The E0V1E strategy is a backtesting strategy that aims to identify potential entry and exit points for trading. Here's a short description of what the strategy does: Indicators: Calculates the Exponential Moving Average (EMA) with different time periods. Calculates the EWO (Elliott Wave Oscillator) using a custom function.
Computes various other indicators such as RSI (Relative Strength Index), STOCHF (Stochastic Fast), Bollinger Bands, CTI (Cumulative Ticker Index), and volume averages.
Entry Conditions: Considers multiple conditions for potential entry points, including RSI values, EMA values, and the EWO indicator.
Checks for specific criteria like RSI thresholds, EMA thresholds, and CTI values to determine entry signals. Stop Loss: Implements a custom stop loss mechanism based on time elapsed since trade entry and current profit levels. Gradually adjusts the stop loss value based on predefined rules and current market conditions. Exit Conditions: Defines exit criteria based on specific conditions, including the deadfish strategy. Evaluates factors such as Bollinger Bands, candlestick patterns, and volume indicators to determine exit signals. Trend Analysis: Identifies and labels potential exit points for the strategy based on trend analysis. Sets exit_long and exit_tag values in the dataframe to indicate when to exit a long position.
Computes various other indicators such as RSI (Relative Strength Index), STOCHF (Stochastic Fast), Bollinger Bands, CTI (Cumulative Ticker Index), and volume averages.
Entry Conditions: Considers multiple conditions for potential entry points, including RSI values, EMA values, and the EWO indicator.
Checks for specific criteria like RSI thresholds, EMA thresholds, and CTI values to determine entry signals. Stop Loss: Implements a custom stop loss mechanism based on time elapsed since trade entry and current profit levels. Gradually adjusts the stop loss value based on predefined rules and current market conditions. Exit Conditions: Defines exit criteria based on specific conditions, including the deadfish strategy. Evaluates factors such as Bollinger Bands, candlestick patterns, and volume indicators to determine exit signals. Trend Analysis: Identifies and labels potential exit points for the strategy based on trend analysis. Sets exit_long and exit_tag values in the dataframe to indicate when to exit a long position.
stoploss: -0.1 timeframe: 5m hash(sha256): 5a945f7085047bb7c8cffe645632b9d23cf07b679baf8c229932d2c4e9010dac indicators: upper EWO close exit_long exit_tag volume_mean_12 fastk rsi_fast bb_middleband2 volume fastd sma_15 bb_upperband2 volume_mean_24 mid bb_width ema_8 ema_16 cti lower rsi_slow rsi low bb_lowerband2
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last change: 2024-05-02 13:38:21