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The BigZ04_TSL3 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:
The populate_indicators method takes a dataframe and metadata as input and returns a modified dataframe with additional indicators calculated based on the input data.
The populate_buy_trend method populates the buy conditions for the strategy.
It defines multiple conditions using logical operators and comparisons on the dataframe's columns.
These conditions determine when to place a buy order. Some of the important conditions include: Condition 1: It checks if the close price is above the 200-day exponential moving average (ema_200) and the 200-day exponential moving average of the 1-hour timeframe (ema_200_1h). It also considers conditions related to Bollinger Bands, relative strength index (RSI), volume, and candlestick patterns. Condition 2: It checks for certain conditions related to the histogram, Bollinger Bands, RSI, volume, and candlestick patterns. Condition 3: It checks for conditions related to the 200-day exponential moving average of the 1-hour timeframe (ema_200_1h), Bollinger Bands, RSI, volume, and candlestick patterns. Condition 4: It checks for conditions related to RSI, Bollinger Bands, volume, and candlestick patterns. Condition 5: It checks for conditions related to exponential moving averages, MACD, Bollinger Bands, volume, and candlestick patterns. Condition 6: It checks for conditions related to RSI of the 1-hour timeframe, exponential moving averages, and volume. These conditions define the specific criteria for buying based on the strategy's rules. The strategy likely has additional methods and logic for other aspects such as selling, risk management, and position sizing, which are not included in the provided code snippet.
The populate_buy_trend method populates the buy conditions for the strategy.
It defines multiple conditions using logical operators and comparisons on the dataframe's columns.
These conditions determine when to place a buy order. Some of the important conditions include: Condition 1: It checks if the close price is above the 200-day exponential moving average (ema_200) and the 200-day exponential moving average of the 1-hour timeframe (ema_200_1h). It also considers conditions related to Bollinger Bands, relative strength index (RSI), volume, and candlestick patterns. Condition 2: It checks for certain conditions related to the histogram, Bollinger Bands, RSI, volume, and candlestick patterns. Condition 3: It checks for conditions related to the 200-day exponential moving average of the 1-hour timeframe (ema_200_1h), Bollinger Bands, RSI, volume, and candlestick patterns. Condition 4: It checks for conditions related to RSI, Bollinger Bands, volume, and candlestick patterns. Condition 5: It checks for conditions related to exponential moving averages, MACD, Bollinger Bands, volume, and candlestick patterns. Condition 6: It checks for conditions related to RSI of the 1-hour timeframe, exponential moving averages, and volume. These conditions define the specific criteria for buying based on the strategy's rules. The strategy likely has additional methods and logic for other aspects such as selling, risk management, and position sizing, which are not included in the provided code snippet.
stoploss: -0.99 timeframe: 5m hash(sha256): 167b13bb37f9c8d5289b130ee1e5990be923c3b8fe66806d45b3ef97e7a6a41e indicators: upper ema_200 ema_50 close sma_5 bb_lowerband ema_200_1h ma_sell_val volume open volume_mean_slow mid macd rsi_1h bb_lowerband_1h hist atr lower ema_12 signal bb_middleband rsi bb_upperband ema_26 low close_1h
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last change: 2022-07-27 18:01:02