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Strategy: Dyna_opti
Downloaded: 20220211
Stoploss: -0.288
The Dyna_opti strategy is a trading strategy implemented as a class in Python. It extends the IStrategy class. Here's a short description of what the strategy does: The strategy populates various technical indicators on the input dataframe, such as Bollinger Bands, Average True Range (ATR), Rate of Change (ROC), Relative Momentum Index (RMI), SSL Channels, and others.

It merges additional informative dataframes with the main dataframe for enhanced analysis.

In the buy signal section, the strategy defines several conditions for triggering a buy signal, including price and indicator relationships.

The sell signal section currently doesn't populate any sell signals. There is a custom stop-loss implementation that checks various conditions, such as the rate of change (ROC) and trade duration, to determine if a stop-loss should be triggered. The strategy also provides dynamic ROI functionality, allowing for customizable returns on investment (ROI) based on different conditions and indicators. Note: The code provided seems to be incomplete and contains some variables that are not defined. Please ensure that all necessary dependencies and variable definitions are included for the strategy to work correctly.

stoploss: -0.288
timeframe: 5m
hash(sha256): b04a36f48cec5fd4a2149895857953f8e22bc6c59cecca48ebbbf9e37268f60d
indicators:
sell upper active_trade rmifast custom_stop
close tail bb_lowerband dynamic_roi bbdelta
date candleuptrend date ssldir buy_params
mp candleup volume price_side rmidncount
rmi ssl candle any closedelta
rmiuptrend date roc mastreak date
sbc streakroc candleuptrend lower upper
both none rmi pcclowerband streakbocount
ssldir mid rocmp date sroc
rmislow price adr 1dlow sell_params
atr sroc lower roc date
rmiuptrend date rmislow rmidn roc
time any bb_middleband pccupperband rmiup
1dhigh bb_upperband r

No similar strategies found. (based on used indicators)

last change: 2024-01-26 08:53:25