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The Saturn5 trading strategy is a backtesting strategy that uses various indicators to generate buy and sell signals for trading. Here is a summary of what the strategy does:
Indicator Population: The strategy starts by populating several indicators on the given dataframe. These indicators include Exponential Moving Averages (EMAs) of different time periods, Bollinger Bands, Average True Range (ATR), and volume-weighted moving averages (VWMAs).
Buy Trend Generation: The strategy generates buy signals based on different conditions and signals.
Buy Signal 1: The strategy checks for multiple conditions, including the VWMA crossing below the signal line, the low price being below a specific EMA value, the close price being above the same EMA value, and the crossing of two EMAs.
If these conditions are met, the strategy sets the "buy" column to 1 and assigns the "buy_signal_1" tag to the "buy_tag" column. Buy Signal 2: The strategy checks for the crossing above condition between the lower band of the Fibonacci retracement and the lower band of the Bollinger Bands. Additionally, it verifies that the close price is below a specific EMA value and the volume is greater than zero. If these conditions are met, it sets the "buy" column to 1 and assigns the "buy_signal_2" tag to the "buy_tag" column. Buy Signal 3: The strategy checks if the low price is below the lower band of the Bollinger Bands and above a specific EMA value. It also verifies that the volume is greater than zero. If these conditions are met, it sets the "buy" column to 1 and assigns the "buy_signal_3" tag to the "buy_tag" column. Buy Signal Consolidation: If none of the three buy signals are active, the strategy sets the "buy" column to 0. Sell Trend Generation: The strategy sets the "sell" column to 0 for all rows, indicating that no sell signals are generated. Finally, the strategy returns the modified dataframe with the "buy" and "sell" columns indicating the generated signals. Note: The specific parameters and values used in the strategy are not included in the provided code snippet.
Buy Trend Generation: The strategy generates buy signals based on different conditions and signals.
Buy Signal 1: The strategy checks for multiple conditions, including the VWMA crossing below the signal line, the low price being below a specific EMA value, the close price being above the same EMA value, and the crossing of two EMAs.
If these conditions are met, the strategy sets the "buy" column to 1 and assigns the "buy_signal_1" tag to the "buy_tag" column. Buy Signal 2: The strategy checks for the crossing above condition between the lower band of the Fibonacci retracement and the lower band of the Bollinger Bands. Additionally, it verifies that the close price is below a specific EMA value and the volume is greater than zero. If these conditions are met, it sets the "buy" column to 1 and assigns the "buy_signal_2" tag to the "buy_tag" column. Buy Signal 3: The strategy checks if the low price is below the lower band of the Bollinger Bands and above a specific EMA value. It also verifies that the volume is greater than zero. If these conditions are met, it sets the "buy" column to 1 and assigns the "buy_signal_3" tag to the "buy_tag" column. Buy Signal Consolidation: If none of the three buy signals are active, the strategy sets the "buy" column to 0. Sell Trend Generation: The strategy sets the "sell" column to 0 for all rows, indicating that no sell signals are generated. Finally, the strategy returns the modified dataframe with the "buy" and "sell" columns indicating the generated signals. Note: The specific parameters and values used in the strategy are not included in the provided code snippet.
stoploss: -0.2 timeframe: 5m hash(sha256): bd45ce054cbb440f329657e703af238e23a1173c81c3590b54ff83039a12b94b indicators: s1_ema_xxl close s2_bb_lower_band s2_fib_lower_band s1_ema_md volume s3_bb_lowerband s1_ema_xl s2_bb_std_dev_value s2_ema slowMA s1_ema_xs s2_ema_xxl_off s2_ema_xxl s1_ema_sm hist vwmacd signal fastMA low
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last change: 2023-07-01 15:05:52