You will be redirected to the original Strategy in 15 seconds.
The MultiMA_TSL strategy is a trading strategy that uses multiple indicators to determine buying conditions in the market. Here is a breakdown of its key components:
Indicators:
Exponential Weighted Oscillator (ewo)
Relative Strength Index (rsi) with different time periods (14, 4, 84, 112)
Heikin-Ashi candles with volume
pmax (maximum value of certain calculations)
Source calculation based on high, low, open, and close prices
pmax threshold calculation based on exponential moving average (EMA)
Heikin-Ashi transformation (HA) of the dataframe
Buy Trend Conditions:
The strategy evaluates various buy conditions using different indicators and offsets. Some of the key conditions include:
Buy offset based on TRIMA (Triangular Moving Average) indicator
Buy offset based on ZEMA (Zero Lag Exponential Moving Average) indicator
Buy offset based on HMA (Hull Moving Average) indicator with additional conditions on RSI values
The strategy also considers additional checks related to live data availability, price conditions, RSI values, and volume.
Sell Trend Conditions: The strategy does not specify any conditions for the sell trend.
It assigns a value of 0 to the 'sell' column in the dataframe.
Other Functions: The 'populate_indicators' function adds the required indicators to the dataframe and performs data preprocessing. The 'populate_buy_trend' function evaluates the buy conditions and updates the 'buy' column in the dataframe accordingly. The 'populate_sell_trend' function assigns a value of 0 to the 'sell' column in the dataframe. The code snippet after the class definition includes calculations for simple moving averages (sma1 and sma2) and the difference between them (smadif). Overall, the MultiMA_TSL strategy combines multiple indicators and conditions to generate buy signals in the market.
Sell Trend Conditions: The strategy does not specify any conditions for the sell trend.
It assigns a value of 0 to the 'sell' column in the dataframe.
Other Functions: The 'populate_indicators' function adds the required indicators to the dataframe and performs data preprocessing. The 'populate_buy_trend' function evaluates the buy conditions and updates the 'buy' column in the dataframe accordingly. The 'populate_sell_trend' function assigns a value of 0 to the 'sell' column in the dataframe. The code snippet after the class definition includes calculations for simple moving averages (sma1 and sma2) and the difference between them (smadif). Overall, the MultiMA_TSL strategy combines multiple indicators and conditions to generate buy signals in the market.
stoploss: -0.15 timeframe: 5m hash(sha256): ddb62da44a32d6d39f21129c0a85870672472c055539f32b97a7130413f2f5a8
Was not able to fetch indicators from Strategyfile.
last change: 2022-07-11 14:46:59