This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications. The results show that the series was non stationary which resulted from the presence of a unit root in it. ...

This article applied GARCH model instead AR or ARMA model to compare with the standard BP and SVM in forecasting of the four international including two Asian stock markets indices.These models were evaluated on five performance metrics or criteria. Our experimental results showed the superiority of SVM and GARCH models, compared to the standard BP in forecasting of the four international stock...

The paper estimate 1-day Value at Risk (VaR) taking into consideration the financial integration of Indian capital market (BSE-SENSEX and NSE-NIFTY) with other global indicators and its own volatility using daily returns covering the period January 2003 to December 2009. The paper specifies a generalized autoregressive conditional heteroscedasticity (GARCH) framework to model the phenomena of v...

Bu çalışmada Covid-19 pandemi sürecinin Türkiye’ de seçilen bazı ekonomik değişkenlerin oynaklıkları üzerindeki etkileri vektör otoregresyon (VAR) modeli ile incelenmiştir. amaçla 2020:03-2022:08 dönemi için BIST100 fiyat endeksi, döviz kuru, ham petrol ölüm ve vaka sayıları kullanılmıştır. Ekonomik GARCH türü modellerin koşullu değişen varyansları elde edilmiştir. endeksi ARMA(1,1)-EGARCH(1,1)...

Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) are of special interest, since they enable richer dynamics (e.g. contrarian or cyclical), provide greater robustness to jumps and outliers, and guarantee the positivity of volatility. The latter is not guaranteed in ordinary ARCH models, in particular when additional exogenous and/or predetermined variables (“X”) are inc...

This paper focuses on the performance of various GARCH models in terms of their ability of delivering volatility forecasts for stock return data. Volatility forecasts obtained from a variety of mean and variance specifications in GARCH models are compared to a proxy of actual volatility calculated using daily data. In-sample tests suggest that a regression of volatility estimates on actual vola...

This paper investigates the asymptotic theory for a vector autoregressive moving average–generalized autoregressive conditional heteroskedasticity ~ARMAGARCH! model+ The conditions for the strict stationarity, the ergodicity, and the higher order moments of the model are established+ Consistency of the quasimaximum-likelihood estimator ~QMLE! is proved under only the second-order moment conditi...

A simple iterative algorithm for nonparametric 1rst-order GARCH modelling is proposed. This method o4ers an alternative to 1tting one of the many di4erent parametric GARCH speci1cations that have been proposed in the literature. A theoretical justi1cation for the algorithm is provided and examples of its application to simulated data from various stationary processes showing stochastic volatili...