The Scalp strategy is designed to generate numerous potential buy signals and make small profits on each trade. It is recommended to have a minimum of 60 parallel trades at any given time to cover unavoidable losses. The strategy focuses on selling based on Return on Investment (ROI).
Key features of the strategy include: Minimal ROI: The strategy aims for a minimum ROI of 0.01 (1%).
Stoploss: The optimal stoploss is set at -0.04 (4% loss).
Ticker interval: The strategy operates on 1-minute intervals. The strategy uses various technical indicators to make buying and selling decisions. The indicators used are: Exponential Moving Averages (EMA): Calculates EMAs for high, close, and low prices with a time period of 5. Stochastic Fast: Calculates the fast %K and %D values for the Stochastic indicator with parameters (5.0, 3.0, 0.0, 3.0, 0.0). Average Directional Index (ADX): Calculates the ADX value. Additionally, the strategy includes Bollinger Bands for graphing purposes. The Bollinger Bands are calculated with a window of 20 and 2 standard deviations. The populate_buy_trend function identifies potential buying opportunities based on the following conditions: The opening price is below the EMA low. The ADX value is above 30. The fast %K and %D values are both below 30 and have crossed above each other. The populate_sell_trend function identifies potential selling opportunities based on the following conditions: The opening price is above or equal to the EMA high. Either the fast %K or %D value has crossed above 70. Overall, the Scalp strategy aims to generate frequent buy signals and take small profits on each trade while using specific indicators and conditions for buying and selling decisions.
Key features of the strategy include: Minimal ROI: The strategy aims for a minimum ROI of 0.01 (1%).
Stoploss: The optimal stoploss is set at -0.04 (4% loss).
Ticker interval: The strategy operates on 1-minute intervals. The strategy uses various technical indicators to make buying and selling decisions. The indicators used are: Exponential Moving Averages (EMA): Calculates EMAs for high, close, and low prices with a time period of 5. Stochastic Fast: Calculates the fast %K and %D values for the Stochastic indicator with parameters (5.0, 3.0, 0.0, 3.0, 0.0). Average Directional Index (ADX): Calculates the ADX value. Additionally, the strategy includes Bollinger Bands for graphing purposes. The Bollinger Bands are calculated with a window of 20 and 2 standard deviations. The populate_buy_trend function identifies potential buying opportunities based on the following conditions: The opening price is below the EMA low. The ADX value is above 30. The fast %K and %D values are both below 30 and have crossed above each other. The populate_sell_trend function identifies potential selling opportunities based on the following conditions: The opening price is above or equal to the EMA high. Either the fast %K or %D value has crossed above 70. Overall, the Scalp strategy aims to generate frequent buy signals and take small profits on each trade while using specific indicators and conditions for buying and selling decisions.
Traceback (most recent call last): File "/freqtrade/freqtrade/main.py", line 42, in main return_code = args['func'](args) ^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/commands/optimize_commands.py", line 58, in start_backtesting backtesting.start() File "/freqtrade/freqtrade/optimize/backtesting.py", line 1401, in start min_date, max_date = self.backtest_one_strategy(strat, data, timerange) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 1318, in backtest_one_strategy preprocessed = self.strategy.advise_all_indicators(data) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, in advise_all_indicators return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, inreturn {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1410, in advise_indicators return self.populate_indicators(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/Scalp.py", line 43, in populate_indicators stoch_fast = ta.STOCHF(dataframe, 5.0, 3.0, 0.0, 3.0, 0.0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "talib/_abstract.pxi", line 444, in talib._ta_lib.Function.__call__ File "talib/_abstract.pxi", line 310, in talib._ta_lib.Function.set_function_args File "talib/_abstract.pxi", line 513, in talib._ta_lib.Function.__check_opt_input_value TypeError: Invalid parameter value for fastk_period (expected int, got float)
stoploss: -0.04 timeframe: 1m hash(sha256): ece7af8ccb99bb791d111da374769eba9518d2b70749d85a17c16ecb2e94ae63 indicators: upper ema_close adx lower mid ema_high close bb_middleband bb_upperband bb_lowerband open ema_low fastd fastk
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last change: 2024-04-28 15:32:21