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Conditional Heteroskedasticity and Global Stock Return Distributions
Author(s) -
Errunza Vihang,
Hogan Kedreth,
Kini Omesh,
Padmanabhan Prasad
Publication year - 1994
Publication title -
financial review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.621
H-Index - 47
eISSN - 1540-6288
pISSN - 0732-8516
DOI - 10.1111/j.1540-6288.1994.tb00399.x
Subject(s) - heteroscedasticity , econometrics , arch , stock (firearms) , economics , autoregressive conditional heteroskedasticity , autoregressive model , financial economics , sample (material) , stock market , statistics , volatility (finance) , mathematics , geography , context (archaeology) , archaeology , chemistry , chromatography
This paper investigates conditional return distribution characteristics for seven developed markets (DMs) and eight emerging markets (EMs). With the exception of Germany and Japan, the behavior of monthly returns of DM sample countries is similar to that of the U.S. In contrast, EM returns exhibit a substantially greater degree of serial correlation and a higher incidence of autoregressive conditional heteroskedasticity (ARCH) in monthly data. Aggregation of returns into two‐ and three‐month holding periods decreases the significance of the ARCH effects. However, there are cross‐sectional differences in the rate at which ARCH effects become insignificant. The findings of ARCH in monthly returns sample data is attributed to differences in the rate at which information arrives and is transmitted into prices in each market.