The Turn-of-the-Month-Effect: Evidence from Periodic Generalized Autoregressive Conditional Heteroskedasticity (PGARCH) Model

Eleftherios Giovanis ()

International Journal of Business and Economic Sciences Applied Research (IJBESAR), 2014, vol. 7, issue 3, 43-61

Abstract: 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.

Keywords: Calendar Effects; GARCH; Periodic-GARCH; Stock Returns; Turn of the Month Effect (search for similar items in EconPapers)
JEL-codes: C22 G14 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:tei:journl:v:7:y:2014:i:3:p:43-61

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