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The EMACross strategy is a trading strategy that uses exponential moving averages (EMAs) to generate buy and sell signals. Here's a breakdown of what the strategy does:
populate_indicators function:
Calculates EMAs with different time periods for short and long EMAs. Adds the calculated EMAs to the input dataframe.
populate_entry_trend function: Based on the calculated EMAs, determines the buy signal for the dataframe.
Conditions for buy signal: The short EMA crosses above the long EMA.
The volume is greater than 0. If the conditions are met, sets the 'buy' column in the dataframe to 1. populate_exit_trend function: Based on the calculated EMAs, determines the sell signal for the dataframe. Conditions for sell signal: The long EMA crosses above the short EMA. The volume is greater than 0. If the conditions are met, sets the 'sell' column in the dataframe to 1. The strategy utilizes the TA-Lib library to calculate the EMAs and the qtpylib library for comparing the EMAs and volume. The goal of the strategy is to identify potential entry and exit points for trading based on the EMA crossovers and volume conditions.
populate_entry_trend function: Based on the calculated EMAs, determines the buy signal for the dataframe.
Conditions for buy signal: The short EMA crosses above the long EMA.
The volume is greater than 0. If the conditions are met, sets the 'buy' column in the dataframe to 1. populate_exit_trend function: Based on the calculated EMAs, determines the sell signal for the dataframe. Conditions for sell signal: The long EMA crosses above the short EMA. The volume is greater than 0. If the conditions are met, sets the 'sell' column in the dataframe to 1. The strategy utilizes the TA-Lib library to calculate the EMAs and the qtpylib library for comparing the EMAs and volume. The goal of the strategy is to identify potential entry and exit points for trading based on the EMA crossovers and volume conditions.
stoploss: -0.044 timeframe: 5m hash(sha256): 15cf9e19ab8667d48a9982ece19d738eaf504ac4218b12a34e5caad9815ae3dc
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last change: 2023-01-04 18:41:06