Strategy: hacker_noon
Downloaded: 20220112
Stoploss: -0.305

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Average Overall
Trades/DayRejected Signals
Ninja Score: 46
The "HackerNoon" strategy is a trading strategy that uses various technical indicators to generate buy and sell signals for backtesting. Here's a breakdown of what the strategy does: Import necessary libraries: The strategy imports numpy, pandas, and other required libraries for data manipulation and technical analysis. Define ROI and stop-loss: The strategy sets the minimum return on investment (ROI) for different time periods.

It also sets a stop-loss level to limit potential losses.

Informative pairs: This function returns an empty list, indicating that the strategy doesn't require any additional pairs for analysis.

Populate indicators: This function calculates and adds several technical indicators to the dataframe, including Stochastic Oscillator (STOCH), Relative Strength Index (RSI), Bollinger Bands, Fisher Transform, SAR (Stop and Reverse), and CDLHAMMER candlestick pattern. Populate buy trend: This function identifies buy opportunities based on the conditions that the RSI is below 20 and the lower Bollinger Band is above the closing price. Populate sell trend: This function identifies sell opportunities based on the condition that the Fisher Transform indicator is above a certain threshold. The strategy uses these buy and sell signals to determine when to enter or exit a trade during backtesting. Keep in mind that this is a simplified description, and the actual implementation may involve more complex logic and considerations.

startup_candle_count : 20
bb_lowerband: -0.021%
sar: -0.277%
stoploss: -0.305
timeframe: 5m
hash(sha256): 7d211d67074a109b4496732fa3162420a31c0e83c1496c929f4ce923964a8908
slowk rsi bb_lowerband CDLHAMMER sar

No similar strategies found. (based on used indicators)

last change: 2024-04-02 01:00:58