PINE LIBRARY
Forecasting
Updated
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.
Release Notes
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
Release Notes
v3Pine library
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