategy's "Personality Traits"​

✅ Pros (Praise Section)​

  1. Simple to no friends: Code just dozens of lines, beginners understand at a glance
  2. Long-Short Symmetry: Entry/exit logic consistent, no bias
  3. Few Parameters: Just two EMAs, small tuning space, hard to overfit
  4. Learning Friendly: Freqtrade official default strategy, lots of docs, good community support

⚠️ Cons (Roast Section)​

  1. No Protection: No filtering at all, tons of false signals
  2. 20% Too High: For 1-hour level, this take-profit basically decoration
  3. Doesn't Distinguish Trend: Same set in bull/bear markets, gets slapped repeatedly in ranging markets
  4. Bollinger Bands Useless: Has bb in name, but Bollinger Bands just for looking, isn't this deceiving 🤣

One-Sentence Summary:

"This is teaching entry strategy, not live trading money-making tool."

7. Applicable Scenarios: When to Use It?​

Market EnvironmentRecommended ActionReason
Clear uptrend✅ UsableGolden cross can catch trend
Clear downtrend✅ Usable (short)Death cross can exit timely
Ranging sideways❌ Don't useWill get repeatedly stoplossed
Violent volatility⚠️ Caution10% stoploss may trigger frequently

Best Scenarios:

  • Crypto big bull market, trend clear
  • Or you want to learn strategy code, use it as textbook

Worst Scenarios:

  • Ranging market, price repeatedly crosses between two MAs
  • Will constantly "buy→stoploss→buy→stoploss", fees make you doubt life

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

One-Sentence Review​

"Quant trading's 'Hello World' — beginner must-learn, veteran must-abandon."

Who Should Use It?​

  • ✅ Quant trading beginners (learning strategy code structure)
  • ✅ People wanting to understand EMA crossover principles
  • ✅ People wanting to test Freqtrade platform features
  • ✅ Beginners who don't mind losing money practicing

Who Should NOT Use It?​

  • ❌ People wanting to make money with strategy live trading
  • ❌ Ranging market traders
  • ❌ Investors with risk control requirements
  • ❌ People who mastered basics wanting to advance

My Suggestions​

  1. Use as textbook: Learn EMA crossover, indicator calculation, strategy structure
  2. Don't go live directly: Add some protection mechanisms before considering
  3. Adjust parameters: Change take-profit to 5-10%, don't wait for 20%
  4. Add filtering conditions: At least add RSI or volume filtering

9. What Markets Can This Strategy Make Money In?​

9.1 Core Logic: Trend Following's "Naked Version"​

bbema is simplest trend following strategy, code volume maybe just 50 lines, what concept? Length of an intro tutorial 📖

Its Profit Philosophy:

"I follow when trend comes, I retreat when trend leaves."

  • Simple and Brutal: No complex confirmation conditions
  • Fast Reaction: EMA more sensitive than traditional MAs
  • No Protection: Gets repeatedly harvested in ranging markets

9.2 Performance in Different Markets (Plain English Version)​

Market TypePerformance RatingPlain English Explanation
📈 Clear uptrend⭐⭐⭐⭐☆Golden cross catches trend, can eat big meat
📉 Clear downtrend⭐⭐⭐⭐☆Death cross exits timely, protects principal
🔄 Ranging sideways⭐☆☆☆☆Repeated golden/death cross, fees eat you full
⚡️ Sharp rise/fall⭐⭐☆☆☆Reaction may lag, miss best entry points

One-Sentence Summary:

"Can drink soup when trend clear, gets repeatedly slapped in ranging markets."

10. Want to Run This Strategy? Check These Configs First​

10.1 Pair Configuration​

Configuration ItemSuggested ValueRoast
Number of pairs1-10Don't be greedy, test first
Timeframe1h (default)Can also try 4h
Min volumeNormal settingsNo special requirements

10.2 Parameter Adjustment Suggestions​

# Default take-profit (too aggressive)
minimal_roi = {"0": 0.20}  # 20%, wait you to death

# Suggest change to
minimal_roi = {
    "0": 0.10,  # 10% immediate take-profit
    "30": 0.05,  # Run at 5% after 30 min
    "60": 0.02   # Accept 2% after 1 hour
}

# Stoploss can keep
stoploss = -0.10  # 10%, standard setting

10.3 Hardware Requirements (Important!)​

This strategy very lightweight, extremely low hardware requirements:

Number of PairsMinimum MemoryRecommended MemoryExperience
1-20512MB1GBSilk smooth
20-501GB2GBSmooth
50+2GB4GBEnough

Roast:

"This strategy saves hardware, saves electricity, saves brain cells. Raspberry Pi can run it."

10.4 Backtest vs Live Trading​

Backtest Performance:

  • Years with clear trends, backtest data looks good
  • Ranging years, gets repeatedly stoplossed

Live Trading Differences:

  • Slippage may eat part of profits
  • False breakouts more than backtest
  • Suggest test with small capital first

Suggested Process:

  1. Backtest recent 1 year data
  2. Paper trading test for 1 month
  3. Small capital live test
  4. Gradually increase position

Don't go all-in immediately, even simplest strategies need breaking in!

11. Easter Egg: The Strategy Author's "Little Thoughts"​

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

  1. Bollinger Bands are decoration

    # Calculated Bollinger Bands
    bollinger = qtpylib.bollinger_bands(...)
    # But completely not used in trading signals

    "I calculated Bollinger Bands, but I don't want to use them, what you gonna do?"

  2. close10 variable unused

    dataframe["close10"] = dataframe["close"].shift(periods=-10)
    # This line exists, but never referenced

    "I defined variable, but I just won't use it, play."

  3. Simplicity extreme

    Code so simple can serve as Freqtrade teaching case, author may be intentionally keeping it simple.

Guess: This may be Freqtrade official teaching example, not live trading strategy.

12. Final Final Thoughts​

One-Sentence Review​

"Quant world's 'Hello World' — first strategy you write, not strategy you make money with."

Who Should Use It?​

  • ✅ Beginners just entering quant trading
  • ✅ People wanting to learn Freqtrade platform
  • ✅ People wanting to understand EMA crossover principles
  • ✅ Adventurers who don't mind practicing with small money

Who Should NOT Use It?​

  • ❌ Investors wanting stable profits
  • ❌ People focused on ranging markets
  • ❌ Institutions needing complex risk control
  • ❌ Veterans who already know how to write strategies

Manual Trader Suggestions​

If you're manual trading, can borrow this approach:

  • Use EMA10 and EMA50 to judge trend
  • Golden cross go long, death cross observe
  • But add your own filtering conditions, like RSI, support/resistance levels
  • Take-profit don't wait for 20%, 5-10% more realistic

13. ⚠️ Risk Reminder (Must Read This Section)​

Backtest Looks Great, Live Trading Needs Caution​

bbema in historical backtests, may perform well during periods with clear trends — but there's a trap:

Because logic too simple, it has no ability to filter false signals.

Simply put:

"Drinks soup when trend comes, gets repeatedly beaten when ranging comes."

Hidden Risks of This Strategy​

In live trading, simple logic may cause:

  1. Frequent False Breakouts

    • EMA golden cross may be false breakout
    • Immediately death cross stoploss after buying
    • Fees make you doubt life

  2. Ranging Market Harvester

    • Price repeatedly crosses between MAs
    • Buy→stoploss→buy→stoploss
    • Strategy becomes exchange's fee worker

  3. 20% Take-Profit is Decoration

    • 1-hour level rising 20% needs big market
    • Most times can't wait for take-profit
    • Finally exits via stoploss or death cross

My Suggestions (Real Talk)​

1. Use as textbook, learn strategy structure
2. Add protection mechanisms on this foundation:
   - RSI filtering overbought/oversold
   - Volume confirming trend
   - Bollinger Band boundary filtering (this time really use it)
3. Adjust take-profit to 5-10%
4. Paper trade test at least 1 month
5. Small capital live verification

Remember:

"Simple strategy doesn't equal stable strategy. Market will educate everyone running naked."

Final Reminder: No matter how simple the strategy, the market won't say hello when teaching you lessons. Light position test, staying alive is most important! 🙏