Skip to main content

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

Categories Application 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