Not Enough Data to display!
Average Overall
| Not Enough Data! / Avg statistics not populated yet. |
|---|
The stochrsi3 strategy is a trading strategy implemented in Python for backtesting purposes. Here is a short description of what the strategy does:
The strategy uses the Stochastic RSI (Relative Strength Index) indicator along with exponential moving averages (EMA) and the Average True Range (ATR) indicator. It operates on the 1-hour timeframe and uses the same timeframe for informative data.
The strategy calculates various indicators such as EMA, ATR, and Stochastic RSI for both the main and informative dataframes.
It defines a minimal return on investment (ROI) of 1, meaning that it aims to achieve at least a 1% return on each trade.
It sets a stop loss at -30%, meaning that if a trade's profit reaches -30%, it will be stopped out. The strategy does not use trailing stop loss. It uses limit orders for both buying and selling. The strategy plots the EMA indicators (EMA_8, EMA_50, EMA_15) on the main plot and the ATR indicator on a subplot. It defines a custom stop loss based on the ATR indicator. For the buy signal, the strategy looks for conditions where EMA_15 is greater than EMA_50, EMA_8 is greater than EMA_15, the closing price is greater than EMA_8, and there is a cross above signal in the Stochastic RSI indicator. For the sell signal, the strategy looks for conditions where EMA_15 is less than EMA_50 or EMA_8 is less than EMA_15. The strategy checks if the current profit of a trade has reached a minimum ROI, taking into account the trade duration and the ROI value from a custom trade info dataframe. That's a brief overview of what the stochrsi3 strategy does. It uses technical indicators to generate buy and sell signals and implements risk management through stop loss and minimum ROI conditions.
The strategy calculates various indicators such as EMA, ATR, and Stochastic RSI for both the main and informative dataframes.
It defines a minimal return on investment (ROI) of 1, meaning that it aims to achieve at least a 1% return on each trade.
It sets a stop loss at -30%, meaning that if a trade's profit reaches -30%, it will be stopped out. The strategy does not use trailing stop loss. It uses limit orders for both buying and selling. The strategy plots the EMA indicators (EMA_8, EMA_50, EMA_15) on the main plot and the ATR indicator on a subplot. It defines a custom stop loss based on the ATR indicator. For the buy signal, the strategy looks for conditions where EMA_15 is greater than EMA_50, EMA_8 is greater than EMA_15, the closing price is greater than EMA_8, and there is a cross above signal in the Stochastic RSI indicator. For the sell signal, the strategy looks for conditions where EMA_15 is less than EMA_50 or EMA_8 is less than EMA_15. The strategy checks if the current profit of a trade has reached a minimum ROI, taking into account the trade duration and the ROI value from a custom trade info dataframe. That's a brief overview of what the stochrsi3 strategy does. It uses technical indicators to generate buy and sell signals and implements risk management through stop loss and minimum ROI conditions.
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 1335, in backtest_one_strategy results = self.backtest( ^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 1270, in backtest open_trade_count_start = self.backtest_loop( ^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 1175, in backtest_loop self._check_trade_exit(trade, row, current_time) # Place exit order if necessary ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 736, in _check_trade_exit exits = self.strategy.should_exit( ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1153, in should_exit and self.min_roi_reached(trade=trade, current_profit=current_profit_best, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/Discord_stochrsi3.py", line 129, in min_roi_reached _, roi = self.min_roi_reached_dynamic(trade, current_profit, current_time, trade_dur) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/Discord_stochrsi3.py", line 144, in min_roi_reached_dynamic open_date_mask = custom_info_pair.index.unique().get_loc(open_date, method='ffill') ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: DatetimeIndex.get_loc() got an unexpected keyword argument 'method'
stoploss: -0.3 timeframe: 1h hash(sha256): ce58159fc5252cff939f2f32bc1fe0c9f1540ed86d3c62d1ea13e6038dd6bad6 indicators: EMA_8 EMA_15 EMA_50 roi ATR close date stop roi STOCHRSIk_14_14_3_3 date STOCHRSId_14_14_3_3 stop date open high low close volume
No similar strategies found. (based on used indicators)
last change: 2024-04-28 23:07:09