The NDrop strategy is a trading strategy that utilizes various technical analysis (TA) indicators to generate buy and sell signals. In the populate_indicators method, the strategy calculates and adds the following indicators to the input DataFrame:
Money Flow Index (MFI)
Simple Moving Average (SMA)
Moving Average Convergence Divergence (MACD)
Stochastic Fast Indicator (STOCHF)
Relative Strength Index (RSI)
Fisher Transform of RSI (fisher_rsi)
Bollinger Bands (bb_upperband, bb_middleband, bb_lowerband)
Bollinger Bands Gain (bb_gain)
Exponential Moving Averages (ema5, ema10, ema50, ema100)
Parabolic SAR (sar)
In the populate_entry_trend method, the strategy defines the conditions for entering a trade. These conditions include:
MFI being below a specified value (buy_mfi)
Fisher RSI being less than a specified value (buy_fisher)
Close price being below the lower Bollinger Band (bb_lowerband)
Previous candles' close prices being lower than their respective open prices
The drop percentage between the previous candle's open and the current close being greater than or equal to a specified value (buy_drop)
If any of these conditions are met, the buy column in the DataFrame is set to 1 for the corresponding row.
In the populate_exit_trend method, the strategy populates the sell column in the DataFrame.
In this particular implementation, all rows have a sell value of 0, indicating no specific sell signal is generated based on the TA indicators.
Overall, the NDrop strategy combines multiple TA indicators to identify potential buying opportunities based on specific conditions, while not providing a specific exit signal based on the given implementation.