The "Crypto Strategy Using MA and EMA" is a trading strategy that uses two types of moving averages (MA and EMA) to generate buy and sell signals in the cryptocurrency market. Here's a breakdown of the important parts of the strategy:
Strategy Type: This strategy is implemented as a class named "EMAMA" that inherits from the "IStrategy" interface provided by the Freqtrade bot. ROI and Stoploss: The strategy sets a minimal return on investment (ROI) target and a stoploss value.
The minimal ROI is defined as a dictionary with different percentage targets for different time periods.
The stoploss value is set to -0.99, indicating a high-risk approach.
Ticker Interval: The strategy is optimized for a ticker interval of 15 minutes, meaning it analyzes price data in 15-minute intervals. Indicators: The strategy uses two indicators, EMA (Exponential Moving Average) and MA (Moving Average), to generate trading signals. It calculates a 50-period EMA and a 4-period MA based on the price data. Buy Trend: The "populate_buy_trend" method defines the conditions for generating a buy signal. It checks if the RSI (Relative Strength Index) is below 35, the fastd indicator is below 35, the ADX (Average Directional Index) is above 30, and the plus_di indicator is above 0.5. Additionally, if the ADX is above 65 and the plus_di is above 0.5, a buy signal is also generated. Sell Trend: The "populate_sell_trend" method defines the conditions for generating a sell signal. It checks if either the RSI or the fastd indicator crosses above 70, the ADX is above 10, and the minus_di indicator is above 0. If the ADX is above 70 and the minus_di is above 0.5, a sell signal is also generated. Overall, this strategy aims to identify potential buying opportunities when certain conditions are met based on the MA and EMA indicators, and it looks to sell when certain conditions suggest a potential downturn in the market.
The minimal ROI is defined as a dictionary with different percentage targets for different time periods.
The stoploss value is set to -0.99, indicating a high-risk approach.
Ticker Interval: The strategy is optimized for a ticker interval of 15 minutes, meaning it analyzes price data in 15-minute intervals. Indicators: The strategy uses two indicators, EMA (Exponential Moving Average) and MA (Moving Average), to generate trading signals. It calculates a 50-period EMA and a 4-period MA based on the price data. Buy Trend: The "populate_buy_trend" method defines the conditions for generating a buy signal. It checks if the RSI (Relative Strength Index) is below 35, the fastd indicator is below 35, the ADX (Average Directional Index) is above 30, and the plus_di indicator is above 0.5. Additionally, if the ADX is above 65 and the plus_di is above 0.5, a buy signal is also generated. Sell Trend: The "populate_sell_trend" method defines the conditions for generating a sell signal. It checks if either the RSI or the fastd indicator crosses above 70, the ADX is above 10, and the minus_di indicator is above 0. If the ADX is above 70 and the minus_di is above 0.5, a sell signal is also generated. Overall, this strategy aims to identify potential buying opportunities when certain conditions are met based on the MA and EMA indicators, and it looks to sell when certain conditions suggest a potential downturn in the market.
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 152, in pandas._libs.index.IndexEngine.get_loc File "index.pyx", line 181, in pandas._libs.index.IndexEngine.get_loc File "pandas/_libs/hashtable_class_helper.pxi", line 7080, in pandas._libs.hashtable.PyObjectHashTable.get_item File "pandas/_libs/hashtable_class_helper.pxi", line 7088, in pandas._libs.hashtable.PyObjectHashTable.get_item KeyError: 'rsi' 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 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 1391, in ft_advise_signals dataframe = self.advise_entry(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1425, in advise_entry df = self.populate_entry_trend(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 225, in populate_entry_trend return self.populate_buy_trend(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/EMAMA.py", line 69, in populate_buy_trend (dataframe['rsi'] < 35) & ~~~~~~~~~^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/frame.py", line 3893, in __getitem__ indexer = self.columns.get_loc(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: 'rsi'
stoploss: -0.99 timeframe: 15m hash(sha256): da0c1b56c611cb155e2af998ba03b16e9b4f21a84c0506f03b4dd19ed540d8a1 indicators: adx ma4 minus_di rsi ema50 fastd plus_di
No similar strategies found. (based on used indicators)
last change: 2024-04-29 19:18:21