This study was conducted to explore the varying volatility of world rice price for the period 1961 to 2008 using monthly data. The paper provides estimates of two GARCH models, namely, GARCH and EGARCH which were used to capture the stochastic variation and asymmetries in the world rice price....

This paper discusses nonparametric kernel regression with the regressor being a \(d\)-dimensional \(\beta\)-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate \(\sqrt{n(T)h^{d}}\), where \(n(T)\) is...

This paper aims to use the local level models with GARCH and SV errors to predict Polish inflation. The series to be forecast, measured monthly, is consumer price index (CPI) in Poland during 1992-2008. We selected three forecasting models i.e. LL-GARCH(1,1) with Normal or Student errors and...

This paper is dedicated to research of level of profitability and risk in Russian stock market in the period of world crisis 2008-2009 Correlations of Russian stock market with the main world stock indices and prices of energy commodities are discussed Autocorrelation of returns is researched...

The volatility clustering frequently observed in financial/economic time series is often ascribed to GARCH and/or stochastic volatility models. This paper demonstrates the usefulness of re- conceptualizing the usual definition of conditional heteroscedasticity as the (h = 1) special case of...

The purpose of this paper is to test whether the Lebanese foreign exchange rate market is weak form efficient by studying the stochastic behavior of six foreign currencies against the Lebanese pound on a daily basis. Efficiency requires that the data meet more than one condition. The first...

To accommodate the inhomogenous character of financial time series over longer time periods, standard parametric models can be extended by allow- ing their coeffcients to vary over time. Focusing on conditional heteroscedas- ticity models, we discuss various strategies to identify and estimate...

The Single Factor Model (SFMT) of stock returns in its simplest form, namely the one that assumes time-invariant beta and homoskedastic error has been found to be empirically inadequate.The beta coefficient and the error process exhibit signi��cant time-variation and dynamic...

In this paper we performed an analysis in order the make an evidence of GARCH modeling on the performances of trading rules applied for a stock market index. Our study relays on the overlap between econometrical modeling, technical analysis and a simulation computing technique. The nonlinear...

This paper investigates the implications of time-varying betas in factor models for stock returns. It is shown that a single-factor model (SFMT) with autoregressive betas and homoscedastic errors (SFMT-AR) is capable of reproducing the most important stylized facts of stock returns. An empirical...