This paper empirically investigates the exchange rate effects of Iranian Rial against Dollar (Rial vs.US) on stock prices in Iran. The sample period for the study has been taken from March 20, 2004 to March 20, 2010 using daily nominal exchange rate of Rial /us and daily closing values of Tehran Stock Exchange. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model has been use...

this paper empirically investigates the exchange rate effects of iranian rial against dollar (rial vs.us) on stock prices in iran. the sample period for the study has been taken from march 20, 2004 to march 20, 2010 using daily nominal exchange rate of rial /us and daily closing values of tehran stock exchange. generalized autoregressive conditional heteroskedasticity (garch) model has been use...

the price volatility spillover effect indicates that price volatility in different markets can be mutually affected. the objective of the study is to analyze volatility price spillover effects on the vertical levels including input, wholesale and retail sale levels in the tehran beef supply chain. the multivariate generalized autoregressive conditional heteroskedastic (mvgarch) model was used b...

Inspired by the idea that regime switching may give rise to persistence that is observationally equivalent to a unit root, we derive a regime switching process that exhibits long memory. The feature of the process that generates long memory is a heavytailed duration distribution. Using this process for volatility, we obtain a regime switching stochastic volatility (RSSV) model that we "t to dai...

Beta-t-EGARCH models in which the dynamics of the logarithm of scale are driven by the conditional score are known to exhibit attractive theoretical properties for the t-distribution and general error distribution (GED). The generalized-t includes both as special cases. We derive the information matrix for the generalized-t and show that, when parameterized with the inverse of the tail index, i...

In financial modeling, it has been constantly pointed out that volatility clustering and conditional nonnormality induced leptokurtosis observed in high frequency data. Financial time series data are not adequately modeled by normal distribution, and empirical evidence on the non-normality assumption is well documented in the financial literature (details are illustrated by Engle (1982) and Bol...

We consider a class of semiparametric GARCH models with additive autoregressive components linked together by a dynamic coefficient. We propose estimators for the additive components and the dynamic coefficient based on spline smoothing. The estimation procedure involves only a small number of least squares operations, thus it is computationally efficient. Under regularity conditions, the propo...

volatility transmission means the connection between different markets in a way that volatility can be transmitted from one market to another. the volatility of oil price in global markets is one of the factors which influence the capital markets of the countries of which their economy is based on oil revenues. most of these markets have long-run memory characteristic which should be considered...

A series of GARCH models are investigated for the volatility of the Chinese equity data from the Shenzhen and Shanghai markets. There has been empirical evidence of volatility clustering, contrary to findings in previous studies. Each market contains different GARCH models which fit well. The models are used to test for a spill-over effect between the two Chinese markets, an example of volatili...

Volatility of a stock may incur a risk premium, leading to a positive correlation between volatility and returns. On the other hand the leverage effect, whereby negative returns increase volatility, acts in the opposite direction. We propose a reformulation and extension of the ARCH in Mean model, in which the logarithm of scale is driven by the score of the conditional distribution. This EGARC...