memecoin-freqtrade-bot

Virtual paper-trading bot for memecoins built on Freqtrade.

All trades are simulated with real exchange fees (0.1 % taker/maker) and order-book-based fill prices so the numbers reflect what live trading would actually cost and earn.

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What this does

• Runs entirely in dry-run / paper-trading mode (no real money ever moves).
• Applies 0.1 % fee per side (0.2 % round-trip) — the standard Binance spot fee.
• Uses order-book top-1 pricing to approximate realistic fill slippage.
• Targets the 20 most liquid memecoins on Binance (configurable in user_data/config/pairs.json).
• Exposes FreqUI at http://localhost:8080 for a live dashboard.

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Prerequisites

• Docker and Docker Compose (v2)
• make (optional but convenient; all commands can be run with docker compose directly)

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Quick start

1. Clone the repo

git clone https://github.com/YOUR_USERNAME/memecoin-freqtrade-bot.git
cd memecoin-freqtrade-bot

2. Configure credentials

cp .env.example .env
# Edit .env with any values you want to change.
# API keys are not required for paper trading.

Update user_data/config/config.json and set strong values for:

"jwt_secret_key": "your-random-secret",
"ws_token":       "your-random-token",
"username":       "freqtradeuser",
"password":       "your-password"

3. Download historical data (needed for backtesting)

make download-data TIMERANGE=20240101-20241231

This downloads 5 m OHLCV candles for all pairs from the pairs.json list.

4. Run a backtest

make backtest TIMERANGE=20240101-20241231

Freqtrade prints a full profit/loss table including:

• Total profit (USDT and %)
• Win/loss ratio
• Max drawdown
• Average trade duration
• Per-pair breakdown

Because enable_protections: true and realistic fees are set, the numbers represent what you would have earned or lost on a real account.

5. Start paper trading (live simulation)

make trade

The bot connects to Binance, fetches real-time prices, and places virtual orders. Open http://localhost:8080 to see the FreqUI dashboard.

make logs    # tail the log
make status  # show container status
make stop    # stop the bot

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Workflow for evaluating profitability

Download data  →  Backtest  →  Tune parameters  →  Paper trade live
   make            make           make hyperopt        make trade
download-data     backtest

1. Backtest over a historical period to get a rough signal.
2. Hyperopt to search for better parameter values.
3. Paper trade live for at least 2–4 weeks before drawing conclusions.
4. Compare paper-trading results to backtest to check for overfitting.

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Pair list

Edit user_data/config/pairs.json to add or remove coins. Current list includes: DOGE, SHIB, PEPE, FLOKI, BONK, WIF, MEME, NEIRO, POPCAT, TURBO, BRETT, MOG, DOGS, HMSTR, CATI, NOT, 1000SATS, BOME, MYRO, SLERF.

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Strategy overview (MemecoinStrategy)

Entry conditions (all must be true):

1. Volume ratio > N × 24-candle rolling average (configurable, default 2×)
2. RSI between 35 and 60 (momentum zone, not overbought)
3. Price > EMA-9 and EMA-9 > EMA-21 (short-term uptrend)
4. EMA-21 ≥ EMA-50 (medium-term trend)
5. MACD histogram positive and rising
6. Price < 98 % of upper Bollinger Band
7. Stochastic RSI below 85

Exit conditions (any one triggers exit):

1. RSI > 75 (overbought)
2. Price crosses below EMA-9
3. MACD histogram flips negative

ROI targets:

Time	Target
Any time	6 %
30 min	4 %
1 h	2.5 %
2 h	1.5 %
4 h	1 %

Stop-loss: 8 % hard stop + trailing stop (activates at +4 %, trails 2 %)

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Hyperopt

Find better parameter values automatically:

make hyperopt TIMERANGE=20240601-20241231 EPOCHS=300

After hyperopt completes, the best parameters are saved to user_data/hyperopt_results/. Update MemecoinStrategy.py with the printed values to apply them.

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Cost model

Cost item	Value
Taker fee	0.1 % (standard Binance spot)
Maker fee	0.1 %
Round-trip cost	0.2 % (two taker fills)
Slippage model	Order-book top-1 (use_order_book)
Spread	Included via order-book pricing

To model BNB fee discount (0.075 %), change taker/maker to 0.00075 in config.json.

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Switching to live trading

Only do this after extensive paper-trading validation.

1. Set real API keys in .env and update config.json accordingly.
2. Change "dry_run": false in config.json.
3. Remove "dry_run_wallet" or set it to your actual balance.
4. Restart with make stop && make trade.

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Project structure

memecoin-freqtrade-bot/
  user_data/
    config/
      config.json           Main bot configuration (fees, API server, etc.)
      config.backtest.json  Overrides for backtesting and hyperopt
      pairs.json            Memecoin pair whitelist
    strategies/
      MemecoinStrategy.py   Trading strategy
    data/                   Downloaded OHLCV data (gitignored)
    logs/                   Bot logs (gitignored)
    backtest_results/       Backtest JSON exports
  docker-compose.yml              Live paper-trading
  docker-compose.backtesting.yml  Backtesting
  docker-compose.hyperopt.yml     Hyperopt
  Makefile                        Convenience commands
  .env.example                    Environment variable template

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Disclaimer

This project is for educational and simulation purposes only. Past backtest results do not guarantee future performance. Memecoins are extremely high-risk assets.