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The CombinedBinHClucAndSMAOffset strategy combines multiple indicators to generate buy and sell signals for trading. Here's a breakdown of what the strategy does:
populate_indicators: This function populates the indicators used by the strategy. It takes a DataFrame containing price and volume data and returns the modified DataFrame with additional indicator columns.
populate_buy_trend: This function determines the conditions for buying an asset.
It defines multiple sets of conditions using logical operators like & (AND) and | (OR).
The conditions include comparisons between different price and indicator values, rolling calculations, and threshold checks. If any of the conditions are met, the 'buy' signal is set to 1 for the corresponding rows in the DataFrame. populate_sell_trend: This function determines the conditions for selling an asset. Similar to populate_buy_trend, it defines conditions based on price and indicator values. If any of the conditions are met, the 'sell' signal is set to 1 for the corresponding rows in the DataFrame. The strategy uses various indicators such as moving averages (MA), exponential moving averages (EMA), Bollinger Bands (BB), relative strength index (RSI), moving average convergence divergence (MACD), and others. The specific parameters and calculations involved in these indicators are not explicitly mentioned in the provided code snippet. Overall, the strategy aims to identify potential buying and selling opportunities based on the defined conditions and the values of different indicators.
populate_buy_trend: This function determines the conditions for buying an asset.
It defines multiple sets of conditions using logical operators like & (AND) and | (OR).
The conditions include comparisons between different price and indicator values, rolling calculations, and threshold checks. If any of the conditions are met, the 'buy' signal is set to 1 for the corresponding rows in the DataFrame. populate_sell_trend: This function determines the conditions for selling an asset. Similar to populate_buy_trend, it defines conditions based on price and indicator values. If any of the conditions are met, the 'sell' signal is set to 1 for the corresponding rows in the DataFrame. The strategy uses various indicators such as moving averages (MA), exponential moving averages (EMA), Bollinger Bands (BB), relative strength index (RSI), moving average convergence divergence (MACD), and others. The specific parameters and calculations involved in these indicators are not explicitly mentioned in the provided code snippet. Overall, the strategy aims to identify potential buying and selling opportunities based on the defined conditions and the values of different indicators.
stoploss: -0.99 timeframe: 5m hash(sha256): 2eacf04b8334d7dfd6d6f1577bb810fd5d9872385755deb214b2368eca417525 indicators: sma_200_1h upper EWO ema_200 ema_50 close ewo_low sma_5 tail ma_offset_buy bb_lowerband mfi ema_200_1h bbdelta bull_100_1h volume smaHigh low_offset ATR ma_buy ssl_up closedelta ema_100_1h sslDown high_offset open hlv volume_mean_slow base_nb_candles_buy bull_100 smaLow ema_50_1h sma_200 high sslUp fast_ewo slow_ewo mid ma_offset_sell sell_trigger base_nb_candles_sell ssl_down_1h ssl_down rsi_1h ma_sell ema_100 lower ema_12 bb_middleband rsi buy_trigger sma_200_dec bb_upperband ema_slow low ema_
Similar Strategies: (based on used indicators)
Strategy: CombinedBinHClucAndSMAOffset, Similarity Score: 98.25%
last change: 2023-04-26 07:38:14