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The TDSequentialStrategy is a trading strategy that utilizes various technical indicators to generate buy and sell signals. Here's a breakdown of its key components:
populate_indicators: This function adds multiple technical indicators to the given DataFrame. The indicators include RSI (Relative Strength Index), ADX (Average Directional Index), MFI (Money Flow Index), MACD (Moving Average Convergence Divergence), SAR (Stop and Reverse), TEMA (Triple Exponential Moving Average), Stochastic Fast, Bollinger Bands, and other derived indicators.
exceed_high and exceed_low: These columns are initially set to False.
They are used to track whether the price exceeds certain thresholds based on the strategy's rules.
seq_buy and seq_sell: These columns calculate buy and sell signals based on the closing price compared to its value four time periods ago. They also assign a sequential count to each signal. Looping through the DataFrame: The strategy iterates through each row of the DataFrame to determine whether the exceed_high and exceed_low conditions are met based on the sequential buy and sell signals. If the count reaches 8 or 9, the strategy checks whether the price has exceeded previous highs or lows. populate_buy_trend: This function populates the buy signal column in the DataFrame. It sets the value to 1 when specific conditions are met, such as the price exceeding previous lows, the RSI being above a certain threshold, and the price being below the lower Bollinger Band. populate_sell_trend: This function populates the sell signal column in the DataFrame. It sets the value to 1 when conditions such as the price exceeding previous highs, the RSI being above a certain threshold, and the price being above the upper Bollinger Band are met. Overall, the TDSequentialStrategy combines multiple technical indicators and sequential analysis to generate buy and sell signals based on specific conditions.
exceed_high and exceed_low: These columns are initially set to False.
They are used to track whether the price exceeds certain thresholds based on the strategy's rules.
seq_buy and seq_sell: These columns calculate buy and sell signals based on the closing price compared to its value four time periods ago. They also assign a sequential count to each signal. Looping through the DataFrame: The strategy iterates through each row of the DataFrame to determine whether the exceed_high and exceed_low conditions are met based on the sequential buy and sell signals. If the count reaches 8 or 9, the strategy checks whether the price has exceeded previous highs or lows. populate_buy_trend: This function populates the buy signal column in the DataFrame. It sets the value to 1 when specific conditions are met, such as the price exceeding previous lows, the RSI being above a certain threshold, and the price being below the lower Bollinger Band. populate_sell_trend: This function populates the sell signal column in the DataFrame. It sets the value to 1 when conditions such as the price exceeding previous highs, the RSI being above a certain threshold, and the price being above the upper Bollinger Band are met. Overall, the TDSequentialStrategy combines multiple technical indicators and sequential analysis to generate buy and sell signals based on specific conditions.
stoploss: -0.1 timeframe: 15m hash(sha256): 12d48d2247b03d0938d2652eff9b054527041be78c7b2c6af500439d035e0171 indicators: sell upper tema close mfi bb_lowerband bb_percent seq_sell fastk macdhist seq_buy fastd sar high macdsignal mid bb_width exceed_high macd buy adx lower bb_middleband rsi bb_upperband low exceed_low
No similar strategies found. (based on used indicators)
last change: 2023-06-27 10:21:09