分享一个交易策略：当价格在过去 24 小时内下跌超过 20% 时，生成买入信号，并在盈利达到 10% 时自动卖出。简单回测 SHIB 在 20220101-20250201 的结果如下：
┏━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ ┃ ┃ ┃ Tot Profit ┃ ┃ ┃ Win Draw ┃ ┃
┃ Strategy ┃ Trades ┃ Avg Profit % ┃ USDT ┃ Tot Profit % ┃ Avg Duration ┃ Loss Win% ┃ Drawdown ┃
┡━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ DipBuyerStra… │ 20 │ 9.99 │ 56064.350 │ 560.64 │ 5 days, │ 20 0 │ 0 USDT 0.00% │
│ │ │ │ │ │ 21:28:00 │ 0 100 │ │
└───────────────┴────────┴──────────────┴───────────────┴──────────────┴───────────────┴───────────────┴───────────────┘这个策略的重点是币圈的超跌+快速回弹，所以要求盘子适当大，没有支撑的纯山寨 meme 不合适，其它币种可以适当调节超跌、止盈比例。
核心策略代码：
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.strategy import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import numpy as np
class DipBuyerStrategy(IStrategy):
INTERFACE_VERSION = 3
minimal_roi = {
"0": 0.1 # 10% 盈利目标
}
stoploss = -0.999 # 不需要止损
trailing_stop = False
timeframe = '1m'
process_only_new_candles = True
startup_candle_count = 1440 # Need 24 hours of data
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
// 计算依赖的指标，24 小时变动幅度
dataframe['price_24h_ago'] = dataframe['close'].shift(1440)
dataframe['price_change_24h'] = (dataframe['close'] - dataframe['price_24h_ago']) / dataframe['price_24h_ago']
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
// 下跌 20% 生成买入信号
dataframe.loc[
(
(dataframe['price_change_24h'] < -0.2) &
(dataframe['volume'] > 0)
),
'enter_long'] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
// 卖出信号依赖 ROI，此处不生成
dataframe['exit_long'] = 0
return dataframe
def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float:
available_balance = self.wallets.get_available_stake_amount()
stake_amount = available_balance
stake_amount = min(max(stake_amount, min_stake), max_stake)
return stake_amount