نتایج جستجو برای: regressive conditional heteroskedactisity garch
تعداد نتایج: 65938 فیلتر نتایج به سال:
exchange rate and national income of countries trading with each other are among the most important factors affecting each country's trade. considering the political and economic ties between iran and venezuela in recent years, the goal of this paper was to investigate the effect of exchange rate volatility on exports of iran to venezuela. data used in this research include annual data for...
In this paper, we consider the problem of optimal estimation of a time-varying positive definite matrix from a collection of noisy measurements. We assume that this positive definite matrix evolves according to an unknown GARCH (generalized auto-regressive conditional heteroskedasticity) model whose parameters must be estimated from experimental data. The main difficulty here, compared against ...
This article develops a numerical method to price American-style Asian option in the context of the generalized autoregressive conditional heteroscedasticity (GARCH) asset return process. The development is based on dynamic programming coupled with the replacement of the normally distributed variable with a binomial one and the whole procedure is under the locally risk-neutral valuation relatio...
We measure global real and nominal macroeconomic uncertainty and analyze its impact on individual countries’ macroeconomic performance. Global uncertainty is measured through the conditional variances of global factors in inflation and output growth, estimated from a bivariate dynamic factor model with GARCH errors. The impact of global uncertainty is measured by including the conditional varia...
We study portfolio optimization of four major cryptocurrencies. Our time series model is a generalized autoregressive conditional heteroscedasticity (GARCH) with multivariate normal tempered stable (MNTS) distributed residuals used to capture the non-Gaussian cryptocurrency return dynamics. Based on model, we optimize in terms Foster-Hart risk. Those sophisticated techniques are not yet documen...
This paper examines the behaviour of European option price (Duan (1995)) and the Black-Scholes model bias when stock returns follow a GARCH (1,1) process. The GARCH option price is not preferenceneutral and depends on the unit risk premium (λ) as well as the two GARCH (1,1) process parameters (α1 , β1). In general, the GARCH option price does not seem overly sensitive to these parameters. Deep-...
We show how the ARMA-Power GARCH model for the conditional mean and variance can be adapted to analyze times series data showing asymmetry. Dynamics is introduced in the location and the dispersion parameters of skewed location-scale distributions using the same type of structure found in the conditional mean and in the conditional variance in the ARMA-APARCH model. We also propose a general dy...
The research of Kim and Schmidt (1993) is extended to examine the properties of asymmetric unit root tests in the presence of generalised autoregressive conditional heteroskedasticity (GARCH). Using Monte Carlo simulation, threshold autoregressive and momentum—threshold autoregressive asymmetric unit tests are shown to suffer greater size distortion than the original (implicitly symmetric) Dick...
This paper aims to investigate a Bayesian sampling approach to parameter estimation in the GARCH model with an unknown conditional error density, which we approximate by a mixture of Gaussian densities centered at individual errors and scaled by a common standard deviation. This mixture density has the form of a kernel density estimator of the errors with its bandwidth being the standard deviat...
Motivated by recent developments in light of the sub-prime and subsequent financial crisis we fit two different vector autoregressive generalized conditional heteroscedastic (VAR-GARCH) models to three financial indices with the aim of understanding the development of dependency structures between credit spreads and other macroeconomic variables. Our analysis includes daily quotes from June 200...
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