Strategy: CofiBitStrategy_4
Downloaded: 20230425
Stoploss: -0.25
The CofiBitStrategy is a trading strategy implemented in Python using the Freqtrade library. It is designed for backtesting trading strategies on financial data. Here is a short description of what the strategy does: The strategy uses technical indicators to make buy and sell decisions based on the given dataframe of financial data.

The minimal_roi attribute specifies the desired return on investment (ROI) for the strategy at different price levels.

For example, it aims for a 5% ROI when the price reaches 40, 6% ROI at 30, 7% ROI at 20, and 10% ROI at 0.

The stoploss attribute sets the desired stop loss for the strategy at -0.25, indicating a 25% loss tolerance. The ticker_interval attribute defines the interval at which the strategy operates. In this case, it is set to '5m', indicating a 5-minute interval. The populate_indicators function calculates various technical indicators, such as stochastic oscillator (STOCH), exponential moving average (EMA), and average directional index (ADX), based on the provided dataframe. The populate_buy_trend function determines the buy signal based on specific conditions. It checks if the opening price is below the EMA low, if the fast %K line crosses above the fast %D line, if both %K and %D are below 30, and if the ADX value is above 30. If these conditions are met, a buy signal is generated. The populate_sell_trend function determines the sell signal based on specific conditions. It checks if the opening price is above the EMA high or if either the %K or %D line crosses above 70. If these conditions are met, a sell signal is generated. Overall, the CofiBitStrategy aims to generate profitable buy and sell signals using technical indicators and predefined ROI and stop loss levels.

stoploss: -0.25
timeframe: 5m
hash(sha256): f015ff3ba5319dacfdcfc1eb52ddc93ace0b8cd10566be415de54b71af501955
ema_close adx ema_high open ema_low
fastd fastk

No similar strategies found. (based on used indicators)

last change: 2024-01-23 18:39:33