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The "TemaMaster2" strategy is a backtesting strategy for trading cryptocurrencies. Here is a brief description of what the strategy does:
The strategy uses various technical indicators such as CMO (Chande Momentum Oscillator), TEMA (Triple Exponential Moving Average), Bollinger Bands, STDDEV (Standard Deviation), MA (Moving Average), and COEFFV (Coefficient of Variation). The strategy is designed to trade on a 1-minute timeframe.
It has a predefined minimal ROI (Return on Investment) table, which specifies the expected returns at different stages of the trade.
It also has an optimal stop loss value, which determines the maximum acceptable loss before exiting a trade.
The strategy uses a trailing stop, which adjusts the stop loss level as the trade moves in a profitable direction. It has options to use a sell signal and sell only for profit, as well as ignore ROI if a buy signal is generated. The strategy defines an "informative_pairs" function, which specifies additional pair/interval combinations to be cached from the exchange for informational purposes. The "populate_indicators" function calculates and adds various technical indicators to the input DataFrame. The "populate_buy_trend" function determines the buy signal based on the defined conditions, including the crossover between TEMA and the lower Bollinger Band and a positive CMO value. The "populate_sell_trend" function determines the sell signal based on the crossover of CMO below certain thresholds. Overall, the strategy aims to generate profits by identifying potential buying opportunities based on the defined technical indicators and selling when certain sell signals are triggered.
It has a predefined minimal ROI (Return on Investment) table, which specifies the expected returns at different stages of the trade.
It also has an optimal stop loss value, which determines the maximum acceptable loss before exiting a trade.
The strategy uses a trailing stop, which adjusts the stop loss level as the trade moves in a profitable direction. It has options to use a sell signal and sell only for profit, as well as ignore ROI if a buy signal is generated. The strategy defines an "informative_pairs" function, which specifies additional pair/interval combinations to be cached from the exchange for informational purposes. The "populate_indicators" function calculates and adds various technical indicators to the input DataFrame. The "populate_buy_trend" function determines the buy signal based on the defined conditions, including the crossover between TEMA and the lower Bollinger Band and a positive CMO value. The "populate_sell_trend" function determines the sell signal based on the crossover of CMO below certain thresholds. Overall, the strategy aims to generate profits by identifying potential buying opportunities based on the defined technical indicators and selling when certain sell signals are triggered.
Unable to parse Traceback (Logfile Exceeded Limit)
stoploss: -0.117 timeframe: 1m hash(sha256): c775b70dc6f1a666af1e7e6b473a2f6e3a703f4fe76f8b6df559c8f3029df647 indicators: upper mid lower stake_currency CMO23 bb_middleband bb_upperband bb_lowerband MA CMO TEMA COEFFV STDDEV
No similar strategies found. (based on used indicators)
last change: 2024-08-02 10:10:16