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The SlowPotato strategy is a slow order strategy based on averages. It operates on a 5-minute interval and uses a 5-day average. The premise of the strategy is to buy when the price reaches or falls below the 5-day average low and wait for a sell trigger when the price reaches or exceeds the 5-day average high.
The strategy calculates the average high and low for the past 288 (5 days * 24 hours * 60 minutes / 5 minutes) data points.
When the current price is below or equal to the average low and the volume is above zero, a buy signal is generated.
Conversely, when the current price is above or equal to the average high and the volume is above zero, a sell signal is generated. The strategy includes a minimal return on investment (ROI) table, which specifies the expected returns at different time periods. It also has a stoploss value that determines the maximum acceptable loss before selling the asset. Trailing stoploss is disabled in this strategy. The populate_indicators function is not implemented in this strategy, so it doesn't calculate any additional technical indicators. Please note that this strategy is currently under development and testing.
The strategy calculates the average high and low for the past 288 (5 days * 24 hours * 60 minutes / 5 minutes) data points.
When the current price is below or equal to the average low and the volume is above zero, a buy signal is generated.
Conversely, when the current price is above or equal to the average high and the volume is above zero, a sell signal is generated. The strategy includes a minimal return on investment (ROI) table, which specifies the expected returns at different time periods. It also has a stoploss value that determines the maximum acceptable loss before selling the asset. Trailing stoploss is disabled in this strategy. The populate_indicators function is not implemented in this strategy, so it doesn't calculate any additional technical indicators. Please note that this strategy is currently under development and testing.
stoploss: -0.171 timeframe: 5m hash(sha256): 6394735adca965c9cdcc479f6d25ec2c3e27c488c0f0a31d9612cfe6e86c915f
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last change: 2022-07-11 03:55:17