Wordcloud
Strategy: SARCross
Downloaded: 20220513
Stoploss: 0
The SARCross strategy is a trading strategy that uses various technical indicators to generate buy and sell signals for a given dataset. In the populate_indicators method, the strategy calculates several technical indicators including ADX (Average Directional Index), PLUS_DM, PLUS_DI, MINUS_DM, MINUS_DI, RSI (Relative Strength Index), Fisher RSI, Stochastic Fast, MACD (Moving Average Convergence Divergence), MFI (Money Flow Index), Bollinger Bands, EMA (Exponential Moving Average), SAR (Stop and Reverse), and TEMA (Triple Exponential Moving Average). These indicators provide insights into market trends, momentum, volatility, and price levels.

The populate_buy_trend method populates the buy signal based on the calculated indicators.

It checks various conditions such as the ADX value, delta values of DM (Directional Movement), MFI value, Fisher RSI value, volume, and BB (Bollinger Bands) gain.

If these conditions are met, a buy signal is assigned to the corresponding data points. Similarly, the populate_sell_trend method populates the sell signal based on the indicators. It checks conditions such as the SAR and TEMA crossing above each other. Overall, the SARCross strategy aims to capture potential buying and selling opportunities in the market based on the calculated technical indicators.

stoploss: 0
timeframe: 5m
hash(sha256): 8ca6ee2dfb9a3e7e4651376da1a84a1cd43db0f97b734824f720edf4b18e431f
indicators:
upper tema close dm_delta bb_gain
mfi bb_lowerband bb_percent fastk macdhist
volume fastd dm_plus sar macdsignal
mid fisher_rsi bb_width di_plus fisher_rsi_norma
macd di_delta ema7 ema25 adx
lower bb_middleband rsi di_minus bb_upperband
dm_minus

Similar Strategies: (based on used indicators)

Strategy: BTCMACDCross, Similarity Score: 96.88%
Strategy: BTCMACDCross_2, Similarity Score: 96.88%
Strategy: MACDCross_2, Similarity Score: 96.88%
Strategy: SARCross_2, Similarity Score: 96.88%
Strategy: MACDTurn, Similarity Score: 93.75%
Strategy: MACDTurn_2, Similarity Score: 93.75%

last change: 2024-04-29 00:29:05