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The NotAnotherSMAOffsetStrategyHOv3 strategy is a trading strategy that uses various technical indicators to make buy and sell decisions in the financial market. Here is a breakdown of what the strategy does:
In the populate_indicators method:
Calculates Exponential Moving Averages (EMA) for different time periods and adds them to the dataframe. Calculates the Hull Moving Average (HMA) with a window of 50 and adds it to the dataframe.
Calculates the EMA with a time period of 100 and adds it to the dataframe.
Calculates the Simple Moving Average (SMA) with a time period of 9 and adds it to the dataframe.
Calculates the Elder's Force Index (EWO) using the provided parameters and adds it to the dataframe. Calculates the Relative Strength Index (RSI) with time periods of 14, 4, and 20 and adds them to the dataframe. Returns the updated dataframe. In the populate_buy_trend method: Checks for specific conditions to determine buy signals based on the indicators and parameters. If the conditions are met, it marks the corresponding rows in the dataframe as a buy signal and assigns a buy tag. Returns the updated dataframe. In the populate_sell_trend method: Defines conditions for sell signals based on the indicators and parameters. If the conditions are met, it marks the corresponding rows in the dataframe as a sell signal. Returns the updated dataframe. Overall, the strategy uses indicators such as moving averages, EWO, RSI, and volume to identify potential buying and selling opportunities in the market.
Calculates the EMA with a time period of 100 and adds it to the dataframe.
Calculates the Simple Moving Average (SMA) with a time period of 9 and adds it to the dataframe.
Calculates the Elder's Force Index (EWO) using the provided parameters and adds it to the dataframe. Calculates the Relative Strength Index (RSI) with time periods of 14, 4, and 20 and adds them to the dataframe. Returns the updated dataframe. In the populate_buy_trend method: Checks for specific conditions to determine buy signals based on the indicators and parameters. If the conditions are met, it marks the corresponding rows in the dataframe as a buy signal and assigns a buy tag. Returns the updated dataframe. In the populate_sell_trend method: Defines conditions for sell signals based on the indicators and parameters. If the conditions are met, it marks the corresponding rows in the dataframe as a sell signal. Returns the updated dataframe. Overall, the strategy uses indicators such as moving averages, EWO, RSI, and volume to identify potential buying and selling opportunities in the market.
startup_candle_count : 200 hma_50: 0.001% ema_100: -0.026% rsi_slow: 0.002%
Unable to parse Traceback (Logfile Exceeded Limit)
stoploss: -0.3 timeframe: 5m hash(sha256): abaae38baa01c91f8f1bbdf5c9f5dd8e3cab1a302a519cb3af044d6055c3c7ed indicators: rsi_buy EWO ewo_high ewo_low high_offset_2 close ewo_high_2 sell_signal rsi_fast ma_sell_val ma_buy_val volume low_offset retries high_offset low_offset_2 base_nb_candles_buy ___retries base_nb_candles_sell hma_50 buy buy_tag sma_9 ema_100 max_slippage rsi_slow rsi low
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last change: 2024-09-30 04:57:08