The ARIMA Trend Forecaster indicator is designed to analyze and predict the trend component of a financial instrument based on the application of the integrated ARIMA autoregression model. The peculiarity of the ARIMA methodology is to identify the presence of unit roots and the order of integration of the time series. In financial markets, autoregressive models are used when working with price time series to predict future price points.
The ARIMA Trend Forecaster indicator, which uses all the advantages of the ARIMA method, makes it possible to predict the behavior of the trend component with high accuracy and see potential points for entering the market. The indicator can be used either separately or in conjunction with other trading indicators or systems to increase the overall profitability of trading.
- start_bar – the bar for which the forecast is calculated;
- arima_length – length of the time series for calculating the ARIMA autoregression model;
- trend_indicator-indicator type (from 0 to 3)
- trend_period – indicator period;
- predict_length – the length of the forecast line;
- arima_p – order of the autoregressive part of the model;
- arima_d – order of the integrated part of the model;
- arima_q – order of the moving average;
- bfgs_iter – the number of iterations when optimizing the roots using the BFGS method.