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The "GodStraNewFTX5000" strategy is a trading strategy implemented as a class. Here's a short description of what it does:
This strategy involves populating indicators and generating buy and sell signals based on specified conditions. The method "populate_indicators" is responsible for calculating default values of hyperoptable parameters and optimizing the strategy by calculating indicators for all time periods.
However, in this strategy, the specific indicators are calculated within the buy and sell strategy populator methods when needed.
The "populate_buy_trend" method populates the buy signals based on a set of conditions.
It takes input parameters such as buy indicators, buy crossed indicators, buy operators, and buy real numbers. For each set of indicators, it generates a condition using the "condition_generator" function and appends it to a list of conditions. If any conditions are met, the corresponding rows in the dataframe are marked as a buy signal. Similarly, the "populate_sell_trend" method populates the sell signals based on a set of conditions. It takes input parameters such as sell indicators, sell crossed indicators, sell operators, and sell real numbers. For each set of indicators, it generates a condition using the "condition_generator" function and appends it to a list of conditions. If any conditions are met, the corresponding rows in the dataframe are marked as a sell signal. Overall, this strategy aims to generate buy and sell signals based on specified indicator conditions, allowing for backtesting and evaluation of its effectiveness in trading scenarios.
However, in this strategy, the specific indicators are calculated within the buy and sell strategy populator methods when needed.
The "populate_buy_trend" method populates the buy signals based on a set of conditions.
It takes input parameters such as buy indicators, buy crossed indicators, buy operators, and buy real numbers. For each set of indicators, it generates a condition using the "condition_generator" function and appends it to a list of conditions. If any conditions are met, the corresponding rows in the dataframe are marked as a buy signal. Similarly, the "populate_sell_trend" method populates the sell signals based on a set of conditions. It takes input parameters such as sell indicators, sell crossed indicators, sell operators, and sell real numbers. For each set of indicators, it generates a condition using the "condition_generator" function and appends it to a list of conditions. If any conditions are met, the corresponding rows in the dataframe are marked as a sell signal. Overall, this strategy aims to generate buy and sell signals based on specified indicator conditions, allowing for backtesting and evaluation of its effectiveness in trading scenarios.
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stoploss: -1 timeframe: 4h hash(sha256): bf324e5cd6c2397ac5b47e5870db2652c9efda73a808b9e7a6352d65f8ed276d indicators: Momentum Indicators volume Statistic Functions Overlap Studies Pattern Recognition indicator_trend_sma crossed_indicator Price Transform indicator Volume Indicators sharp_indicator Cycle Indicators Volatility Indicators
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last change: 2024-07-27 08:32:17