The CryptoFrog strategy is designed for backtesting trading strategies in the cryptocurrency market. Here is a brief description of what the strategy does:
populate_indicators: This function populates indicators for the given dataframe and metadata. It retrieves the necessary data, performs calculations for indicators, and prepares the data for further analysis.
populate_buy_trend: This function determines the conditions for entering a buy trade.
It checks various indicators and criteria such as the close price being lower than a certain value, the moving average convergence divergence (MACD) values, Bollinger Bands, and other factors.
If the conditions are met, it marks the trade as a buy. populate_sell_trend: This function determines the conditions for exiting a buy trade and potentially initiating a sell trade. It checks indicators such as the close price being higher than a certain value, MACD values, Bollinger Bands, and others. If the conditions are met, it marks the trade as a sell and assigns an exit tag. Custom Stoploss: This section calculates the trade duration and checks the current profit to determine if a stop loss should be triggered. The decision is based on user-configurable parameters such as the rate of change (ROC) and trade duration. If the conditions are met, the function returns a value indicating the stop loss. Freqtrade ROI Overload: This section calculates the minimal return on investment (ROI) and table ROI based on the trade duration. It also considers additional factors such as the trend of indicators like Relative Momentum Index (RMI), candlestick patterns, and the direction of the SSL (Squeeze Momentum Indicator). The minimum ROI and maximum profit values are adjusted accordingly. Overall, the CryptoFrog strategy uses a combination of technical indicators and user-defined parameters to determine the conditions for entering and exiting trades, as well as implementing stop loss and calculating ROI.
populate_buy_trend: This function determines the conditions for entering a buy trade.
It checks various indicators and criteria such as the close price being lower than a certain value, the moving average convergence divergence (MACD) values, Bollinger Bands, and other factors.
If the conditions are met, it marks the trade as a buy. populate_sell_trend: This function determines the conditions for exiting a buy trade and potentially initiating a sell trade. It checks indicators such as the close price being higher than a certain value, MACD values, Bollinger Bands, and others. If the conditions are met, it marks the trade as a sell and assigns an exit tag. Custom Stoploss: This section calculates the trade duration and checks the current profit to determine if a stop loss should be triggered. The decision is based on user-configurable parameters such as the rate of change (ROC) and trade duration. If the conditions are met, the function returns a value indicating the stop loss. Freqtrade ROI Overload: This section calculates the minimal return on investment (ROI) and table ROI based on the trade duration. It also considers additional factors such as the trend of indicators like Relative Momentum Index (RMI), candlestick patterns, and the direction of the SSL (Squeeze Momentum Indicator). The minimum ROI and maximum profit values are adjusted accordingly. Overall, the CryptoFrog strategy uses a combination of technical indicators and user-defined parameters to determine the conditions for entering and exiting trades, as well as implementing stop loss and calculating ROI.
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: 1717250460000000000 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('2024-06-01 14:01:00+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('2024-06-01 14:01:00+0000', tz='UTC') The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/freqtrade/freqtrade/strategy/strategy_wrapper.py", line 27, in wrapper return f(*args, **kwargs) ^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/Discord_2_CryptoFrog.py", line 392, in custom_stoploss sroc = self.custom_trade_info[trade.pair]['sroc'].loc[current_time]['sroc'] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^ 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, 6, 1, 14, 1, tzinfo=datetime.timezone.utc)
stoploss: -0.085 timeframe: 5m hash(sha256): 346a7651541579e43711604d1aa6f7552197402d8fdec389fcfeefc93767fa0a indicators: upper close HA_Close bb_lowerband date candleuptrend HA_High volume smaHigh sslDown DI high sslUp emac date sroc atr adx hhlow roc time any runmode HA_Open HA_Close low open close low Smooth_HA_C active_trade sell exit_tag emao_1h sqzmi maxdown Smooth_HA_L srsi_k rmiuptrend date roc candleuptrend hlv lower roc rsi emac_1h HA_Low date open high low close volume emac emao srsi_d hhopen mfi date ssldir candleup price_side ATR dmi_minus maxup emao sar smaLow ssldir mid bb_width Smooth_HA_H hhclose h
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last change: 2024-07-27 00:23:45