You will be redirected to the original Strategy in 15 seconds.
The NostalgiaForInfinityX2 strategy is a trading strategy implemented as a class in Python. It inherits from the IStrategy class. Here is a brief description of what the strategy does:
populate_indicators method: This method populates the indicators used in the strategy.
It retrieves BTC (Bitcoin) informative indicators and merges them with the base timeframe indicators.
The informative indicators are obtained based on the stake currency (e.g., USDT, BUSD) or default to BTC/USDT.
The method merges these indicators with the base timeframe indicators by filling missing values. It drops unnecessary columns from the dataframe. populate_entry_trend method: This method populates the entry trend conditions for executing trades. It sets up a list of conditions based on different buy parameters. For each buy parameter, it checks specific conditions related to the index. These conditions involve various technical indicators and their relationships, such as moving averages (EMA, SMA), percentage changes, price levels, and trend direction. The method assigns an enter tag to the dataframe based on the satisfied conditions. Overall, the NostalgiaForInfinityX2 strategy combines informative indicators with the base timeframe indicators and defines entry trend conditions for initiating trades based on specific technical analysis criteria.
It retrieves BTC (Bitcoin) informative indicators and merges them with the base timeframe indicators.
The informative indicators are obtained based on the stake currency (e.g., USDT, BUSD) or default to BTC/USDT.
The method merges these indicators with the base timeframe indicators by filling missing values. It drops unnecessary columns from the dataframe. populate_entry_trend method: This method populates the entry trend conditions for executing trades. It sets up a list of conditions based on different buy parameters. For each buy parameter, it checks specific conditions related to the index. These conditions involve various technical indicators and their relationships, such as moving averages (EMA, SMA), percentage changes, price levels, and trend direction. The method assigns an enter tag to the dataframe based on the satisfied conditions. Overall, the NostalgiaForInfinityX2 strategy combines informative indicators with the base timeframe indicators and defines entry trend conditions for initiating trades based on specific technical analysis criteria.
stoploss: -0.99 timeframe: 5m hash(sha256): 6f05ba810fe376a334862ec8d8162ce2ed2678e05b99d3bd8508ca39eed6495f indicators: sma_200_1h upper not_downtrend_4h close res1 low_s not_downtrend_1h ema_200_1h pct_close_max_24 profit sma_12 volume xe1 r_480_4h sma_50 hl_pct_change_6 hl_pct_change_48_1h rsi_14 high ema_12_4h tpct_change_2 btc_is_bull_4h r_480 sma_12_4h cti_20 crossed_below_ema_12_26 xe6 openclosehighlow bb20_2_mid ha_high ema_12 tpct_change_12 T3Average force_entry 1 2 3 runmode ema_26 res_level close_max_48 pct_close_max_72 pivot USDTBUSDUSDCDAITUSDPAXUSDEURGBP hl_pct_change_12_1h bb20_2_upp_1h live_data_ok
Similar Strategies: (based on used indicators)
Strategy: NostalgiaForInfinityX2_13, Similarity Score: 97.92%
Strategy: NostalgiaForInfinityX2_12, Similarity Score: 91.67%
Strategy: NostalgiaForInfinityX2_14, Similarity Score: 91.67%
Strategy: NostalgiaForInfinityX2_15, Similarity Score: 91.67%
Strategy: NostalgiaForInfinityX2_16, Similarity Score: 91.67%
Strategy: NostalgiaForInfinityX2_17, Similarity Score: 91.67%
Strategy: NostalgiaForInfinityX2_18, Similarity Score: 89.58%
Strategy: NostalgiaForInfinityX2_10, Similarity Score: 87.5%
Strategy: NostalgiaForInfinityX2_19, Similarity Score: 81.25%
Strategy: NostalgiaForInfinityX2_20, Similarity Score: 81.25%
Strategy: NostalgiaForInfinityX2_21, Similarity Score: 81.25%
Strategy: NostalgiaForInfinityX2_22, Similarity Score: 81.25%
last change: 2023-04-03 14:59:11