SmaCrossStrat

The strategy implemented in the provided code is called "SmaCrossStrat" (Simple Moving Average Cross Strategy). Here's a brief description of what the strategy does: The strategy is designed to backtest trading signals based on the crossover of simple moving averages (SMAs). The timeframe used for analysis is daily (1d), and the strategy requires at least 25 candles of historical data before generating valid signals.

The strategy defines a set of target return on investment (ROI) values for different holding periods.

These ROI values determine the take profit levels for trades.

A stop loss of -10% is set, meaning that if the trade goes against the position by 10%, it will be automatically sold. Trailing stop loss is disabled, meaning that the stop loss level is fixed and not adjusted as the trade moves in favor of the position. The strategy uses buy signals generated by the crossover of two SMAs: a quick SMA (buy_quick_sma) and a slow SMA (buy_slow_sma). The specific values for these SMAs can be optimized within the range of 5 to 60. Similarly, the strategy uses sell signals generated by the crossover of two SMAs: a quick SMA (sell_quick_sma) and a slow SMA (sell_slow_sma). These SMA values can also be optimized within the range of 5 to 60. The strategy populates these indicators by calculating the SMAs for different periods and storing them in the dataframe. In the populate_buy_trend method, the strategy checks for a bullish crossover of the buy_quick_sma and buy_slow_sma to generate a buy signal. In the populate_sell_trend method, the strategy checks for a bearish crossover of the sell_quick_sma and sell_slow_sma to generate a sell signal. This strategy aims to capture potential trading opportunities based on the crossover of different SMAs. It provides flexibility to optimize the SMA periods for both buying and selling signals, allowing for customization and adaptation to different market conditions.