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GARCH models for daily stock returns : impact of estimation frequency on value-at-risk and expected shortfall forecasts

Ardia, David; Hoogerheide, Lennart - 2013

Persistent link: https://www.econbiz.de/10010191413

Forecasting stock market volatility conditional on macroeconomic conditions.

Becker, Ralf; Clements, Adam - National Centre for Econometric Research (NCER) - 2007

This paper presents a GARCH type volatility model with a time-varying unconditional volatility which is a function of … macroeconomic information. It is an extension of the SPLINE GARCH model proposed by Engle and Rangel (2005). The advantage of the … proposed here can lead to significantly improved volatility forecasts compared to traditional GARCH type volatility models. …

Persistent link: https://www.econbiz.de/10005416549

Day-of-the-week effect in the Nigerian stock market returns and volatility : does the distributional assumptions influence disappearance?

Osarumwense, Osabuohien-Irabor - In: European financial and accounting journal : EFAJ 10 (2015) 4, pp. 33-44

error distribution were incorporated in the GARCH (2,1) and EGARCH (2,1) models. Result reveals that day-of-the-week effects …

Persistent link: https://www.econbiz.de/10011471089

Modelling the Volatility-Return Trade-Off When Volatility May Be Nonstationary

Dahl, Christian M.; Iglesias, Emma M. - 2009

In this paper a new GARCH–M type model, denoted the GARCH-AR, is proposed. In particular, it is shown that it is … disturbance process. Importantly, the volatility in the GARCH-AR model enters the return function in terms of relative volatility … characterization of the stationarity properties of the GARCH-AR process by generalizing the results of Bougerol and Picard (1992b …

Persistent link: https://www.econbiz.de/10014199817

Modeling Stock Price Movements : Multifractality or Multifractionality?

Bianchi, Sergio - 2011

The scaling properties of two alternative fractal models recently proposed to characterize the dynamics of stock market prices are compared. The former is the Multifractal Model of Asset Return (MMAR) introduced in 1997 by Mandelbrot, Calvet and Fisher in three companion papers. The latter is...

Persistent link: https://www.econbiz.de/10013122371

Spot Variance Path Estimation and Its Application to High Frequency Jump Testing

Bos, Charles S. - 2009

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...

Persistent link: https://www.econbiz.de/10013153285

A Note on Bootstrapping Autoregression Under Nonstationary Volatility

Kourogenis, Nikolaos - 2012

In a recent article, Xu (2008) developed the asymptotic theory for autoregressions around a polynomial trend, under nonstationary volatility. In the same article, Xu proposed a set of t-tests for the regression coefficients and claimed that these tests are asymptotically standard normal. A...

Persistent link: https://www.econbiz.de/10013112126

Bootstrap score tests for fractional integration in heteroskedastic ARFIMA models, with an application to price dynamics in commodity spot and futures markets

Cavalierea, Giuseppe; Ørregard Nielsen, Morten; … - 2013 - 12-2013

We propose bootstrap implementations of the asymptotic Wald, likelihood ratio and Lagrange multiplier tests for the order of integration of a fractionally integrated time series. Our main purpose in doing so is to develop tests which are robust to both conditional and unconditional...

Persistent link: https://www.econbiz.de/10009743847

Inference on the long-memory properties of time series with non-stationary volatility

Demetrescu, Matei; Sibbertsen, Philipp - 2014

Many time series exhibit unconditional heteroskedasticity, often in addition to conditional one. But such time-varying volatility of the data generating process can have rather adverse effects when inferring about its persistence; e.g. unit root and stationarity tests possess null distributions...

Persistent link: https://www.econbiz.de/10010375374

Short patches of outliers, ARCH and volatility modeling

Franses, Philip Hans; Dijk, Dick van; Lucas, André - 1998

In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily data on 22 … exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is … significant effects on test outcomes. Our main empirical result is that we find spurious GARCH in about 40% of the cases, while in …

Persistent link: https://www.econbiz.de/10011284080