Forecasting

1 gen 2024

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.

14 gen 2024

Note di rilascio

v2

Added:
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

14 gen 2024

Note di rilascio

v3