Measuring and modeling systematic risk in factor pricing models using high-frequency data

By Tim Bollerslev, B. Y. Zhang. 2003

121 citations recorded by the source corpus.

Subfields: Finance

View Paper: https://www.semanticscholar.org/paper/d5b43ff7766d05e5c43769e091a72b07d24fb97a

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Citations in the corpus

Realized Beta: Persistence and Predictability (2004, background): “…trading problem so that the market return is nearly uncorrelated and the individual stock return series are approximately serially uncorrelated and orthogonal to all but the first lagged and leading 15-minute market 2 See also the more recent discussion in Bollerslev and Zhang (2003).”
Marketing and Firm Value: Metrics, Methods, Findings, and Future Directions (2009, unknown): “Bollerslev and Zhang (2003) use high-frequency data (e.g., five-minute intervals) to find a sign reversal in these two factors.”
Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns (2014, unknown): “Bollerslev and Zhang (2003), Barndorff-Nielsen and Shephard (2004a), and Andersen, Bollerslev, Diebold, and Wu (2005, 2006), in particular, have previ- ously explored the use of high-frequency data and the asymptotic notion of increasingly finer sampled returns over fixed time intervals for more…”
Jumps and Betas: A New Framework for Disentangling and Estimating Systematic Risks (2010, unknown): “2 (2006), Bollerslev and Zhang (2003), Barndorff-Nielsen and Shephard (2004a) and Hooper et al. (2006) among others, have all explored new procedures for measuring and forecasting period-by-period betas based on so-called realized variation measures constructed from the summation of squares and…”
Covariance measurement in the presence of non-synchronous trading and market microstructure noise (2011, unknown): “Recent empirical application of the RCLL estimator can be found in Bollerslev and Zhang (2003) and Bandi and Russell (2005).”
HAR Modeling for Realized Volatility Forecasting (2012, unknown): “To solve this problem, various approaches have been proposed in the literature: incorporate lead and lag cross returns in the estimator ([70], [32],[22], [9]), avoid any synchronization by directly using tick-by-tick data ([42],[54],[53],[67],[71],[72],[35]), multivariate realized kernel ([11]),…”
REALIZED BETA GARCH: A MULTIVARIATE GARCH MODEL WITH REALIZED MEASURES OF VOLATILITY (2012, methodology): “Bollerslev and Zhang (2003) carry out a large scale estimation of the Fama-French three-factor model using high-frequency (5-minute) data on 6,400 stocks over a period of 7 years.”
Forecasting Volatility Using High-Frequency Data (2011, background): “In Bollerslev and Zhang (2003) and Andersen, Bollerslev, Diebold and Wu (2005, 2006) systematic risk is measured by the so-called realized beta that is derived from the realized covariance matrix.”
Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use? (2008, unknown): “Third, Andersen et al. (2003) suggest that with more and more assets eventually a factor model will be needed, see Andersen et al. (2001a) and Hafner et al. (2006) for additional motivation and discussion and Bollerslev and Zhang (2003) for an application using the Fama-French three-factor model.”
Adaptive estimation of continuous-time regression models using high-frequency data (2017, background): “In financial applications estimators for β from high-frequency data have been considered by Bollerslev and Zhang (2003), BarndorffNielsen and Shephard (2004), Andersen et al. (2006), Mykland ✩ We thank the editor (Oliver Linton), the associate editor and three anonymous referees for many helpful…”