Traditional linear regression and time-series models often fail to produce accurate forecasts due to inherent nonlinearities and structural instabilities, which characterize financial markets and challenge the Efficient Market Hypothesis. Machine learning techniques are becoming widespread tools for return forecasting as they are capable of dealing efficiently with nonlinear modeling. An evolutionary programming approach based on genetic algorithms is introduced in order to estimate and fine-tune the parameters of the STAR-class models, as opposed to conventional techniques. Using a hybrid method we employ trading rules that generate excess returns for the Eurozone southern periphery stock markets, over a long out-of-sample period after the introduction of the Euro common currency. Our results may have important implications for market efficiency and predictability. Investment or trading strategies based on the proposed approach may allow market agents to earn higher returns.
Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets
BEKIROS S;
2015-01-01
Abstract
Traditional linear regression and time-series models often fail to produce accurate forecasts due to inherent nonlinearities and structural instabilities, which characterize financial markets and challenge the Efficient Market Hypothesis. Machine learning techniques are becoming widespread tools for return forecasting as they are capable of dealing efficiently with nonlinear modeling. An evolutionary programming approach based on genetic algorithms is introduced in order to estimate and fine-tune the parameters of the STAR-class models, as opposed to conventional techniques. Using a hybrid method we employ trading rules that generate excess returns for the Eurozone southern periphery stock markets, over a long out-of-sample period after the introduction of the Euro common currency. Our results may have important implications for market efficiency and predictability. Investment or trading strategies based on the proposed approach may allow market agents to earn higher returns.File | Dimensione | Formato | |
---|---|---|---|
Evolutionary-based return forecasting with nonlinear STAR models.pdf
Accesso riservato
Tipo di file:
PDF EDITORIALE
Dimensione
590.36 kB
Formato
Adobe PDF
|
590.36 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.