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The "vulcanhopt" strategy is a trading strategy implemented in Python. Here is a short description of what the strategy does:
The strategy uses various technical indicators such as SMA (Simple Moving Average), RSI (Relative Strength Index), and Stochastic Oscillator to make buy and sell decisions. It defines certain parameters for the strategy, such as the stop loss percentage, the timeframe for analyzing price data, and the minimum return on investment (ROI) required for selling.
The strategy populates indicators by calculating the RSI and its moving average, as well as multiple SMA values.
It also calculates the Stochastic Oscillator values.
For the buy signal, the strategy checks if the current closing price is above the specified SMA value, the SMA is increasing over the previous three periods, the RSI is above its moving average, and the RSI is above a certain threshold value. For the sell signal, the strategy checks if the Stochastic Oscillator values are above a specified threshold, there is a bearish crossover between the slowk and slowd lines, or there is a lower low in the price compared to the previous 100 periods. The strategy assigns a "buy" or "sell" signal to the corresponding rows in the dataframe based on the conditions mentioned above. Overall, the strategy aims to identify buying opportunities when certain conditions related to moving averages, RSI, and Stochastic Oscillator are met, and it aims to sell when the Stochastic Oscillator indicates overbought conditions or when there is a lower low in the price.
The strategy populates indicators by calculating the RSI and its moving average, as well as multiple SMA values.
It also calculates the Stochastic Oscillator values.
For the buy signal, the strategy checks if the current closing price is above the specified SMA value, the SMA is increasing over the previous three periods, the RSI is above its moving average, and the RSI is above a certain threshold value. For the sell signal, the strategy checks if the Stochastic Oscillator values are above a specified threshold, there is a bearish crossover between the slowk and slowd lines, or there is a lower low in the price compared to the previous 100 periods. The strategy assigns a "buy" or "sell" signal to the corresponding rows in the dataframe based on the conditions mentioned above. Overall, the strategy aims to identify buying opportunities when certain conditions related to moving averages, RSI, and Stochastic Oscillator are met, and it aims to sell when the Stochastic Oscillator indicates overbought conditions or when there is a lower low in the price.
stoploss: -0.25 timeframe: 5m hash(sha256): f024c7e22a5ac13e5e5f45d7041229f010c978d5b64291a9cb5773034319bf26
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last change: 2022-08-09 19:37:46