The "SmoothScalp" strategy is designed for backtesting trading strategies on a website. Here is a short description of what the strategy does:
The strategy aims to generate multiple 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.
Key components of the strategy include: Minimal ROI: The strategy targets a minimal return on investment (ROI) of 0.01.
Stoploss: The optimal stoploss for the strategy is set at -0.5, indicating a maximum loss of 0.5%.
Timeframe: The strategy operates on a 1-minute timeframe, aiming for quick trades. Indicator Population: The strategy populates various technical indicators on the input dataframe, including exponential moving averages (EMA) for high, close, and low prices, stochastic indicators (fastk and fastd), average directional index (ADX), commodity channel index (CCI), relative strength index (RSI), money flow index (MFI), Bollinger Bands, and moving average convergence divergence (MACD). Grid Calculations: The strategy calculates grid parameters based on the highest and lowest prices in the input dataframe. Buy Trend: The strategy identifies buy signals based on conditions such as the open price being lower than the EMA low, ADX being above 30, MFI being below 30, fastk and fastd being below 30 and crossing above each other, and CCI being below -150. Sell Trend: The strategy identifies sell signals based on conditions such as the open price being higher than or equal to the EMA high, fastk or fastd crossing above 70, and CCI being above 150. The strategy aims to make small profits on each trade by capturing short-term price movements and relies on a combination of technical indicators to generate buy and sell signals.
Key components of the strategy include: Minimal ROI: The strategy targets a minimal return on investment (ROI) of 0.01.
Stoploss: The optimal stoploss for the strategy is set at -0.5, indicating a maximum loss of 0.5%.
Timeframe: The strategy operates on a 1-minute timeframe, aiming for quick trades. Indicator Population: The strategy populates various technical indicators on the input dataframe, including exponential moving averages (EMA) for high, close, and low prices, stochastic indicators (fastk and fastd), average directional index (ADX), commodity channel index (CCI), relative strength index (RSI), money flow index (MFI), Bollinger Bands, and moving average convergence divergence (MACD). Grid Calculations: The strategy calculates grid parameters based on the highest and lowest prices in the input dataframe. Buy Trend: The strategy identifies buy signals based on conditions such as the open price being lower than the EMA low, ADX being above 30, MFI being below 30, fastk and fastd being below 30 and crossing above each other, and CCI being below -150. Sell Trend: The strategy identifies sell signals based on conditions such as the open price being higher than or equal to the EMA high, fastk or fastd crossing above 70, and CCI being above 150. The strategy aims to make small profits on each trade by capturing short-term price movements and relies on a combination of technical indicators to generate buy and sell signals.
stoploss: -0.5 timeframe: 1m hash(sha256): 9732139cbe6894819d2d7042fc1183104038769d6bd74f18192b810541ad9555 indicators: upper ema_close close mfi bb_lowerband macdhist fastk open fastd high macdsignal mid ema_high cci macd ema_low adx lower bb_middleband rsi bb_upperband low
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last change: 2024-04-29 20:37:58