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The ClucV5M1 strategy is a trading strategy implemented as a class in Python. It follows a backtesting approach to evaluate various trading strategies. The populate_indicators function is responsible for calculating and populating the required indicators for the strategy.
It merges informative data from the 1-hour timeframe with the current timeframe, ensuring that the data is filled forward when necessary.
Additionally, it calculates indicators for the normal timeframe.
The populate_buy_trend function identifies the buy signals for the strategy. It applies specific conditions to determine when to enter a buy position. These conditions include: The current close price is higher than the 1-hour exponential moving average (ema_200_1h). The 50-day exponential moving average (ema_50) is higher than the 200-day exponential moving average (ema_200). The 50-day exponential moving average of the 1-hour timeframe (ema_50_1h) is higher than the 200-day exponential moving average of the 1-hour timeframe (ema_200_1h). The lower value (lower) of the Bollinger Bands indicator is positive (shifted one period back). The difference between the Bollinger Bands (bbdelta) and the close price is greater than 3.1% of the close price. The difference between the close price and the previous close price (closedelta) is greater than 1.8% of the close price. The tail value is less than 23.3% of the Bollinger Bands delta (bbdelta). The close price is lower than the lower value of the Bollinger Bands (shifted one period back). The close price is less than or equal to the previous close price. The volume is greater than 0 (to ensure it is not zero). The populate_sell_trend function identifies the sell signals for the strategy. It applies a single condition to determine when to exit a buy position. The condition is: The current close price is higher than 1.01 times the middle value of the Bollinger Bands (bb_middleband), and the volume is greater than 0 (to ensure it is not zero). The functions modify the input dataframe by adding a "buy" or "sell" value of 1 to the respective rows where the conditions are met. The modified dataframe is then returned.
It merges informative data from the 1-hour timeframe with the current timeframe, ensuring that the data is filled forward when necessary.
Additionally, it calculates indicators for the normal timeframe.
The populate_buy_trend function identifies the buy signals for the strategy. It applies specific conditions to determine when to enter a buy position. These conditions include: The current close price is higher than the 1-hour exponential moving average (ema_200_1h). The 50-day exponential moving average (ema_50) is higher than the 200-day exponential moving average (ema_200). The 50-day exponential moving average of the 1-hour timeframe (ema_50_1h) is higher than the 200-day exponential moving average of the 1-hour timeframe (ema_200_1h). The lower value (lower) of the Bollinger Bands indicator is positive (shifted one period back). The difference between the Bollinger Bands (bbdelta) and the close price is greater than 3.1% of the close price. The difference between the close price and the previous close price (closedelta) is greater than 1.8% of the close price. The tail value is less than 23.3% of the Bollinger Bands delta (bbdelta). The close price is lower than the lower value of the Bollinger Bands (shifted one period back). The close price is less than or equal to the previous close price. The volume is greater than 0 (to ensure it is not zero). The populate_sell_trend function identifies the sell signals for the strategy. It applies a single condition to determine when to exit a buy position. The condition is: The current close price is higher than 1.01 times the middle value of the Bollinger Bands (bb_middleband), and the volume is greater than 0 (to ensure it is not zero). The functions modify the input dataframe by adding a "buy" or "sell" value of 1 to the respective rows where the conditions are met. The modified dataframe is then returned.
stoploss: -0.99 timeframe: 5m hash(sha256): 3c06a04653cc05cccfd3738c720973c8d1bab8fd8bf1198aced85caaf7678816 indicators: upper ema_200 ema_50 close sma_5 tail bb_lowerband ema_200_1h bbdelta volume closedelta volume_mean_slow ema_50_1h mid max_open_trades lower bb_middleband rsi bb_upperband ema_slow low
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last change: 2023-08-03 15:35:30