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The BinHV27 strategy is a trading strategy implemented in Python for backtesting purposes. Here is a short description of what the strategy does:
It uses various technical indicators from the talib and qtpylib libraries to analyze price data. The strategy is designed for a 5-minute timeframe.
It calculates indicators such as RSI, EMA, ADX, MINUS_DI, PLUS_DI, and SMA based on the input dataframe.
It determines the trend direction by comparing moving averages.
It identifies specific conditions for entering a buy trade based on a combination of indicator values, trend patterns, and price levels. It generates buy signals when certain conditions are met, such as the RSI being above a certain threshold, the trend changing direction, and the ADX indicating a strong trend. It determines the conditions for exiting a buy trade based on the reversal of trend, slowing down of price movement, and other criteria. It generates sell signals when specific conditions are met, such as the price exceeding certain moving averages, the RSI reaching a high level, or the trend showing signs of reversal. Overall, the strategy aims to capture potential trading opportunities by identifying buy and sell signals based on a combination of technical indicators and trend patterns.
It calculates indicators such as RSI, EMA, ADX, MINUS_DI, PLUS_DI, and SMA based on the input dataframe.
It determines the trend direction by comparing moving averages.
It identifies specific conditions for entering a buy trade based on a combination of indicator values, trend patterns, and price levels. It generates buy signals when certain conditions are met, such as the RSI being above a certain threshold, the trend changing direction, and the ADX indicating a strong trend. It determines the conditions for exiting a buy trade based on the reversal of trend, slowing down of price movement, and other criteria. It generates sell signals when specific conditions are met, such as the price exceeding certain moving averages, the RSI reaching a high level, or the trend showing signs of reversal. Overall, the strategy aims to capture potential trading opportunities by identifying buy and sell signals based on a combination of technical indicators and trend patterns.
stoploss: -0.5 timeframe: 5m hash(sha256): 3525c2bc47b46e0c34dd8e507f468b655d177fd5fc19a793dfeccaf3ef056736 indicators: preparechangetrend close lowsma delta trend minusdi slowingdown continueup slowsma highsma bigdown emarsi bigup minusdiema adx plusdi fastsma preparechangetrendconfirm rsi plusdiema
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last change: 2022-11-02 04:22:48