This paper proposes efficient estimators of risk measures in a semiparametric GARCH model defined through moment constraints. Moment constraints are often used to identify and estimate the mean and variance parameters and are however discarded when estimating error quantiles. In order to prevent...

The objective of this paper is to evaluate the behaviour of Nigerian Stock Exchange (NSE) sector indices. Specifically, the paper analyzes the returns correlation, serial correlation and heteroscedasticity on the NSE All-share Index, Banking Index, Consumer Goods Index, Oil & Gas Index, NSE 30...

Since the introduction of the autoregressive conditional heteroskedastic (ARCH) model in Engle (1982), numerous applications of this modeling strategy have already appeared. A common finding in many of these studies with high frequency financial or monetary data concerns the presence of an...

Among the harmful effects of inflation, the negative consequences of inflation volatility are of particular concern. These include higher risk premia, hedging costs and unforeseen redistribution of wealth. This paper presents panel estimations for a sample of OECD countries which suggest that...

We lay out an empirical and a theoretical model to analyze the effects of non-fundamental exchange rate volatility on economic activity and welfare. In the first part of the paper, the GARCH-SVARmodel is applied to measure empirically the effect of the conditional exogenous exchange rate...

This article employed the ARCH, GARCH and EGARCH models to model the oil price volatility and macroeconomic variables in South Africa for the period 1990Q1 to 2018Q2. The macroeconomic variables used in the study are GDP, inflation, interest rate and exchange rates. According to ARCH (1) and...

We show that the empirical process of the squared residuals of an ARCH(p) sequence converges in distribution 1,0 a Gaussirm process B(F(t)) +t f(t) e, where F is the distribution function of the squared innovations, f its derivative, {B(tl, 0 <; t>1} a Brownian bridge and e a normal random variable.