Discord_5_emacrossover

The emacrossover strategy is a trading strategy that uses exponential moving averages (EMAs) to generate buy and sell signals. Here's a breakdown of how the strategy works: The strategy uses four EMA indicators: buy-fastMA, buy-slowMA, sell-fastMA, and sell-slowMA. These indicators are calculated using the ta.EMA function from the talib library.

In the populate_indicators method, the EMA indicators are calculated for the given dataframe using the specified time periods (buy_fastema, buy_slowema, sell_fastema, sell_slowema).

The calculated indicators are added as columns to the dataframe.

The populate_buy_trend method is responsible for determining the buy signals based on the EMA crossover. If the buy-fastMA is greater than the buy-slowMA, it generates a buy signal by setting the 'buy' column of the corresponding row in the dataframe to 1. Similarly, the populate_sell_trend method determines the sell signals. If the sell-fastMA is less than the sell-slowMA, it generates a sell signal by setting the 'sell' column of the corresponding row in the dataframe to 1. The strategy also defines hyperparameters (buy_fastema, buy_slowema, sell_fastema, sell_slowema) that can be optimized during backtesting. These parameters control the time periods used for calculating the EMA indicators. It specifies a minimal return on investment (ROI) table and a stop loss value (minimal_roi, stoploss) for risk management. The strategy is designed to be used on 15-minute timeframe data (timeframe = '15m'). Overall, the emacrossover strategy aims to capture buy signals when the short-term EMA is above the long-term EMA and sell signals when the short-term EMA is below the long-term EMA.