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The Test4 strategy is a trading strategy implemented in Python. Here's a brief description of what the strategy does:
It uses various technical indicators such as exponential moving averages (ema), simple moving averages (sma), and the SIG_dip_1 indicator. The strategy defines buy and sell conditions based on these indicators and other criteria.
In the populate_indicators function, the strategy calculates three exponential moving averages: ema_9, ema_21, and ema_200.
The strategy also calculates the SIG_dip_1 indicator, which measures the percentage difference between the highest price in the last two periods and the closing price.
The populate_buy_trend function sets the "buy" signal to 1 when the SIG_dip_1 value is greater than a predefined threshold (buy_sig_dip_1) and the volume is greater than zero. The populate_sell_trend function sets the "sell" signal to 1 when the ema_9 crosses below the ema_21, the closing price is above the ema_200, and the volume is greater than zero. The strategy also includes additional parameters for buy and sell hyperspace optimization, ROI table for defining the desired return on investment, stop-loss and trailing stop settings, and custom stop-loss options. It requires at least 210 candles before producing valid signals. Please note that this is a simplified explanation, and there may be additional complexities or considerations in the full implementation.
In the populate_indicators function, the strategy calculates three exponential moving averages: ema_9, ema_21, and ema_200.
The strategy also calculates the SIG_dip_1 indicator, which measures the percentage difference between the highest price in the last two periods and the closing price.
The populate_buy_trend function sets the "buy" signal to 1 when the SIG_dip_1 value is greater than a predefined threshold (buy_sig_dip_1) and the volume is greater than zero. The populate_sell_trend function sets the "sell" signal to 1 when the ema_9 crosses below the ema_21, the closing price is above the ema_200, and the volume is greater than zero. The strategy also includes additional parameters for buy and sell hyperspace optimization, ROI table for defining the desired return on investment, stop-loss and trailing stop settings, and custom stop-loss options. It requires at least 210 candles before producing valid signals. Please note that this is a simplified explanation, and there may be additional complexities or considerations in the full implementation.
startup_candle_count : 1000 Recursive Analysis found no issues while using 1000 startup_candle_count
stoploss: -0.344 timeframe: 5m hash(sha256): 07dc622a95a81425cf6049861072b873e92b420d349178143a5a47b0290a5ee5 indicators: ema_21 volume ema_200 close ema_9 SIG_dip_1
No similar strategies found. (based on used indicators)
last change: 2023-07-01 14:07:02