Artikel
The Turn-of-the-Month-Effect: Evidence from Periodic Generalized Autoregressive Conditional Heteroskedasticity (PGARCH) Model
The current study examines the turn of the month effect on stock returns in 20 countries. This will allow us to explore whether the seasonal patterns usually found in global data; America, Australia, Europe and Asia. Ordinary Least Squares (OLS) is problematic as it leads to unreliable estimations; because of the autocorrelation and Autoregressive Conditional Heteroskedasticity (ARCH) effects existence. For this reason Generalized GARCH models are estimated. Two approaches are followed. The first is the symmetric Generalized ARCH (1,1) model. However, previous studies found that volatility tends to increase more when the stock market index decreases than when the stock market index increases by the same amount. In addition there is higher seasonality in volatility rather on average returns. For this reason the Periodic-GARCH (1,1) is estimated. The findings support the persistence of the specific calendar effect in 19 out of 20 countries examined.
- Language
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Englisch
- Bibliographic citation
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Journal: International Journal of Economic Sciences and Applied Research ; ISSN: 1791-3373 ; Volume: 7 ; Year: 2014 ; Issue: 3 ; Pages: 43-61 ; Kavala: Eastern Macedonia and Thrace Institute of Technology
- Classification
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Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Information and Market Efficiency; Event Studies; Insider Trading
- Subject
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Calendar Effects
GARCH
Periodic-GARCH
Stock Returns
Turn of the Month Effect
- Event
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Geistige Schöpfung
- (who)
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Giovanis, Eleftherios
- Event
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Veröffentlichung
- (who)
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Eastern Macedonia and Thrace Institute of Technology
- (where)
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Kavala
- (when)
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2014
- Handle
- Last update
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10.03.2025, 11:44 AM CET
Data provider
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Object type
- Artikel
Associated
- Giovanis, Eleftherios
- Eastern Macedonia and Thrace Institute of Technology
Time of origin
- 2014
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