The Gumbo1 strategy is a trading strategy that uses various indicators to generate buy and sell signals. Here is a brief description of what the strategy does:
The populate_indicators function calculates and adds several indicators to the input dataframe, including:
EWO (Elder's Force Index Wilder)
EMA (Exponential Moving Average)
T3 averages with different periods (T3_1, T3_2, ..., T3_n)
Bollinger Bands with a time period of 40 (bb_lowerband_40, bb_middleband_40, bb_upperband_40)
Stochastic indicators with different periods (stoch_1, stoch_2, ..., stoch_n)
The populate_buy_trend function checks specific conditions for a buy signal and assigns a value of 1 to the 'buy' column in the dataframe if the conditions are met. The conditions include:
EWO being less than a specified low value
The 1-hour Bollinger Bands' middle band being greater than or equal to the 1-hour T3 average
The T3 average with a specified period being less than or equal to the EMA
The populate_sell_trend function checks specific conditions for a sell signal and assigns a value of 1 to the 'sell' column in the dataframe if the conditions are met.
The conditions include:
The stochastic indicator with a specified period being greater than a specified high value
The T3 average with a specified period being greater than or equal to the 40-period Bollinger Bands' middle band
Additionally, the strategy uses custom functions to calculate some of the indicators:
The T3Average function calculates a T3 average based on exponential moving averages (EMAs) with different lengths.
The emadif function calculates the difference between two EMAs and normalizes it by dividing by the 'low' price.
The stoch function calculates the stochastic indicator and then applies a simple moving average (SMA) to the average of the 'slow_k' and 'slow_d' values. Please note that the code provided is a partial implementation, and additional code or context may be required to fully understand the strategy.