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Accelerating GARCH and score-driven models : optimality, estimation and forecasting

Blasques, Francisco F.; Gorgi, Paolo; Koopman, Siem Jan S.J. - 2017

of US inflation using a model with time-varying mean and variance; we report significant improvements in the forecasting …

Persistent link: https://www.econbiz.de/10011688512

Asymmetries in conditional mean and variance : modelling stock returns by asMA-asQGARCH

Brännäs, Kurt; Gooijer, Jan G. de - 2000

The asymmetric moving average model (asMA) is extended to allow forasymmetric quadratic conditional heteroskedasticity (asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We introduce a framework fortesting asymmetries in...

Persistent link: https://www.econbiz.de/10011303289

Score driven exponentially weighted moving average and value-at-risk forecasting

Lucas, André; Zhang, Xin - 2014

We present a simple new methodology to allow for time-variation in volatilities using a recursive updating scheme similar to the familiar RiskMetrics approach. It exploits the link between exponentially weighted moving average and integrated dynamics of score driven time varying parameter...

Persistent link: https://www.econbiz.de/10010384110

Score driven exponentially weighted moving averages and value-at-risk forecasting

Lucas, André; Zhang, Xin - 2015

A simple methodology is presented for modeling time variation in volatilities and other higher-order moments using a recursive updating scheme similar to the familiar RiskMetricsTM approach. We update parameters using the score of the forecasting distribution. This allows the parameter dynamics...

Persistent link: https://www.econbiz.de/10011332948

Forecasting value-at-risk with time-varying variance, skewnessn and kurtosis in an exponential weighted moving average framework

Gabrielsen, Alexandros; Zagaglia, Paolo; Kirchner, Axel; … - 2012 - This version: June 6, 2012

This paper provides an insight to the time-varying dynamics of the shape of the distribution of financial return series by proposing an exponential weighted moving average model that jointly estimates volatility, skewness and kurtosis over time using a modified form of the Gram-Charlier density...

Persistent link: https://www.econbiz.de/10011731521

Forecasting Energy Price Volatilities and Correlations : New Evidence From Fractionally Integrated Multivariate Garch Models

marchese, malvina - 2020

Energy price volatilities and correlations have been modeled extensively using short-memory multivariate GARCH models. This paper investigates the potential benefits from using multivariate fractionally integrated GARCH models from a forecasting and a risk management perspective. Several...

Persistent link: https://www.econbiz.de/10012840754

Forecasting Inflation with Gradual Regime Shifts and Exogenous Information

Hubrich, Kirstin - 2011

-mean autoregressive model can be used to describe characteristic features in inflation series. This implies that we decompose the … inflation process into a slowly moving nonstationary component and dynamic short-run fluctuations around it. An important … quantity to be forecast. This makes it possible to form a single model-based inflation forecast that also incorporates the …

Persistent link: https://www.econbiz.de/10013122536

Forecasting inflation with gradual regime shifts and exogenous information

González, Andrés; Hubrich, Kirstin; Teräsvirta, Timo - 2011

Persistent link: https://www.econbiz.de/10009238009

Forecasting inflation in Vietnam with univariate and vector autoregressive models

Tran Thanh Hoa - 2017

In this paper, I apply univariate and vector autoregressive (VAR) models to forecast inflation in Vietnam. To … properties of inflation in Vietnam. Then, I compute the pseudo out-of-sample root mean square error (RMSE) as a measure of … forecasting models from among the different candidates. I find that VAR_m2 is the best monthly model to forecast inflation in …

Persistent link: https://www.econbiz.de/10011606109

GARCH Models for Daily Stock Returns : Impact of Estimation Frequency on Value-at-Risk and Expected Shortfall Forecasts

Ardia, David - 2014

We analyze the impact of the estimation frequency - updating parameter estimates on a daily, weekly, monthly or quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily returns for constituents of the S&P 500 index. We assess the...

Persistent link: https://www.econbiz.de/10013064474