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The given code represents a trading strategy called "epretrace." Here is a short description of what the strategy does:
The epretrace strategy is designed to identify potential buying and selling opportunities in the market. It uses various indicators and conditions to make trading decisions. In the populate_indicators method, the strategy populates any required indicators in the provided dataframe.
The populate_buy_trend method identifies buy signals based on the following conditions: The current value of a specified indicator (self.epcat1.value) is less than a certain percentage of the maximum value of the same indicator in the previous window (self.ep_retracement_window.value).
The current value of the indicator is greater than another percentage of the maximum value in the previous window.
The volume is greater than zero. If these conditions are met, the method sets the 'buy' column of the dataframe to 1 for the corresponding row. The populate_sell_trend method identifies sell signals based on the following condition: The closing price is greater than one million. The volume is greater than zero. If these conditions are met, the method sets the 'sell' column of the dataframe to 1 for the corresponding row. The should_stop_loss method determines whether a trade should be stopped based on the current rate, current profit, and other parameters. It calculates a stop loss price (set_stoploss) based on the open rate of the trade and a specified percentage (self.ep_stop.value). If the current rate falls below the stop loss price, a negative value (-0.000001) is returned to indicate that the trade should be stopped. The should_sell method determines whether a trade should be closed based on the current rate, current profit, and other parameters. It calculates a target sell price (eptarget) based on the open rate of the trade and a specified percentage (self.ep_target.value). If the current rate exceeds or equals the target sell price, 'sell_ep2mas' is returned to indicate that the trade should be closed. In summary, the epretrace strategy aims to identify buy and sell signals based on specific indicator values, volume conditions, and price thresholds. It also incorporates stop loss and target sell prices to manage trades.
The populate_buy_trend method identifies buy signals based on the following conditions: The current value of a specified indicator (self.epcat1.value) is less than a certain percentage of the maximum value of the same indicator in the previous window (self.ep_retracement_window.value).
The current value of the indicator is greater than another percentage of the maximum value in the previous window.
The volume is greater than zero. If these conditions are met, the method sets the 'buy' column of the dataframe to 1 for the corresponding row. The populate_sell_trend method identifies sell signals based on the following condition: The closing price is greater than one million. The volume is greater than zero. If these conditions are met, the method sets the 'sell' column of the dataframe to 1 for the corresponding row. The should_stop_loss method determines whether a trade should be stopped based on the current rate, current profit, and other parameters. It calculates a stop loss price (set_stoploss) based on the open rate of the trade and a specified percentage (self.ep_stop.value). If the current rate falls below the stop loss price, a negative value (-0.000001) is returned to indicate that the trade should be stopped. The should_sell method determines whether a trade should be closed based on the current rate, current profit, and other parameters. It calculates a target sell price (eptarget) based on the open rate of the trade and a specified percentage (self.ep_target.value). If the current rate exceeds or equals the target sell price, 'sell_ep2mas' is returned to indicate that the trade should be closed. In summary, the epretrace strategy aims to identify buy and sell signals based on specific indicator values, volume conditions, and price thresholds. It also incorporates stop loss and target sell prices to manage trades.
stoploss: -0.999 timeframe: 5m hash(sha256): bfb8ac5483941664cbdd2d382a4b6f85b0ca153a937908e8b6576d749c04f327 indicators: date volume close
No similar strategies found. (based on used indicators)
last change: 2024-04-29 20:15:34