You will be redirected to the original Strategy in 15 seconds.
The given code appears to define a class named Infinity that implements a trading strategy. Here is a short description of what the strategy does:
The strategy performs the following steps:
Populates indicators:
Retrieves BTC (Bitcoin) price data for informative timeframes (5 minutes and 1 hour) and merges it with the current timeframe's data. Removes unnecessary columns from the merged data.
If an informative timeframe is specified: Calculates indicators for the informative timeframe.
Merges the indicators with the current timeframe's data and removes unnecessary columns.
If a resampling timeframe is specified: Resamples the data to the specified timeframe. Calculates indicators for the resampled data. Merges the indicators with the current timeframe's data and renames the columns accordingly. Removes unnecessary columns. Calculates indicators for the normal (5 minutes) timeframe. Populates buy trend: Initializes a list of conditions. Adds buy protection conditions based on the specified parameters. If the first buy condition is enabled: Defines a logic list for the first buy condition. Adds the buy protection conditions for the first condition. Adds additional conditions based on various indicators. Creates a combined condition for the first buy condition. Appends the combined condition to the list of conditions. Updates the 'buy_tag' column in the DataFrame based on the first buy condition. If the second buy condition is enabled: Defines a logic list for the second buy condition. Adds the buy protection conditions for the second condition. Adds additional conditions based on various indicators. Creates a combined condition for the second buy condition. Appends the combined condition to the list of conditions. Updates the 'buy_tag' column in the DataFrame based on the second buy condition. If the third buy condition is enabled: Adds a buy protection condition for the third condition. Defines a logic list for the third buy condition. Adds additional conditions based on various indicators. Creates a combined condition for the third buy condition. Appends the combined condition to the list of conditions. Updates the 'buy_tag' column in the DataFrame based on the third buy condition. If the fourth buy condition is enabled: Defines a logic list for the fourth buy condition. Adds additional conditions based on various indicators. Creates a combined condition for the fourth buy condition. Appends the combined condition to the list of conditions. Updates the 'buy_tag' column in the DataFrame based on the fourth buy condition. The given code seems to be a partial implementation, and the specific details of each indicator and buy condition are not provided.
If an informative timeframe is specified: Calculates indicators for the informative timeframe.
Merges the indicators with the current timeframe's data and removes unnecessary columns.
If a resampling timeframe is specified: Resamples the data to the specified timeframe. Calculates indicators for the resampled data. Merges the indicators with the current timeframe's data and renames the columns accordingly. Removes unnecessary columns. Calculates indicators for the normal (5 minutes) timeframe. Populates buy trend: Initializes a list of conditions. Adds buy protection conditions based on the specified parameters. If the first buy condition is enabled: Defines a logic list for the first buy condition. Adds the buy protection conditions for the first condition. Adds additional conditions based on various indicators. Creates a combined condition for the first buy condition. Appends the combined condition to the list of conditions. Updates the 'buy_tag' column in the DataFrame based on the first buy condition. If the second buy condition is enabled: Defines a logic list for the second buy condition. Adds the buy protection conditions for the second condition. Adds additional conditions based on various indicators. Creates a combined condition for the second buy condition. Appends the combined condition to the list of conditions. Updates the 'buy_tag' column in the DataFrame based on the second buy condition. If the third buy condition is enabled: Adds a buy protection condition for the third condition. Defines a logic list for the third buy condition. Adds additional conditions based on various indicators. Creates a combined condition for the third buy condition. Appends the combined condition to the list of conditions. Updates the 'buy_tag' column in the DataFrame based on the third buy condition. If the fourth buy condition is enabled: Defines a logic list for the fourth buy condition. Adds additional conditions based on various indicators. Creates a combined condition for the fourth buy condition. Appends the combined condition to the list of conditions. Updates the 'buy_tag' column in the DataFrame based on the fourth buy condition. The given code seems to be a partial implementation, and the specific details of each indicator and buy condition are not provided.
stoploss: -0.15 timeframe: 5m hash(sha256): 656285281848d60496947193ecd1b5450773b4744b1a8f2f73e56959b7bada6b indicators: sell_pump_36_3_1h sma_200_1h upper safe_pump_type safe_pump_24_30 close tsi_ema_fast ema_15 sell_pump_36_2 sma_5 buy_condition_4_enable sell_pump_24_1_1h safe_pump_period ema_25 ema_200_1h buy_condition_27_enable safe_dump_50 ewo sma200_rising_val buy_condition_6_enable buy_condition_16_enable r_480_1h safe_pump_24_100 volume rsi_4 sma_200_dec_20 safe_pump_24_120 safe_dips_70 sell_pump_36_1_1h ema_20 safe_pump_48_30 safe_pump_48_100_1h buy_condition_29_enable oc_pct_change_48 sell_pump_48_1_1h h
Similar Strategies: (based on used indicators)
Strategy: Infinity, Similarity Score: 97.3%
Strategy: Infinity_0, Similarity Score: 97.3%
Strategy: NFINextMultiOffsetAndHO2, Similarity Score: 97.3%
Strategy: Nostalgia, Similarity Score: 97.3%
Strategy: NostalgiaForInfinityV8_9_1, Similarity Score: 97.3%
Strategy: NFINextMultiOffsetAndHO, Similarity Score: 94.59%
Strategy: NostalgiaForInfinityNext2, Similarity Score: 94.59%
Strategy: NostalgiaForInfinityNext_960, Similarity Score: 94.59%
Strategy: nostaljiaforinfinitynext, Similarity Score: 94.59%
Strategy: NFI731_BUSD, Similarity Score: 91.89%
Strategy: NostalgiaForInfinityNext_ChangeToTower_V2, Similarity Score: 89.19%
Strategy: Nostalgia_2, Similarity Score: 83.78%
last change: 2022-07-11 15:44:23