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Table 1 Time series forecasting techniques

From: A novel hybrid model based on Hodrick–Prescott filter and support vector regression algorithm for optimizing stock market price prediction



Specific techniques

Qualitative techniques

Useful when historical data are scare or non-existent

Delphi technique

Scenario writing

Visionary forecast

Historic analogies

Causal techniques

Useful when historical data are available for both the dependent (forecast) and the independent variables

Regression models

Econometric models

Leading indicators

Correlation methods

Time Series techniques

Useful when historical data exists for forecast variable and the data exhibits a pattern

Moving average

Autoregression models

Seasonal regression models

Exponential smoothing

Trend projection

Cointegration models