The "EMASkipPump" strategy is designed to avoid pump and dump market conditions. It utilizes a combination of technical indicators to make buying and selling decisions. Here is a breakdown of how the strategy works:
The strategy uses three Exponential Moving Averages (EMAs) with different time periods: a short-term EMA (5 periods), a medium-term EMA (12 periods), and a long-term EMA (21 periods).
It also calculates Bollinger Bands using the typical price and a window of 20 periods with 2 standard deviations.
The strategy calculates the minimum and maximum values of the closing price over a medium-term EMA period.
During the "populate_buy_trend" phase: It identifies potential buy signals based on the following conditions: The volume is less than 20 times the 30-day rolling average volume. The closing price is below both the short-term EMA and the medium-term EMA. The closing price is equal to the minimum value calculated over the medium-term EMA period. The closing price is less than or equal to the lower Bollinger Band. During the "populate_sell_trend" phase: It identifies potential sell signals based on the following conditions: The closing price is above both the short-term EMA and the medium-term EMA. The closing price is greater than or equal to the maximum value calculated over the medium-term EMA period. The closing price is greater than or equal to the upper Bollinger Band. Additionally, the strategy has defined a minimal return on investment (ROI) and a stop-loss value: The minimal_roi dictionary specifies the minimum desired ROI at different sell points. For example, at the sell point "0", a minimum ROI of 0.2 (20%) is expected. The stoploss attribute defines the optimal stop-loss value for the strategy, which is set to -0.1 (-10%) by default. The ticker_interval attribute specifies the optimal ticker interval for the strategy, which is set to '5m' (5 minutes) by default. Overall, the strategy aims to identify potential buying opportunities when the market shows signs of avoiding pump and dump scenarios and sell when specific criteria are met based on the EMAs, Bollinger Bands, and other indicators.
It also calculates Bollinger Bands using the typical price and a window of 20 periods with 2 standard deviations.
The strategy calculates the minimum and maximum values of the closing price over a medium-term EMA period.
During the "populate_buy_trend" phase: It identifies potential buy signals based on the following conditions: The volume is less than 20 times the 30-day rolling average volume. The closing price is below both the short-term EMA and the medium-term EMA. The closing price is equal to the minimum value calculated over the medium-term EMA period. The closing price is less than or equal to the lower Bollinger Band. During the "populate_sell_trend" phase: It identifies potential sell signals based on the following conditions: The closing price is above both the short-term EMA and the medium-term EMA. The closing price is greater than or equal to the maximum value calculated over the medium-term EMA period. The closing price is greater than or equal to the upper Bollinger Band. Additionally, the strategy has defined a minimal return on investment (ROI) and a stop-loss value: The minimal_roi dictionary specifies the minimum desired ROI at different sell points. For example, at the sell point "0", a minimum ROI of 0.2 (20%) is expected. The stoploss attribute defines the optimal stop-loss value for the strategy, which is set to -0.1 (-10%) by default. The ticker_interval attribute specifies the optimal ticker interval for the strategy, which is set to '5m' (5 minutes) by default. Overall, the strategy aims to identify potential buying opportunities when the market shows signs of avoiding pump and dump scenarios and sell when specific criteria are met based on the EMAs, Bollinger Bands, and other indicators.
stoploss: -0.1 timeframe: 5m hash(sha256): d0f58c73c9ad5981600270c4c1b6ce7740bb8dba418628c6d927e69844b719cf indicators: min upper mid lower volume bb_middleband close bb_upperband bb_lowerband max
No similar strategies found. (based on used indicators)
last change: 2024-04-29 21:01:24