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Fractional integration and fat tails for realized covariance kernels and returns

Lucas, André; Opschoor, Anne - 2016 - This version: September 1, 2016

We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by appropriate distributional assumptions. The covariance...

Persistent link: https://www.econbiz.de/10011531139

Spot variance path estimation and its application to high frequency jump testing

Bos, Charles S.; Janus, Paweł; Koopman, Siem Jan - 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/10011379469

What do professional forecasters actually predict?

Nibbering, Didier; Paap, Richard; Wel, Michel van der - 2015

In this paper we study what professional forecasters actually explain. We use spectral analysis and state space modeling to decompose economic time series into a trend, a business-cycle, and an irregular component. To examine which components are captured by professional forecasters we regress...

Persistent link: https://www.econbiz.de/10011305773

Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil

Aastveit, Knut Are; Cross, Jamie; Dijk, Herman K. van - 2021

We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil …, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach …

Persistent link: https://www.econbiz.de/10012795319