업데이트됨
Forecasting
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.
릴리즈 노트
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
릴리즈 노트
v3
Check out the new Website!
merlintrades.net
Get access to:
- Indicators
- Merlin Trading Software
- Discord
- Documentation
merlintrades.net
Get access to:
- Indicators
- Merlin Trading Software
- Discord
- Documentation
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.
Check out the new Website!
merlintrades.net
Get access to:
- Indicators
- Merlin Trading Software
- Discord
- Documentation
merlintrades.net
Get access to:
- Indicators
- Merlin Trading Software
- Discord
- Documentation
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.