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A generalized ARFIMA process with Markov-switching fractional differencing parameter

Tsay, Wen-jen (contributor); Härdle, Wolfgang (contributor) - 2007

We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the DLV algorithm proposed. This algorithm...

Persistent link: https://www.econbiz.de/10003633683

A Note on Optimal Linear Filtering, Smoothing and Trend Extraction for Processes with Unit Roots with Drift

Thomakos, Dimitrios D. - 2008

In this note I show that the method proposed in Thomakos (2008) for optimal linear filtering, smoothing and trend extraction for a unit root process can be applied with no changes when a drift parameter is added to the process. The method in the aforementioned paper is based on Singular Spectrum...

Persistent link: https://www.econbiz.de/10012724772

Long Memory in UK Real GDP, 1851-2013 : An ARFIMA-FIGARCH Analysis

Caporale, Guglielmo Maria - 2014

volatility (d=0.80) is also confirmed …

Persistent link: https://www.econbiz.de/10013051843

A Generalized ARFIMA Process with Markov-Switching Fractional Differencing Parameter

Tsay, Wen-Jen - 2017

Persistent link: https://www.econbiz.de/10012966243

Optimal Linear Filtering, Smoothing and Trend Extraction for Processes with Unit Roots and Cointegration

Thomakos, Dimitrios D. - 2008

In this paper I propose a novel optimal linear filter for smoothing, trend and signal extraction for time series with a unit root. The filter is based on the Singular Spectrum Analysis (SSA) methodology, takes the form of a particular moving average and is different from other linear filters...

Persistent link: https://www.econbiz.de/10014219324

Revealing Cluster Structures Based on Mixed Sampling Frequencies

Rho, Yeonwoo; Liu, Yun; Ahn, Hie Joo - 2020

This paper proposes a new nonparametric mixed data sampling (MIDAS) model and develops a framework to infer clusters in a panel regression with mixed frequency data. The nonparametric MIDAS estimation method is more flexible and substantially simpler to implement than competing approaches. We...

Persistent link: https://www.econbiz.de/10014048748

Long memory persistence in the factor of Implied volatility dynamics

Härdle, Wolfgang Karl; Mungo, Julius - 2007

The volatility implied by observed market prices as a function of the strike and time to maturity form an Implied … Volatility Surface (IVS). Practical applications require reducing the dimension and characterize its dynamics through a small … investigating long range dependence in the factor loadings series. Our result reveals that shocks to volatility persist for a very …

Persistent link: https://www.econbiz.de/10010274129

Value-at-risk and expected shortfall when there is long range dependence

Härdle, Wolfgang Karl; Mungo, Julius - 2008

characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …

Persistent link: https://www.econbiz.de/10010274140

Out-of-sample Comparison of Copula Specifications in Multivariate Density Forecasts

Diks, Cees; Panchenko, Valentyn; van Dijk, Dick - 2008

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation...

Persistent link: https://www.econbiz.de/10010325942

Bootstrap joint prediction regions

Wolf, Michael; Wunderli, Dan - 2013

Many statistical applications require the forecast of a random variable of interest over several periods into the future. The sequence of individual forecasts, one period at a time, is called a path forecast, where the term path refers to the sequence of individual future realizations of the...

Persistent link: https://www.econbiz.de/10010316854