On measuring volatility and the GARCH forecasting performance

By Emilio Barucci, Roberto Renò. 2002

94 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/889d12c286699a8584264ef97f7d38820650fd1a

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Citations in the corpus

A Fourier transform method for nonparametric estimation of multivariate volatility (2009, methodology): “The efficiency of the Fourier series procedure for computing and forecasting the integrated volatility has been analyzed in [12, 13, 21, 29, 38].”
Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility (2007, unknown): “…(e.g., Andreou & Ghysels, 2002; Areal & Taylor, 2002; Bollen & Inder, 2002; Corsi, Zumbach, Müller, & Dacorogna, 2001; Oomen, 2006), Fourier methods (Barucci & Reno, 2002; Malliavin & Mancino, 2002), or other kernel type estimators (e.g., Barndorff-Nielsen, Hansen, Lunde, & Shephard, 2006;…”
Measuring and modeling systematic risk in factor pricing models using high-frequency data (2003, background): “A large and rapidly growing literature has sought to better characterize the general impact of these effects along with practical ways in which best to deal with the complications that arise in specific applications for different markets (see e.g., Andersen et al., 2000; Andreou and Ghysels, 2002; B”
Return distributions and volatility forecasting in metal futures markets: Evidence from gold, silver, and copper (2011, unknown): “Reno and Barucci (2002) compare IVFT with realized volatility in a Monte Carlo study to generate latent instantaneous volatility, and they show that the IVFT method is superior to the realized volatility approach.”
NONPARAMETRIC ESTIMATION OF THE DIFFUSION COEFFICIENT OF STOCHASTIC VOLATILITY MODELS (2008, methodology): “…we prefer to use s 2 instead of x as the real variable+ 4+ Using different interpolation techniques we get a bias in the volatility measurement ~Barucci and Renò, 2002b!+ 5+ This value of d1 was found by minimizing the integrated square error between the generated and reconstructed trajectory,…”
On covariance estimation of non-synchronously observed diffusion processes (2005, background): “Indeed, some authors (for instance Barucci and Renò 2002) point out a potential bias caused by the linear interpolation adopted by the aforementioned paper by Andersen et al. (2001) on estimating volatilities.”
Variation, jumps, market frictions and high frequency data in financial econometrics (2005, unknown): “The performance of this Fourier estimator of QV is discussed by, for example, Barucci and Reno (2002b), Barucci and Reno (2002a), Kanatani (2004b), Precup and Iori (2005), Nielsen and Frederiksen (2005) and Kanatani (2004a) who carry out some extensive simulation and empirical studies of the…”
Realized Volatility: A Review (2008, unknown): “The authors considered three estimators: the realized variance, the estimator based on Fourier series (Malliavin and Macino (2002) and Barucci and Reno (2002a, 2002b)), and finally, the wavelet estimator of Høg and Lunde (2003). The main conclusion of the paper is that the Fourier estimator is prefe”