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The MultiMA_TSL3 strategy is a trading strategy implemented as a class in Python. It is used for backtesting trading strategies on a website. Here is a brief description of what the strategy does:
The strategy calculates several indicators and conditions to determine when to buy a particular asset.
It first populates indicators such as EWO (Elliott Wave Oscillator), RSI (Relative Strength Index), Heikin Ashi candles, and others using the input data.
It also calculates moving averages and their offsets based on user-defined parameters.
The strategy then applies various buy conditions based on the calculated indicators. These conditions include checks on TRIMA (Triangular Moving Average), ZEMA (Zero Lag Exponential Moving Average), HMA (Hull Moving Average), and other criteria such as price movements, volume, and RSI values. If these conditions are met, the strategy sets a buy signal for the asset. Additionally, the strategy incorporates live data handling, where it checks if the data is available and sets a flag accordingly. It also tracks custom information specific to each trading pair. The MultiMA_TSL3a class extends the MultiMA_TSL3 strategy and adds additional functionalities. It retrieves informative indicators from a 15-minute timeframe, merges them with the original dataframe, and drops unnecessary columns. The rest of the strategy remains the same. Overall, the strategy combines various technical indicators and conditions to generate buy signals for trading assets based on user-defined parameters and market conditions.
It first populates indicators such as EWO (Elliott Wave Oscillator), RSI (Relative Strength Index), Heikin Ashi candles, and others using the input data.
It also calculates moving averages and their offsets based on user-defined parameters.
The strategy then applies various buy conditions based on the calculated indicators. These conditions include checks on TRIMA (Triangular Moving Average), ZEMA (Zero Lag Exponential Moving Average), HMA (Hull Moving Average), and other criteria such as price movements, volume, and RSI values. If these conditions are met, the strategy sets a buy signal for the asset. Additionally, the strategy incorporates live data handling, where it checks if the data is available and sets a flag accordingly. It also tracks custom information specific to each trading pair. The MultiMA_TSL3a class extends the MultiMA_TSL3 strategy and adds additional functionalities. It retrieves informative indicators from a 15-minute timeframe, merges them with the original dataframe, and drops unnecessary columns. The rest of the strategy remains the same. Overall, the strategy combines various technical indicators and conditions to generate buy signals for trading assets based on user-defined parameters and market conditions.
stoploss: -0.15 timeframe: 5m hash(sha256): cab2292ebaedaa14c70302bfa83bc35e2aa252ee5aaa2a5ce60d3e6ba40e5c43
Was not able to fetch indicators from Strategyfile.
last change: 2022-07-02 19:54:08