t he relationship between the price of oil and the level of economic activity is a fundamental empirical issue in macroeconomics. in this research, by using a multivariate garch-in-mean var, we try to investigate direct effects of uncertainty of oil price on macroeconomics of iran by using annually data from 1965 to 2013.results show that uncertainty about oil prices had a negative and signific...

Electricity is sensitive to extreme price events and spot volatility an inherent characteristic of competitive electricity markets. The purpose this article it model the realized in Brazil. Brazilian industry presents unique characteristics because varies a lot short period. So, we developed GARCH using 862 weekly observations understand four different market. We conclude that Brazil high risk ...

This paper considers the pricing of options when there are jumps in the pricing kernel and correlated jumps in asset returns and volatilities. Our model nests Duan’s GARCH option models where conditional returns are constrained to being normal, as well as extends Merton’s jump-diffusion model by allowing return volatility to exhibit GARCH-like behavior. Empirical analysis on the S&P 500 index r...

The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the ...

The skewness in physical distributions of equity index returns and the implied volatility skew in the risk neutral measure are subjects of extensive academic research. Much attention is now being focused on models that are able to capture time-varying conditional skewness and kurtosis. For this reason normal mixture GARCH(1,1) models have become very popular in financial econometrics. We introd...

This paper develops a closed-form option pricing formula for a spot asset whose variance follows a GARCH process. The model allows for correlation between returns of the spot asset and variance and also admits multiple lags in the dynamics of the GARCH process. The single-factor (one-lag) version of this model contains Heston’s (1993) stochastic volatility model as a diffusion limit and therefo...

In this paper we present several new findings on the NoVaS transformation approach for volatility forecasting introduced by Politis (2003a,b, 2007). In particular: (a) we present a new method for accurate volatility forecasting using NoVaS ; (b) we introduce a “timevarying” version of NoVaS and show that the NoVaS methodology is applicable in situations where (global) stationarity for returns f...

The present study aims at applying different methods i.e GARCH, EGARCH, GJRGARCH, IGARCH & ANN models for calculating the volatilities of Indian stock markets. Fourteen years of data of BSE Sensex & NSE Nifty are used to calculate the volatilities. The performance of data exhibits that, there is no difference in the volatilities of Sensex, & Nifty estimated under the GARCH, EGARCH, GJR GARCH, I...

It is well-known that causal forecasting methods that include appropriately chosen Exogenous Variables (EVs) very often present improved forecasting performances over univariate methods. However, in practice, EVs are usually difficult to obtain and in many cases are not available at all. In this paper, a new causal forecasting approach, called Wavelet Auto-Regressive Integrated Moving Average w...

The key problem for option pricing in Garch models is that the risk neutral distribution of the underlying is known in explicit form only one day ahead and not at maturity. This problem was solved in the HestonNandi model (1997), where it is possible to compute the characteristic function of the underlying by a recursive procedure and options can be priced by Inverse Fourier Transform, see Hest...