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The "titanium" strategy is a trading strategy implemented as a class called "titanium" that extends the "IStrategy" class. It consists of three main functions: "populate_indicators," "populate_buy_trend," and "populate_sell_trend."
The "populate_indicators" function adds various technical analysis (TA) indicators to the given DataFrame. These indicators include the Stochastic Oscillator (slowk), Relative Strength Index (RSI), Fisher Transform of RSI (fisher_rsi), Bollinger Bands lower band (bb_lowerband), Parabolic SAR (sar), and Hammer Candlestick Pattern (CDLHAMMER).
The purpose of adding these indicators is to provide information about price trends, volatility, and potential reversal patterns.
The "populate_buy_trend" function populates the buy signal for the given DataFrame based on certain conditions.
It uses the crossed_above function from the qtpylib library to check if the value of a fast key (buy_fast_key) has crossed above a calculated value derived from a slow key (buy_slow_key) multiplied by a vertical push factor (buy_vertical_push). If the conditions are met, the 'buy' column in the DataFrame is set to 1. The "populate_sell_trend" function populates the sell signal for the given DataFrame based on certain conditions. It checks if the Parabolic SAR value (sar) is greater than the closing price and if the Fisher Transform of RSI (fisher_rsi) is greater than 0.3. If both conditions are true, the 'sell' column in the DataFrame is set to 1. Overall, the strategy uses a combination of TA indicators and specific conditions to generate buy and sell signals for trading.
The purpose of adding these indicators is to provide information about price trends, volatility, and potential reversal patterns.
The "populate_buy_trend" function populates the buy signal for the given DataFrame based on certain conditions.
It uses the crossed_above function from the qtpylib library to check if the value of a fast key (buy_fast_key) has crossed above a calculated value derived from a slow key (buy_slow_key) multiplied by a vertical push factor (buy_vertical_push). If the conditions are met, the 'buy' column in the DataFrame is set to 1. The "populate_sell_trend" function populates the sell signal for the given DataFrame based on certain conditions. It checks if the Parabolic SAR value (sar) is greater than the closing price and if the Fisher Transform of RSI (fisher_rsi) is greater than 0.3. If both conditions are true, the 'sell' column in the DataFrame is set to 1. Overall, the strategy uses a combination of TA indicators and specific conditions to generate buy and sell signals for trading.
stoploss: -0.1 timeframe: 5m hash(sha256): ad1579edcc025c53e9eb998e4ebe1430586f1aaad835db6e9707086eb4123dd0 indicators: slowk lower fisher_rsi close rsi bb_lowerband CDLHAMMER sar
No similar strategies found. (based on used indicators)
last change: 2024-04-29 02:58:27