İşletme Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/403
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Article Citation - WoS: 9Citation - Scopus: 15Stock Returns and Volatility: Empirical Evidence From Fourteen Countries(Routledge Journals, Taylor & Francis Ltd, 2005) Balaban, E; Bayar, AThis is a pioneering effort to test in 14 countries the relationship between stock market returns and their forecast volatility derived from the symmetric and asymmetric conditional heteroscedasticity models. Both weekly and monthly returns and their volatility are investigated. An out-of-sample testing methodology is employed using volatility forecasts instead of investigating the relation between stock returns and their in-sample volatility estimates. Expected volatility is derived from the ARCH(p), GARCH(1, 1), GJR-GARCH(1, 1) and EGARCH(1, 1) forecast models. Expected volatility is found to have a significant negative or positive effect on country returns in a few cases. Unexpected volatility has a negative effect on weekly stock returns in six to seven countries and on monthly returns in nine to eleven countries depending on the volatility forecasting model. However, it has a positive effect on weekly and monthly returns in none of the countries investigated. It is concluded that the return variance may not be an appropriate measure of risk.Article Citation - WoS: 18Citation - Scopus: 18Estimation in Bivariate Nonnormal Distributions With Stochastic Variance Functions(Elsevier Science Bv, 2008) Tiku, Moti L.; Islam, M. Qamarul; Sazak, Hakan S.Data sets in numerous areas of application can be modelled by symmetric bivariate nonnormal distributions. Estimation of parameters in such situations is considered when the mean and variance of one variable is a linear and a positive function of the other variable. This is typically true of bivariate t distribution. The resulting estimators are found to be remarkably efficient. Hypothesis testing procedures are developed and shown to be robust and powerful. Real life examples are given. (C) 2007 Elsevier B.V. All rights reserved.