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ARIMA Trend Forecaster

100 USD

Descargado demo: 211

Publicado: 23 noviembre 2017

Versión actual: 9.0

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ARIMA Trend Forecaster

Indicadores
Ilya Antipin
Versión: 9.0
Actualizado: 16 abril 2018
Activaciones: 5

The ARIMA Trend Forecaster indicator is designed for analyzing and forecasting the trend component of a financial instrument based on the integrated ARIMA autoregressive model. The ARIMA methodology aims at identifying the presence of unit roots and the order of time series integration. In financial markets, autoregressive models are used for working with price time series to predict future price points.

The ARIMA Trend Forecaster indicator using all the advantages of the ARIMA method allows to accurately forecast a trend component behavior and to see potential market entry points. The indicator can be used either separately or in combination with other trading indicators or systems to improve the overall results of trading.

Adjustable Parameters

start_bar - bar to calculate the forecast for;
arima_length - the length of the time series for the calculation of the ARIMA autoregressive model;
trend_indicator - indicator type (from 0 to 3)
trend_period - indicator period;
predict_length - the length of the forecast;
arima_p - the order of the autoregressive part of the model;
arima_d - the order of the integrated part of the model;
arima_q - the order of the moving average;
bfgs_iter - the number of iterations in root optimization by the BFGS method.

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Biwavelet is an indicator for harmonic forecast of the market based on one-dimensional wavelet transform functions. Wavelet transforms are one of the main tools of digital algorithmic trading. This is due to their ability to analyze and predict processes occurring in two independent basic dimensions - price and time. Wavelets have significant advantages over the Fourier transform, because wavelet transform allows evaluating not only the frequency spectrum of the price signal, but also the time a

50 USD

The Discrete wavelet transform indicator is an enhanced implementation of the numerical and functional analysis for MetaTrader 4, the discrete wavelet transform method (DWT). The specific feature of DWT is the way the wavelet is represented in the form of a discrete signal (sample). DWT is widely used for filtering and preliminary processing of data, for analyzing the state and making forecasts for the stock and currency markets, for recognizing patterns, processing and synthesizing various sign

100 USD

MultiTrendLines - мультивалютный индикатор для автоматизации графического анализа трендовых линий. Позволяет быстро выполнять трудоемкий анализ трендовой ситуации на рынке. Использует точные математические алгоритмы выделения ключевых точек рынка для извлечения трендовой струкртуры инструмента. За счет применения корреляционных сигналов можно улучшить симметричную оценку поведения инструмента. Включает в себя возможность точно задавать необходимый уровень глубины и угла трендовой линии. Основной

400 USD

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Versión 9.0 2018.04.16

Added parameter start_bar - bar to calculate the forecast for. This parameter allows testing the indicator on history data and finding the optimal parameters.

Versión 8.0 2017.12.26

Fixed the indicator re-calculation when updating the chart.