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The CofiBitStrategy is a trading strategy implemented in the form of a backtesting website. Here is a short description of what the strategy does:
The strategy uses technical analysis indicators to make buy and sell decisions. The minimal ROI (Return on Investment) is defined, which specifies the desired profit targets at different stages of the trade.
The stoploss is set at -0.25, indicating the maximum acceptable loss before triggering a sell signal.
The ticker interval is set to 5 minutes, indicating that the strategy operates on 5-minute candlestick data.
The strategy uses the following indicators: Stochastic Fast: Calculates the fast %K and %D values based on the high, low, and close prices of the candles. EMA (Exponential Moving Average): Calculates the exponential moving average for the high, close, and low prices with a time period of 5. ADX (Average Directional Index): Calculates the average directional index. The populate_indicators() function is responsible for calculating these indicators and adding them to the input dataframe. The populate_buy_trend() function populates the "buy" column of the dataframe based on the following conditions: The open price is below the EMA low. The fast %K crosses above the fast %D. The fast %K and fast %D values are both below 30. The ADX value is above 30. The populate_sell_trend() function populates the "sell" column of the dataframe based on the following conditions: The open price is equal to or above the EMA high. Either the fast %K or the fast %D crosses above 70. These buy and sell signals are used to determine the entry and exit points for trades when backtesting the strategy.
The stoploss is set at -0.25, indicating the maximum acceptable loss before triggering a sell signal.
The ticker interval is set to 5 minutes, indicating that the strategy operates on 5-minute candlestick data.
The strategy uses the following indicators: Stochastic Fast: Calculates the fast %K and %D values based on the high, low, and close prices of the candles. EMA (Exponential Moving Average): Calculates the exponential moving average for the high, close, and low prices with a time period of 5. ADX (Average Directional Index): Calculates the average directional index. The populate_indicators() function is responsible for calculating these indicators and adding them to the input dataframe. The populate_buy_trend() function populates the "buy" column of the dataframe based on the following conditions: The open price is below the EMA low. The fast %K crosses above the fast %D. The fast %K and fast %D values are both below 30. The ADX value is above 30. The populate_sell_trend() function populates the "sell" column of the dataframe based on the following conditions: The open price is equal to or above the EMA high. Either the fast %K or the fast %D crosses above 70. These buy and sell signals are used to determine the entry and exit points for trades when backtesting the strategy.
stoploss: -0.25 timeframe: 5m hash(sha256): 0464eff84ee0de18a7c2f53625afcff6c8d232bd826d9762df6263141a9949e1
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last change: 2022-07-11 13:18:34