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The NostalgiaForInfinityV7_SMA strategy is a backtesting strategy that involves using various indicators to determine buying conditions in a trading system. Here's a breakdown of its main components:
populate_indicators: This function is responsible for calculating and merging different indicators for the strategy. It takes a DataFrame and metadata as input and returns the updated DataFrame.
populate_buy_trend: This function determines the buying conditions based on a set of criteria.
It creates a list of conditions that need to be satisfied for a buy signal to be generated.
Some of the important conditions include: RSI (Relative Strength Index) conditions: The RSI values need to be within certain ranges. Trend conditions: The strategy checks for an uptrend in the 1-hour timeframe. Moving averages: The strategy checks if the close price is below the lower moving average. Volume: The volume needs to be greater than zero. Various protection conditions: The strategy includes several additional conditions based on indicators like EMA (Exponential Moving Average), SMA (Simple Moving Average), safe dips, safe pumps, etc. The logic for the buy conditions is implemented using a combination of logical operations like AND (&) and OR (|). After evaluating the conditions, the function updates the DataFrame with a new column called 'buy_01_trigger', which indicates whether the buy conditions are met. The function also includes additional sets of conditions for buy signals (buy_02_trigger, buy_03_trigger) that can be enabled or disabled based on configuration settings. Overall, the strategy uses a combination of different indicators and conditions to generate buy signals in a trading system.
populate_buy_trend: This function determines the buying conditions based on a set of criteria.
It creates a list of conditions that need to be satisfied for a buy signal to be generated.
Some of the important conditions include: RSI (Relative Strength Index) conditions: The RSI values need to be within certain ranges. Trend conditions: The strategy checks for an uptrend in the 1-hour timeframe. Moving averages: The strategy checks if the close price is below the lower moving average. Volume: The volume needs to be greater than zero. Various protection conditions: The strategy includes several additional conditions based on indicators like EMA (Exponential Moving Average), SMA (Simple Moving Average), safe dips, safe pumps, etc. The logic for the buy conditions is implemented using a combination of logical operations like AND (&) and OR (|). After evaluating the conditions, the function updates the DataFrame with a new column called 'buy_01_trigger', which indicates whether the buy conditions are met. The function also includes additional sets of conditions for buy signals (buy_02_trigger, buy_03_trigger) that can be enabled or disabled based on configuration settings. Overall, the strategy uses a combination of different indicators and conditions to generate buy signals in a trading system.
startup_candle_count : 400 ema_100_1h: 0.001% ema_200_1h: 0.078% ewo: 0.086%
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stoploss: -0.99 timeframe: 5m hash(sha256): 23e102fa76614fd3cd444c7167cb17b2e60422fc035ca8de54c8824bb39bda07 indicators: sell_pump_36_3_1h sma_200_1h upper safe_pump_24_30 close ema_15 sell_pump_36_2 sma_5 sell_pump_24_1_1h buy_22_trigger ema_200_1h ewo rsi_fast buy_17_trigger safe_pump_24_100 volume sma_200_dec_20 buy_09_trigger safe_pump_24_120 rsi_slow_descending sell_pump_36_1_1h ema_20 safe_dips_70 safe_pump_48_30 uptrend_1h safe_pump_48_100_1h buy_21_trigger oc_pct_change_48 sell_pump_48_1_1h high tpct_change_2 safe_dips_30 sell_pump_48_3 safe_pump_48_10 safe_dips_80 rsi_1h ema_slow_1h bb20_2_mid ema_12 tpct
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last change: 2024-08-02 07:30:01