Wordcloud
Strategy: MultiMA_TSL_618
Downloaded: 20220115
Stoploss: -0.15
5mSpotv2UnbiasedLink


Not Enough Data to display!

Average Overall
Not Enough Data! / Avg statistics not populated yet.
The MultiMA_TSL strategy is a trading strategy that uses multiple moving averages and other indicators to determine buy and sell signals. Here is a breakdown of what the strategy does: In the populate_indicators method: Calculates the EWO (Elder's Force Index) using the fast and slow EWO values. Calculates the RSI (Relative Strength Index) with a time period of 14.

Calculates a rolling 12-period rate of change (ROC) and stores it as "roc_max" in the dataframe.

Returns the updated dataframe.

In the populate_buy_trend method: Calculates various offset values based on different moving averages (EMA, ZEMA, TRIMA) and their corresponding candle periods. Initializes some columns in the dataframe for buy tagging and tracking. Defines conditions for buying based on the offset values, EWO values, and RSI values. Appends the conditions to a list. If any conditions are present: Updates the "buy_copy" and "buy" columns of the dataframe for the selected buy conditions. Returns the updated dataframe. In the populate_sell_trend method: Initializes a column in the dataframe for sell tracking. Calculates offset values for selling based on EMA and TRIMA moving averages. Initializes a list for sell conditions. Adds conditions for selling based on the offset values and volume. If any conditions are present: Updates the "sell_copy" and "sell" columns of the dataframe for the selected sell conditions. If the strategy is not in backtest or hyperopt mode: Sets all values in the "sell" column to 0. Returns the updated dataframe. The last part of the code outside the class definition appears to be a separate function that calculates the difference between two exponential moving averages (EMA) and returns it as "smadif". Overall, the strategy calculates various indicators, sets buy and sell conditions based on moving average offsets, EWO values, and RSI values, and updates corresponding columns in the dataframe to indicate buy and sell signals.

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 1213, in backtest data: Dict = self._get_ohlcv_as_lists(processed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 381, in _get_ohlcv_as_lists df_analyzed = self.strategy.ft_advise_signals(pair_data, {'pair': pair}) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1392, in ft_advise_signals dataframe = self.advise_exit(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1443, in advise_exit df = self.populate_exit_trend(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 244, in populate_exit_trend return self.populate_sell_trend(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/MultiMA_TSL_618.py", line 247, in populate_sell_trend dataframe.loc[ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexing.py", line 881, in __setitem__ indexer = self._get_setitem_indexer(key) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexing.py", line 734, in _get_setitem_indexer self._ensure_listlike_indexer(key) File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexing.py", line 865, in _ensure_listlike_indexer self.obj._mgr = self.obj._mgr.reindex_axis(keys, axis=0, only_slice=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/internals/base.py", line 113, in reindex_axis new_index, indexer = self.axes[axis].reindex(new_index) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexes/base.py", line 4434, in reindex raise ValueError("cannot reindex on an axis with duplicate labels") ValueError: cannot reindex on an axis with duplicate labels
stoploss: -0.15
timeframe: 5m
hash(sha256): 0f11f2269d5577c05b4ca81b8fba1f2cdec44b0303b853cfad826ed517c9aefb
indicators:
volume sell_copy sell trima_offset_sell roc_max
close rsi buy_copy ema_offset_buy trima_offset_buy
runmode ema_offset_sell buy_copybuy ewo sell_copy
rsi_fast zema_offset_buy

No similar strategies found. (based on used indicators)

last change: 2024-09-12 15:07:28