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The LookaheadStrategy is a trading strategy implemented in Python for backtesting purposes. Here's a short description of what the strategy does:
The strategy uses moving averages to determine buy and sell signals. It calculates two exponential moving averages (EMAs) for the buy signal: a fast EMA and a slow EMA.
Similarly, it calculates two EMAs for the sell signal: a fast EMA and a slow EMA.
To populate the indicators, the strategy uses the TA-Lib library, specifically the SMA function to calculate the moving averages based on the specified time periods (buy_params["buy_fast"], buy_params["buy_slow"], sell_params["sell_fast"], sell_params["sell_slow"]).
In the populate_buy_trend function, the strategy checks for a crossover above between the shifted fast EMA and the shifted slow EMA multiplied by a buy push factor. If this condition is met, the strategy sets the "buy" signal to 1 for the corresponding data points. In the populate_sell_trend function, the strategy checks for a crossover below between the shifted fast EMA and the shifted slow EMA multiplied by a sell push factor. If this condition is met, the strategy sets the "sell" signal to 1 for the corresponding data points. The strategy also defines buy and sell hyperspace parameters, a return on investment (ROI) table, a stop loss value, and trailing stop parameters. The timeframe for the strategy is set to "5m" (5 minutes). Overall, the LookaheadStrategy uses moving averages and crossover signals to generate buy and sell signals for trading.
Similarly, it calculates two EMAs for the sell signal: a fast EMA and a slow EMA.
To populate the indicators, the strategy uses the TA-Lib library, specifically the SMA function to calculate the moving averages based on the specified time periods (buy_params["buy_fast"], buy_params["buy_slow"], sell_params["sell_fast"], sell_params["sell_slow"]).
In the populate_buy_trend function, the strategy checks for a crossover above between the shifted fast EMA and the shifted slow EMA multiplied by a buy push factor. If this condition is met, the strategy sets the "buy" signal to 1 for the corresponding data points. In the populate_sell_trend function, the strategy checks for a crossover below between the shifted fast EMA and the shifted slow EMA multiplied by a sell push factor. If this condition is met, the strategy sets the "sell" signal to 1 for the corresponding data points. The strategy also defines buy and sell hyperspace parameters, a return on investment (ROI) table, a stop loss value, and trailing stop parameters. The timeframe for the strategy is set to "5m" (5 minutes). Overall, the LookaheadStrategy uses moving averages and crossover signals to generate buy and sell signals for trading.
startup_candle_count : 50 Recursive Analysis found no issues while using 50 startup_candle_count
Biased Entry Signals:
20Biased Exit Signals:
3
stoploss: -0.194 timeframe: 5m hash(sha256): 3c8208d2fa4eb8221646b1b34781204866773e712e6ad017aa9094c045c6139a indicators: sell_ema_slow buy_ema_slow sell_ema_fast buy_ema_fast
No similar strategies found. (based on used indicators)
last change: 2023-07-05 08:46:11