The NostalgiaForInfinityV1 strategy is a trading strategy implemented in a backtesting website. It consists of three main components: indicator population, buy signal generation, and sell signal generation. Indicator Population:
The strategy first populates various indicators using the input dataframe and metadata.
These indicators are calculated based on different timeframes and are used for making trading decisions.
Buy Signal Generation: The buy signal is generated based on multiple conditions: The close price is below the 9-day simple moving average (sma_9) and above the 200-day exponential moving average of the 1-hour timeframe (ema_200_1h).
The 50-day exponential moving average (ema_50) is above the 200-day exponential moving average (ema_200) on the current timeframe, as well as on the 1-hour timeframe (ema_50_1h). Other conditions related to indicators such as lower, bbdelta, closedelta, tail, and volume are also checked. Sell Signal Generation: The sell signal is generated based on multiple conditions: The close price is above the upper Bollinger Band (bb_upperband), and the previous two close prices were also above their respective upper Bollinger Bands. The relative strength index (rsi) is above 78. The close price is below the 200-day exponential moving average (ema_200), but above the 50-day exponential moving average (ema_50), and the rsi is above 50. The strategy assigns a value of 1 to the 'buy' column when the buy conditions are met and a value of 1 to the 'sell' column when the sell conditions are met. The updated dataframe with buy and sell signals is then returned.
These indicators are calculated based on different timeframes and are used for making trading decisions.
Buy Signal Generation: The buy signal is generated based on multiple conditions: The close price is below the 9-day simple moving average (sma_9) and above the 200-day exponential moving average of the 1-hour timeframe (ema_200_1h).
The 50-day exponential moving average (ema_50) is above the 200-day exponential moving average (ema_200) on the current timeframe, as well as on the 1-hour timeframe (ema_50_1h). Other conditions related to indicators such as lower, bbdelta, closedelta, tail, and volume are also checked. Sell Signal Generation: The sell signal is generated based on multiple conditions: The close price is above the upper Bollinger Band (bb_upperband), and the previous two close prices were also above their respective upper Bollinger Bands. The relative strength index (rsi) is above 78. The close price is below the 200-day exponential moving average (ema_200), but above the 50-day exponential moving average (ema_50), and the rsi is above 50. The strategy assigns a value of 1 to the 'buy' column when the buy conditions are met and a value of 1 to the 'sell' column when the sell conditions are met. The updated dataframe with buy and sell signals is then returned.
startup_candle_count : 200 ema_50_1h: -0.001%
stoploss: -0.36 timeframe: 5m hash(sha256): 73271ad1c5f2d271ae03eb5a67855e566bcd9a57b2a36b99b06fcc625bdb12e9 indicators: upper ema_200 ema_50 close sma_5 tail bb_lowerband ema_200_1h bbdelta volume smaHigh ATR ssl_up closedelta sslDown ema_20 hlv volume_mean_slow ema_50_1h smaLow high sslUp mid ssl_down_1h ssl_down rsi_1h sma_9 lower bb_middleband rsi bb_upperband ema_slow low ssl_up_1h
Similar Strategies: (based on used indicators)
Strategy: 08_NostalgiaForInfinityV2_OPT, Similarity Score: 97.14%
Strategy: 08_NostalgiaForInfinityV2_OPT_02, Similarity Score: 97.14%
Strategy: NostalgiaForInfinityV2, Similarity Score: 97.14%
Strategy: 01_CombinedBinHAndClucV7_OPT, Similarity Score: 94.29%
Strategy: 01_CombinedBinHAndClucV7_OPT_02, Similarity Score: 94.29%
Strategy: 02_CombinedBinHClucAndMADV5, Similarity Score: 94.29%
Strategy: 04_CombinedBinHAndClucV8, Similarity Score: 94.29%
Strategy: CombinedBinHAndClucV6, Similarity Score: 94.29%
Strategy: CombinedBinHAndClucV6_2, Similarity Score: 94.29%
Strategy: CombinedBinHAndClucV7, Similarity Score: 94.29%
Strategy: CombinedBinHAndClucV7_702, Similarity Score: 94.29%
Strategy: CombinedBinHAndClucV8Hyper, Similarity Score: 94.29%
Strategy: CombinedBinHAndClucV8XH, Similarity Score: 94.29%
Strategy: CombinedBinHAndClucV8XHO, Similarity Score: 94.29%
Strategy: CombinedBinHClucAndMADV5, Similarity Score: 94.29%
Strategy: CombinedBinHClucAndMADV5_2, Similarity Score: 94.29%
Strategy: Discord_1_TEST, Similarity Score: 94.29%
Strategy: Discord_1_test, Similarity Score: 94.29%
Strategy: Discord_Bzed, Similarity Score: 94.29%
Strategy: CombinedBinHClucAndSMAOffset, Similarity Score: 91.43%
Strategy: CombinedBinHClucAndSMAOffset_2, Similarity Score: 91.43%
Strategy: HybridMonster, Similarity Score: 88.57%
Strategy: 02_CombinedBinHClucAndMADV6, Similarity Score: 85.71%
Strategy: FrankenStrat, Similarity Score: 85.71%
Strategy: FrankenStrat_259, Similarity Score: 85.71%
Strategy: MACD_23, Similarity Score: 85.71%
Strategy: 06_CombinedBinHAndClucV9, Similarity Score: 82.86%
Strategy: CBPete9, Similarity Score: 82.86%
Strategy: CombinedAMD, Similarity Score: 82.86%
Strategy: CombinedBinHClucAndMADV9_269, Similarity Score: 82.86%
Strategy: CombinedBinHClucAndMADV9_5, Similarity Score: 82.86%
Strategy: CombinedBinHClucAndMADV9_858, Similarity Score: 82.86%
Strategy: MadV9HO, Similarity Score: 82.86%
last change: 2024-05-02 15:57:14