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The YoyoActionZoneStrategy is a trading strategy that uses various indicators to generate buy and sell signals for trading. Here's a breakdown of what the strategy does:
It calculates several indicators based on the provided dataframe, including exponential moving averages (ema_fast and ema_slow), relative strength index (rsi), and moving average convergence divergence (macd). It determines bullish and bearish conditions based on the macd values.
It identifies different color zones (green, blue, yellow, brown, and red) based on specific conditions related to the bearish state and the relationships between the close price and the exponential moving averages.
It calculates stop-loss levels (sl1 and sl2) based on the average true range (atrFast and atrSlow).
It sets up additional columns in the dataframe to track trading signals and trail the stop-loss levels. It defines specific conditions for buy and sell signals, including the use of previous values and specific relationships between the indicators and the close price. It iterates through the dataframe to calculate the trail2 values, which are used for trailing the stop-loss levels. It determines the long, preBuy, and short signals based on the bullish and bearish conditions from the macd. It defines the greenLine based on a condition involving the close price and the trail2 value. It populates the buy trend by identifying specific conditions for buying, including the presence of long signals, green zones, and the greenLine condition. It populates the sell trend by identifying specific conditions for selling, including the presence of short signals, the absence of the greenLine condition, and the presence of the red color zone. Overall, the strategy combines multiple indicators and conditions to generate buy and sell signals, taking into account the relationships between different indicators and the current market conditions.
It identifies different color zones (green, blue, yellow, brown, and red) based on specific conditions related to the bearish state and the relationships between the close price and the exponential moving averages.
It calculates stop-loss levels (sl1 and sl2) based on the average true range (atrFast and atrSlow).
It sets up additional columns in the dataframe to track trading signals and trail the stop-loss levels. It defines specific conditions for buy and sell signals, including the use of previous values and specific relationships between the indicators and the close price. It iterates through the dataframe to calculate the trail2 values, which are used for trailing the stop-loss levels. It determines the long, preBuy, and short signals based on the bullish and bearish conditions from the macd. It defines the greenLine based on a condition involving the close price and the trail2 value. It populates the buy trend by identifying specific conditions for buying, including the presence of long signals, green zones, and the greenLine condition. It populates the sell trend by identifying specific conditions for selling, including the presence of short signals, the absence of the greenLine condition, and the presence of the red color zone. Overall, the strategy combines multiple indicators and conditions to generate buy and sell signals, taking into account the relationships between different indicators and the current market conditions.
Biased Entry Signals:
4
stoploss: -0.1 timeframe: 4h hash(sha256): 0ad326eda6e897b74f4afbc2a392e6f66d1291d20aea6ed23b36055b5cd15008 indicators: long close preSell brown bearish trail2 preBuy ema_fast red sl1 blue sl2 short yellow macd green bullish greenLine_last rsi greenLine ema_slow
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last change: 2023-07-05 08:23:04