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The Apollo11 strategy is a trading strategy that uses various indicators to generate buy signals and determine the sell conditions. Here's a brief description of what the strategy does:
populate_indicators(): This function calculates and populates several indicators on the given dataframe, including exponential moving averages (EMAs), Bollinger Bands, and volume-weighted moving average convergence divergence (VWMACD). populate_buy_trend(): This function generates buy signals based on specific conditions.
It checks for multiple buy signals (buy_signal_1, buy_signal_2, buy_signal_3) and applies conditions to identify potential buying opportunities.
The conditions involve comparisons between different indicators and price/volume levels.
populate_sell_trend(): This function populates the sell column in the dataframe. Currently, it sets all sell values to 0, indicating that no specific sell conditions are defined in this strategy. should_sell(): This function determines the percentage of the profit to sell at based on the current profit level. It uses a series of if-else conditions to determine the appropriate sell percentage. Higher profits result in higher sell percentages, while significant losses trigger a different selling strategy based on the time since the trade was opened. Overall, the Apollo11 strategy aims to identify buy signals based on indicator conditions and provides a dynamic selling strategy based on the current profit level and trade duration.
It checks for multiple buy signals (buy_signal_1, buy_signal_2, buy_signal_3) and applies conditions to identify potential buying opportunities.
The conditions involve comparisons between different indicators and price/volume levels.
populate_sell_trend(): This function populates the sell column in the dataframe. Currently, it sets all sell values to 0, indicating that no specific sell conditions are defined in this strategy. should_sell(): This function determines the percentage of the profit to sell at based on the current profit level. It uses a series of if-else conditions to determine the appropriate sell percentage. Higher profits result in higher sell percentages, while significant losses trigger a different selling strategy based on the time since the trade was opened. Overall, the Apollo11 strategy aims to identify buy signals based on indicator conditions and provides a dynamic selling strategy based on the current profit level and trade duration.
stoploss: -0.16 timeframe: 5m hash(sha256): a8e9f7f7e46e36750bc431444df11c1ec36ff6c9a57216be4403aa9d1a780384
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last change: 2022-07-11 07:43:06