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The BigZ04_TSL4 strategy is a trading strategy that aims to identify buying opportunities based on various technical indicators. Here is a breakdown of the important parts of the strategy:
Indicators Population:
The strategy starts by populating indicators on the given dataframe, including informative_1h indicators and normal timeframe indicators. Buy Trend Conditions:
The strategy defines multiple conditions for triggering a buy signal.
These conditions are stored in a list.
Each condition is a combination of different technical criteria, such as price, moving averages, Bollinger Bands, RSI (Relative Strength Index), volume, etc.
The conditions are evaluated for each data point in the dataframe to determine if a buy signal should be generated. Here is a summary of some of the buy conditions: Condition 1: Price is above the 200-day exponential moving average (ema_200), and other criteria related to Bollinger Bands, RSI, volume, and candlestick patterns are met. Condition 2: Price is above the 200-day exponential moving average (ema_200), and other criteria related to histogram, Bollinger Bands, RSI, volume, and candlestick patterns are met. Condition 3: Price is above the 200-day exponential moving average (ema_200), and other criteria related to RSI, price dips, volume, and candlestick patterns are met. Condition 4: Price is above the 200-day exponential moving average (ema_200), and other criteria related to Bollinger Bands, volume, and candlestick patterns are met. Condition 5: Price is above the 200-day exponential moving average (ema_200), and other criteria related to moving averages (EMA), MACD (Moving Average Convergence Divergence), Bollinger Bands, volume, and candlestick patterns are met. The strategy evaluates these conditions and generates a buy signal when any of the conditions are satisfied. It uses technical indicators and patterns to identify potential buying opportunities in the market.
These conditions are stored in a list.
Each condition is a combination of different technical criteria, such as price, moving averages, Bollinger Bands, RSI (Relative Strength Index), volume, etc.
The conditions are evaluated for each data point in the dataframe to determine if a buy signal should be generated. Here is a summary of some of the buy conditions: Condition 1: Price is above the 200-day exponential moving average (ema_200), and other criteria related to Bollinger Bands, RSI, volume, and candlestick patterns are met. Condition 2: Price is above the 200-day exponential moving average (ema_200), and other criteria related to histogram, Bollinger Bands, RSI, volume, and candlestick patterns are met. Condition 3: Price is above the 200-day exponential moving average (ema_200), and other criteria related to RSI, price dips, volume, and candlestick patterns are met. Condition 4: Price is above the 200-day exponential moving average (ema_200), and other criteria related to Bollinger Bands, volume, and candlestick patterns are met. Condition 5: Price is above the 200-day exponential moving average (ema_200), and other criteria related to moving averages (EMA), MACD (Moving Average Convergence Divergence), Bollinger Bands, volume, and candlestick patterns are met. The strategy evaluates these conditions and generates a buy signal when any of the conditions are satisfied. It uses technical indicators and patterns to identify potential buying opportunities in the market.
stoploss: -0.99 timeframe: 5m hash(sha256): 98169a55d041b30e0c9647999629f6cbaab01797947c51c9fdff32ecd3616c93 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: 2022-07-02 19:54:08