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Long-term dependence in stock returns
Barkoulas, John T. - In: Economics letters 53 (1996) 3, pp. 253-259
Persistent link: https://www.econbiz.de/10001216270
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Density prediction of stock index returns using GARCH models : frequentist or Bayesian estimation?
Hoogerheide, Lennart F.; Ardia, David; Corré, Nienke - In: Economics letters 116 (2012) 3, pp. 322-325
Persistent link: https://www.econbiz.de/10009674398
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An ARCH model without intercept
Hafner, Christian M.; Preminger, Arie - In: Economics letters 129 (2015), pp. 13-17
Persistent link: https://www.econbiz.de/10011421858
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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
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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
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On estimating market microstructure noise variance
Dong, Yingjie; Tse, Yiu Kuen - In: Economics letters 150 (2017), pp. 59-62
Persistent link: https://www.econbiz.de/10011762850
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Time-varying predictability of the long horizon equity premium based on semiparametric regressions
Yu, Deshui; Li, Chen; Li, Luyang - In: Economics letters 224 (2023), pp. 1-6
Persistent link: https://www.econbiz.de/10014307887
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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
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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/10012545165
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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