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The BinHV45 strategy is a backtesting trading strategy that uses Bollinger Bands to identify buy signals in the market. Here's a breakdown of what the strategy does:
It calculates the Bollinger Bands indicator using the bollinger_bands function, which takes the stock price, window size (40 in this case), and the number of standard deviations (2 in this case). The strategy populates various indicators in the dataframe:
mid: The middle band of the Bollinger Bands.

lower: The lower band of the Bollinger Bands.

bbdelta: The absolute difference between the middle and lower bands.

pricedelta: The absolute difference between the opening and closing prices. closedelta: The absolute difference between the current closing price and the previous closing price. tail: The absolute difference between the closing price and the lowest price. The strategy determines the buy signals based on the following conditions: The previous lower band is greater than 0. The bbdelta is greater than 0.008 times the closing price. The closedelta is greater than 0.0175 times the closing price. The tail is less than 0.25 times the bbdelta. The closing price is less than the previous lower band. The closing price is less than or equal to the previous closing price. The strategy does not provide any sell signals (populate_sell_trend function returns no sell signal). Additionally, the strategy sets the following parameters: minimal_roi: A dictionary defining the minimum return on investment at different time intervals. stoploss: A fixed stoploss percentage. timeframe: The timeframe for the data. Overall, the strategy aims to capture buy signals when the price is near the lower Bollinger Band and certain conditions are met. It doesn't provide any sell signals, so the selling decisions would need to be implemented separately.

lower: The lower band of the Bollinger Bands.

bbdelta: The absolute difference between the middle and lower bands.

pricedelta: The absolute difference between the opening and closing prices. closedelta: The absolute difference between the current closing price and the previous closing price. tail: The absolute difference between the closing price and the lowest price. The strategy determines the buy signals based on the following conditions: The previous lower band is greater than 0. The bbdelta is greater than 0.008 times the closing price. The closedelta is greater than 0.0175 times the closing price. The tail is less than 0.25 times the bbdelta. The closing price is less than the previous lower band. The closing price is less than or equal to the previous closing price. The strategy does not provide any sell signals (populate_sell_trend function returns no sell signal). Additionally, the strategy sets the following parameters: minimal_roi: A dictionary defining the minimum return on investment at different time intervals. stoploss: A fixed stoploss percentage. timeframe: The timeframe for the data. Overall, the strategy aims to capture buy signals when the price is near the lower Bollinger Band and certain conditions are met. It doesn't provide any sell signals, so the selling decisions would need to be implemented separately.

stoploss:-0.34103timeframe:1mhash(sha256):503496bf855f5fb162fe7f183990c6781ebf08145218788d8f7fd097f7f562e6indicators:sell mid lower pricedelta close closedelta tail open low bbdelta

No similar strategies found. (based on used indicators)last change: 2023-06-29 00:57:41