PINE LIBRARY
Forecasting
Actualizado
This Forecasting library has a couple of Novel and traditional approaches to forecasting stock prices.
Traditionally, it provides a basic ARIMA forecaster using simple autoregression, as well as a linear regression and quadratic regression channel forecaster.
Novel approaches to forecasting include:
1) A Moving Average based Forecaster (modelled after ARIMA), it is capable of forecasting based on a user selected SMA.
2) Z-Score Forecast: Forecasting based on Z-Score (example displayed in chart).
Library "Forecasting"
ARIMA_Modeller(src)
: Creates a generic autoregressive ARIMA model
Parameters:
src (float)
Returns: : arima_result, arima_ucl, arima_lcl, arima_cor, arima_r2, arima_err, y1, y2, y3, y0
machine_learning_regression(output, x1, x2, x3, x4, x5, show_statistics)
: Creates an automatic regression based forecast model (can be used for other regression operations) from a list of possible independent variables.
Parameters:
output (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
x5 (float)
show_statistics (bool)
Returns: : result, upper bound levels, lower bound levels, optional statitics table that displays the model parameters and statistics
time_series_linear_forecast(src, forecast_length, standard_deviation_extension_1, standard_deviation_extension_2)
: Creates a simple linear regression time series channel
Parameters:
src (float)
forecast_length (int)
standard_deviation_extension_1 (float)
standard_deviation_extension_2 (float)
Returns: : Linreg Channel
quadratic_time_series_forecast(src, forecast_length)
: Creates a simple quadratic regression time series channel
Parameters:
src (float)
forecast_length (int)
Returns: : Quadratic Regression Channel
moving_average_forecaster(source, train_time, ma_length, forecast_length, forecast_result, upper_bound_result, lower_bound_result)
: Creates an ARIMA style moving average forecaster
Parameters:
source (float)
train_time (int)
ma_length (int)
forecast_length (int)
forecast_result (float[])
upper_bound_result (float[])
lower_bound_result (float[])
Returns: : forecast_result, upper_bound_result, lower_bound_result, moving_average, ucl, lcl
zscore_forecast(z_length, z_source, show_alerts, forecast_length, show_forecast_table)
: Creates a Z-Score Forecast and is capable of plotting the immediate forecast via a Polyline
Parameters:
z_length (int)
z_source (float)
show_alerts (bool)
forecast_length (int)
show_forecast_table (bool)
Returns: : The export is void, it will export the Polyline forecast and the Z-forecast table if you enable it.
Traditionally, it provides a basic ARIMA forecaster using simple autoregression, as well as a linear regression and quadratic regression channel forecaster.
Novel approaches to forecasting include:
1) A Moving Average based Forecaster (modelled after ARIMA), it is capable of forecasting based on a user selected SMA.
2) Z-Score Forecast: Forecasting based on Z-Score (example displayed in chart).
Library "Forecasting"
ARIMA_Modeller(src)
: Creates a generic autoregressive ARIMA model
Parameters:
src (float)
Returns: : arima_result, arima_ucl, arima_lcl, arima_cor, arima_r2, arima_err, y1, y2, y3, y0
machine_learning_regression(output, x1, x2, x3, x4, x5, show_statistics)
: Creates an automatic regression based forecast model (can be used for other regression operations) from a list of possible independent variables.
Parameters:
output (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
x5 (float)
show_statistics (bool)
Returns: : result, upper bound levels, lower bound levels, optional statitics table that displays the model parameters and statistics
time_series_linear_forecast(src, forecast_length, standard_deviation_extension_1, standard_deviation_extension_2)
: Creates a simple linear regression time series channel
Parameters:
src (float)
forecast_length (int)
standard_deviation_extension_1 (float)
standard_deviation_extension_2 (float)
Returns: : Linreg Channel
quadratic_time_series_forecast(src, forecast_length)
: Creates a simple quadratic regression time series channel
Parameters:
src (float)
forecast_length (int)
Returns: : Quadratic Regression Channel
moving_average_forecaster(source, train_time, ma_length, forecast_length, forecast_result, upper_bound_result, lower_bound_result)
: Creates an ARIMA style moving average forecaster
Parameters:
source (float)
train_time (int)
ma_length (int)
forecast_length (int)
forecast_result (float[])
upper_bound_result (float[])
lower_bound_result (float[])
Returns: : forecast_result, upper_bound_result, lower_bound_result, moving_average, ucl, lcl
zscore_forecast(z_length, z_source, show_alerts, forecast_length, show_forecast_table)
: Creates a Z-Score Forecast and is capable of plotting the immediate forecast via a Polyline
Parameters:
z_length (int)
z_source (float)
show_alerts (bool)
forecast_length (int)
show_forecast_table (bool)
Returns: : The export is void, it will export the Polyline forecast and the Z-forecast table if you enable it.
Notas de prensa
v2Added:
auto_trend_lookback_value(src)
: Finds the strongest correlation to time in trend from 50 to 850 candles back
Parameters:
src (float)
Returns: : trend length interval
Notas de prensa
v3Biblioteca Pine
Siguiendo fielmente el espíritu TradingView, el autor ha publicado este código Pine como una biblioteca de código abierto, permitiendo que otros programadores de Pine en nuestra comunidad lo utilicen de nuevo. ¡Olé por el autor! Puede utilizar esta biblioteca de forma privada o en otras publicaciones de código abierto, pero tenga en cuenta que la reutilización de este código en una publicación se rige por las Normas internas.
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