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The Scalp strategy is designed to generate a large number of potential buy signals and make small profits on each trade. It is recommended to have at least 60 parallel trades at any given time to cover unavoidable losses. The strategy focuses on selling based on return on investment (ROI) and has been backtested on the top 20 coins in 2022.
Here are the backtest results for different timeframes: Timeframe: 1d, Winrate: 50%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -2.39% Timeframe: 4h, Winrate: 67.3%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -9.18% Timeframe: 30m, Winrate: 67.8%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -25.41% Timeframe: 5m, Winrate: 77.5%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -63.49% Timeframe: 1m, Winrate: 77.5%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -93.14% The strategy can also be optimized using hyperopt, which is a hyperparameter optimization algorithm.
The optimized results for the 1m timeframe are as follows: Winrate: 46%, Average ROI: 0.54%, Average profit with stop loss: -33.63%, Total profit: 82.66% The strategy uses various indicators such as exponential moving averages (EMA), stochastic fast indicators, and average directional index (ADX).
It also includes Bollinger Bands for graphing purposes. The buy signals are generated when the price crosses below the EMA low, the ADX is above a certain threshold, and the stochastic indicators meet specific criteria. The sell signals occur when the price crosses above the EMA high or the stochastic indicators cross above certain values. Please note that the strategy's minimal ROI is set to 1.5% and the stop loss is set to -3%. The optimal timeframe for the strategy is 1 minute (1m).
Here are the backtest results for different timeframes: Timeframe: 1d, Winrate: 50%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -2.39% Timeframe: 4h, Winrate: 67.3%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -9.18% Timeframe: 30m, Winrate: 67.8%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -25.41% Timeframe: 5m, Winrate: 77.5%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -63.49% Timeframe: 1m, Winrate: 77.5%, Average ROI: 1%, Average profit with stop loss: -4.19%, Total profit: -93.14% The strategy can also be optimized using hyperopt, which is a hyperparameter optimization algorithm.
The optimized results for the 1m timeframe are as follows: Winrate: 46%, Average ROI: 0.54%, Average profit with stop loss: -33.63%, Total profit: 82.66% The strategy uses various indicators such as exponential moving averages (EMA), stochastic fast indicators, and average directional index (ADX).
It also includes Bollinger Bands for graphing purposes. The buy signals are generated when the price crosses below the EMA low, the ADX is above a certain threshold, and the stochastic indicators meet specific criteria. The sell signals occur when the price crosses above the EMA high or the stochastic indicators cross above certain values. Please note that the strategy's minimal ROI is set to 1.5% and the stop loss is set to -3%. The optimal timeframe for the strategy is 1 minute (1m).
stoploss: -0.03 timeframe: 1m hash(sha256): 7866f4386fb4090c1c0d109d091911dc5da7a00f4e1e72b309c3f3c8c70f8d5b indicators: upper ema_close adx lower mid ema_high close bb_middleband bb_upperband bb_lowerband open ema_low fastd fastk
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last change: 2023-07-05 16:06:35