✨ AI Search 🔒
💬 Forum

YoyoActionStrategy

♡

freqle/uploads/user-90abf0da8f3178f3/yoyo_action_strategy_v0.1_converted.py · first seen 2026-07-28

Basics mode: spot timeframe: 4h interface version: 3
Settings has minimal roi
Indicators ATR EMA RSI talib
Concepts mean_reversion
15 related strategies (⧉ identical code, ≈ similar name)

Each tile is a different kind of check — from an instant code lint to full sandboxed backtests and forward tests on recent data. Not sure what a check actually proves? See the FAQ →

Source

Download Raw 
  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
import numpy as np  # noqa
import pandas as pd  # noqa
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib

class YoyoActionStrategy(IStrategy):
    INTERFACE_VERSION = 3
    # Minimal ROI designed for the strategy.
    # This attribute will be overridden if the config file contains "minimal_roi".
    minimal_roi = {'0': 10}
    timeframe = '4h'
    # Optional order type mapping
    order_types = {'entry': 'limit', 'exit': 'limit', 'stoploss': 'limit', 'stoploss_on_exchange': False}
    # emaFast = 12
    # emaSlow = 26
    emaFast = 14
    emaSlow = 84
    rsiPeriod = 14
    overBought = 80
    overSold = 30
    #stoploss = -0.20
    # Fast Trail 
    atrFast = 6
    atrFM = 0.5  # fast ATR multiplier
    # Slow Trail 
    atrSlow = 18  # Slow ATR perod
    atrSM = 2  # Slow ATR multiplier
    # Trailing stoploss
    trailing_stop = False

    def informative_pairs(self):
        return []

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['ohlc4'] = (dataframe['open'] + dataframe['high'] + dataframe['low'] + dataframe['close']) / 4
        dataframe['ema_fast'] = ta.EMA(dataframe, timeperiod=self.emaFast)
        dataframe['ema_slow'] = ta.EMA(dataframe, timeperiod=self.emaSlow)
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=self.rsiPeriod)
        dataframe['macd'] = dataframe['ema_fast'] - dataframe['ema_slow']
        dataframe['bullish'] = dataframe['macd'] > 0
        dataframe['bearish'] = dataframe['macd'] < 0
        dataframe['sl1'] = self.atrFM * ta.ATR(dataframe.high, dataframe.low, dataframe.close, timeperiod=self.atrFast)  # Stop Loss
        dataframe['sl2'] = self.atrSM * ta.ATR(dataframe.high, dataframe.low, dataframe.close, timeperiod=self.atrSlow)
        dataframe.dropna(inplace=True)
        dataframe['atr_stop'] = 0
        dataframe['red'] = False
        dataframe['brown'] = False
        dataframe['yellow'] = False
        dataframe['aqua'] = False
        dataframe['blue'] = False
        dataframe['green'] = False
        dataframe['long'] = False
        dataframe['preBuy'] = False
        dataframe['short'] = False
        dataframe['preSell'] = False
        dataframe['trail2'] = 0.0
        dataframe['over_sole'] = False
        dataframe['over_bought'] = False
        dataframe['bullish_last'] = False
        for index in range(len(dataframe)):
            # length =  len(dataframe)
            # for index in range(length - 84 ,length):
            # Green = bullish and mainSource>fast
            dataframe.green.iloc[index] = dataframe.bullish.iloc[index] and dataframe.ohlc4.iloc[index] > dataframe.ema_fast.iloc[index]
            # Blue = bearish and mainSource>fast and mainSource>slow
            dataframe.blue.iloc[index] = dataframe.bearish.iloc[index] and dataframe.ohlc4.iloc[index] > dataframe.ema_fast.iloc[index]
            # Aqua = bearish and mainSource>fast and mainSource<slow
            dataframe.aqua.iloc[index] = dataframe.bearish.iloc[index] and dataframe.ohlc4.iloc[index] > dataframe.ema_fast.iloc[index] and (dataframe.ohlc4.iloc[index] < dataframe.ema_slow.iloc[index])
            # Yellow = bullish and mainSource<fast and mainSource>slow
            dataframe.yellow.iloc[index] = dataframe.bullish.iloc[index] and dataframe.ohlc4.iloc[index] < dataframe.ema_slow.iloc[index]
            # Brown = bullish and mainSource<fast and mainSource<slow
            dataframe.brown.iloc[index] = dataframe.bullish.iloc[index] and dataframe.ohlc4.iloc[index] < dataframe.ema_fast.iloc[index] and (dataframe.ohlc4.iloc[index] < dataframe.ema_slow.iloc[index])
            # Red = bearish and mainSource<fast
            dataframe.red.iloc[index] = dataframe.bearish.iloc[index] and dataframe.ohlc4.iloc[index] < dataframe.ema_fast.iloc[index]
            # iff(SC>nz(Trail2[1],0)                                    and SC[1]>nz(Trail2[1],0)
            if dataframe.close.iloc[index] > dataframe.trail2.iloc[index - 1] and dataframe.close.iloc[index - 1] > dataframe.trail2.iloc[index - 1]:
                dataframe.trail2.iloc[index] = max(dataframe.trail2.iloc[index - 1], dataframe.close.iloc[index] - dataframe.sl2.iloc[index])
            # iff(SC<nz(Trail2[1],0)                                        and SC[1]<nz(Trail2[1],0)
            elif dataframe.close.iloc[index] < dataframe.trail2.iloc[index - 1] and dataframe.close.iloc[index - 1] < dataframe.trail2.iloc[index - 1]:
                dataframe.trail2.iloc[index] = min(dataframe.trail2.iloc[index - 1], dataframe.close.iloc[index - 1] + dataframe.sl2.iloc[index - 1])
            # iff(SC>nz(Trail2[1],0),    
            elif dataframe.close.iloc[index] > dataframe.trail2.iloc[index - 1]:
                dataframe.trail2.iloc[index] = dataframe.close.iloc[index] - dataframe.sl2.iloc[index]
            else:
                dataframe.trail2.iloc[index] = dataframe.close.iloc[index] + dataframe.sl2.iloc[index]
            # it can use rolling
            dataframe.long.iloc[index] = dataframe.bullish.iloc[index] and dataframe.bullish.iloc[index - 1]
            dataframe.preBuy.iloc[index] = dataframe.bullish.iloc[index] and dataframe.bullish.iloc[index - 1]
            # dataframe.preSell.iloc[index] =  dataframe.yellow.iloc[index] and ta.
            dataframe.short.iloc[index] = dataframe.bearish.iloc[index] and dataframe.bearish.iloc[index - 1]
            # dataframe.over_sole.iloc[index] = dataframe.iloc[-self.rsiPeriod:].where(dataframe.rsi.iloc[index] < 30).any() == False
            dataframe.over_sole.iloc[index] = dataframe.iloc[index - self.rsiPeriod:index].where(dataframe['rsi'] <= self.overSold).any().rsi
            dataframe.over_bought.iloc[index] = dataframe.iloc[index - self.rsiPeriod:index].where(dataframe['rsi'] >= self.overBought).any().rsi
        # greenLine = SC>Trail2
        dataframe['greenLine'] = False
        dataframe.loc[dataframe['close'] > dataframe['trail2'], 'greenLine'] = True
        dataframe['greenLine_last'] = dataframe.greenLine.shift(1)
        dataframe['short_last'] = dataframe.short.shift(1)
        dataframe['bullish_last'] = dataframe.bullish.shift(1)
        dataframe['green_last'] = dataframe.green.shift(1)
        dataframe['red_last'] = dataframe.red.shift(1)
        dataframe['hold_state'] = False
        dataframe.dropna(inplace=True)
        dataframe
        # greenLine = SC>Trail2
        dataframe['greenLine'] = False
        dataframe.loc[dataframe['close'] > dataframe['trail2'], 'greenLine'] = True
        dataframe['greenLine_last'] = dataframe.greenLine.shift(1)
        dataframe['short_last'] = dataframe.short.shift(1)
        dataframe['green_last'] = dataframe.green.shift(1)
        dataframe['red_last'] = dataframe.red.shift(1)
        dataframe['hold_state'] = False
        dataframe.dropna(inplace=True)
        # ATR IN-OUT RSI
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        #     # | ((dataframe['greenLine'] == True) & (dataframe['blue'] == True)) # Over ATR and blue
        #     | ((dataframe['greenLine_last'] == False) & (dataframe['greenLine'] == True) & (dataframe['over_sole'] == True)) # Over ATR and RSI over sole 
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        #     | ((dataframe['greenLine_last'] == True) & (dataframe['greenLine'] == False) & (dataframe['over_bought'] == True)) # Stop lost ATR and RSI over bought            
        # ), 'signal_sell'] = True
        # ATR-BLUE
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        #     | ((dataframe['greenLine'] == True) & (dataframe['blue'] == True)) # Over ATR and blue
        #     #| ((dataframe['greenLine_last'] == False) & (dataframe['greenLine'] == True)) # Over ATR and RSI over sole 
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        #     # | ((dataframe['greenLine_last'] == True) & (dataframe['greenLine'] == False)& (dataframe['over_bought'] == True)) # Stop lost ATR and RSI over bought            
        # ), 'signal_sell'] = True
        # RSI-BLUE-AQUA
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        #     | ((dataframe['greenLine'] == True) & ((dataframe['blue'] == True) | (dataframe['aqua'] == True))) # Over ATR and blue AQUA
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        # ), 'signal_sell'] = True
        # RSI ATR-BLUE-AQUA
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        #     | ((dataframe['greenLine'] == True) & ((dataframe['blue'] == True) | (dataframe['aqua'] == True)) ) # Over ATR and blue AQUA
        #     | (((dataframe['blue'] == True) | (dataframe['aqua'] == True)) & (dataframe['over_sole'] == True)) # RSI and blue AQUA
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        # ), 'signal_sell'] = True
        # RSI over sole Out ATR over bought
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        #      | ((dataframe['over_sole'] == True) & (dataframe['blue'] == True) & dataframe['rsi'] < 50)
        #     #| ((dataframe['greenLine'] == True) & (dataframe['blue'] == True)) # Over ATR and blue
        #     #| ((dataframe['greenLine_last'] == False) & (dataframe['greenLine'] == True) & (dataframe['over_sole'] == True)) # Over ATR and RSI over sole 
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        #     | ((dataframe['greenLine_last'] == True) & (dataframe['greenLine'] == False) & (dataframe['over_bought'] == True)) # Stop lost ATR and RSI over bought            
        # ), 'signal_sell'] = True
        # RSI over sole Out red
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        #      | ((dataframe['over_sole'] == True) & (dataframe['blue'] == True) & dataframe['rsi'] < 50)
        #     #| ((dataframe['greenLine'] == True) & (dataframe['blue'] == True)) # Over ATR and blue
        #     #| ((dataframe['greenLine_last'] == False) & (dataframe['greenLine'] == True) & (dataframe['over_sole'] == True)) # Over ATR and RSI over sole 
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        #     #| ((dataframe['greenLine_last'] == True) & (dataframe['greenLine'] == False) & (dataframe['over_bought'] == True)) # Stop lost ATR and RSI over bought            
        # ), 'signal_sell'] = True
        # RSI over sole blue&aqua + ATR blue&aqua Out red
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        #      | ((dataframe['over_sole'] == True) & ((dataframe['blue'] == True) | (dataframe['aqua'] == True)) & dataframe['rsi'] < 50)
        #      | ((dataframe['greenLine'] == True)  & ((dataframe['blue'] == True) | (dataframe['aqua'] == True))) # Over ATR and blue
        #     #| ((dataframe['greenLine_last'] == False) & (dataframe['greenLine'] == True) & (dataframe['over_sole'] == True)) # Over ATR and RSI over sole 
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        #     #| ((dataframe['greenLine_last'] == True) & (dataframe['greenLine'] == False) & (dataframe['over_bought'] == True)) # Stop lost ATR and RSI over bought            
        # ),  'signal_sell'] = True
        # Green + RSI over sole blue&aqua out Red&ATR over bought 
        # dataframe.loc[(
        #     ((dataframe['green_last'] == True) & (dataframe['green'] == True)) # Green buy
        #      | ((dataframe['over_sole'] == True) & ((dataframe['blue'] == True) | (dataframe['aqua'] == True)) & dataframe['rsi'] < 50)
        #     #| ((dataframe['greenLine_last'] == False) & (dataframe['greenLine'] == True) & (dataframe['over_sole'] == True)) # Over ATR and RSI over sole 
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        #      | ((dataframe['greenLine_last'] == True) & (dataframe['greenLine'] == False) & (dataframe['over_bought'] == True)) # Stop lost ATR and RSI over bought            
        # ), 'signal_sell'] = True
        # Green + RSI over sole blue&aqua out Red&ATR 
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        #     # | ((dataframe['over_sole'] == True) & (dataframe['blue'] == True) & dataframe['rsi'] < 50)
        #      | ((dataframe['greenLine'] == True) & ((dataframe['aqua'] == True) | (dataframe['blue'] == True))) # Over ATR + blue and aqua
        #     #| ((dataframe['greenLine_last'] == False) & (dataframe['greenLine'] == True) & (dataframe['over_sole'] == True)) # Over ATR and RSI over sole 
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        #     | ((dataframe['greenLine_last'] == True) & (dataframe['greenLine'] == False)) # Stop lost ATR and RSI over bought            
        # ), 'signal_sell'] = True
        # MACD ATR STOP
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        # ), 'signal_buy'] = True
        # dataframe.loc[
        #         (
        #             (dataframe["signal_buy"] == True)
        #             & (dataframe['greenLine'] == True)
        #         ),
        #         'atr_stop'] =  dataframe['sl1']
        # dataframe.loc[
        #         (
        #             (dataframe["signal_buy"] == False)
        #         ),
        #         'atr_stop'] =  dataframe.atr_stop.shift(1)
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        #     | dataframe['atr_stop'] > dataframe['close']
        # ), 'signal_sell'] = True
        # dataframe.loc[
        #         (
        #             (dataframe["signal_sell"] == True)
        #         ),
        #         'atr_stop'] = 0
        # MACD + dobule bullish
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        #     | ((dataframe['greenLine'] == True) & (dataframe['blue'] == True)) 
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        # ), 'signal_sell'] = True
        # MACD + dobule bullish + blue ATR
        # Green buy
        #| ((dataframe['bullish_last'] == True) & (dataframe['bullish'] == True)) # Dobule bullish
        #| ((dataframe['greenLine'] == True) & (dataframe['blue'] == True))  # Blue ATR
        dataframe.loc[(dataframe['green_last'] == False) & (dataframe['green'] == True), 'signal_buy'] = True
        dataframe.loc[(dataframe['signal_buy'] == True) & (dataframe['greenLine'] == True), 'atr_stop'] = dataframe['trail2']
        dataframe.loc[dataframe['signal_buy'] == False, 'atr_stop'] = dataframe.atr_stop.shift(1)  # Red Sell
        dataframe.loc[(dataframe['red_last'] == False) & (dataframe['red'] == True) | (dataframe['atr_stop'] > dataframe['close']), 'signal_sell'] = True
        # MACD
        # dataframe.loc[(
        #     ((dataframe['green_last'] == False) & (dataframe['green'] == True)) # Green buy
        # ), 'signal_buy'] = True
        # dataframe.loc[(
        #     ((dataframe['red_last'] == False) & (dataframe['red'] == True)) # Red Sell
        # ), 'signal_sell'] = True
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[dataframe['signal_buy'] == True, 'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[dataframe['signal_sell'] == True, 'exit_long'] = 1
        return dataframe