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Strategy: Discord_stochrsi
Downloaded: 20220727
Stoploss: -0.05
The "stochrsi" strategy is a trading strategy that uses the Stochastic RSI indicator in combination with exponential moving averages (EMAs) to generate buy and sell signals. Here's a breakdown of what the strategy does: The strategy is designed to be used on 1-hour timeframe data. It calculates various indicators using the "pandas_ta" library, including Stochastic RSI, EMAs of different lengths, and Average True Range (ATR).

It sets a minimal return on investment (ROI) of 0.05 (5%).

It sets a stop loss level of -0.05 (-5%).

It does not use trailing stop loss. It does not process only new candles. It uses limit orders for buying and selling, and market orders for stop loss. The order time in force is set to "good till canceled" (gtc) for both buy and sell orders. It plots various indicators on the chart, including TEMA, SAR, MACD, and RSI. It does not provide informative pairs. It populates indicators by calculating Stochastic RSI, EMAs, and ATR for the given dataframe. It calculates a custom stop loss based on the ATR value. It populates trade information and adjusts min/max rates for active trades. It generates buy signals based on the conditions: EMA 15 is greater than EMA 50. EMA 8 is greater than EMA 15. Close price is greater than EMA 8. Stochastic RSI crosses above its signal line. It determines if the minimum ROI has been reached based on the current profit and trade duration. It generates sell signals based on the condition: EMA 15 is less than EMA 50 or EMA 8 is less than EMA 15. Overall, the strategy aims to capture trends by buying when the shorter EMAs are above the longer EMAs and selling when the shorter EMAs cross below the longer EMAs. The Stochastic RSI is used to confirm the buy signals, and the ATR is used for setting the stop loss level.

Traceback (most recent call last): File "index.pyx", line 598, in pandas._libs.index.DatetimeEngine.get_loc File "pandas/_libs/hashtable_class_helper.pxi", line 2606, in pandas._libs.hashtable.Int64HashTable.get_item File "pandas/_libs/hashtable_class_helper.pxi", line 2630, in pandas._libs.hashtable.Int64HashTable.get_item KeyError: 1709254860000000000 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexes/base.py", line 3791, in get_loc return self._engine.get_loc(casted_key) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "index.pyx", line 566, in pandas._libs.index.DatetimeEngine.get_loc File "index.pyx", line 600, in pandas._libs.index.DatetimeEngine.get_loc KeyError: Timestamp('2024-03-01 01:01:00+0000', tz='UTC') The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexes/datetimes.py", line 631, in get_loc return Index.get_loc(self, key) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexes/base.py", line 3798, in get_loc raise KeyError(key) from err KeyError: Timestamp('2024-03-01 01:01:00+0000', tz='UTC') The above exception was the direct cause of the following exception: 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_stochrsi.py", line 132, in min_roi_reached _, roi = self.min_roi_reached_dynamic(trade, current_profit, current_time, trade_dur) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/Discord_stochrsi.py", line 148, in min_roi_reached_dynamic ATR = self.custom_trade_info[trade.pair]['ATR'].loc[current_time]['ATR'] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexing.py", line 1153, in __getitem__ return self._getitem_axis(maybe_callable, axis=axis) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexing.py", line 1393, in _getitem_axis return self._get_label(key, axis=axis) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexing.py", line 1343, in _get_label return self.obj.xs(label, axis=axis) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/generic.py", line 4236, in xs loc = index.get_loc(key) ^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexes/datetimes.py", line 633, in get_loc raise KeyError(orig_key) from err KeyError: datetime.datetime(2024, 3, 1, 1, 1, tzinfo=datetime.timezone.utc)
stoploss: -0.05
timeframe: 1h
hash(sha256): 3e3651eea12ab87c3ba9cd1d529dd50c0ee4e4447e008dd62f61006a4ba8be16
indicators:
high EMA_8 date ATR EMA_15
EMA_50 STOCHRSIk_14_14_3_3 ATR close date
STOCHRSId_14_14_3_3 runmode low

No similar strategies found. (based on used indicators)

last change: 2024-04-28 23:33:37