On the use of high frequency measures of volatility in MIDAS regressions
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Publication:726593
DOI10.1016/j.jeconom.2016.04.012zbMath1431.62468OpenAlexW3122728420MaRDI QIDQ726593
Publication date: 12 July 2016
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: http://papers.econ.ucy.ac.cy/RePEc/papers/03-16.pdf
Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70)
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Cites Work
- Long-run risk-return trade-offs
- Predicting volatility: getting the most out of return data sampled at different frequencies
- Volatility puzzles: a simple framework for gauging return-volatility regressions
- The VIX, the variance premium and stock market volatility
- On the definition, stationary distribution and second order structure of positive semidefinite Ornstein-Uhlenbeck type processes
- Multivariate supOU processes
- Regression models with mixed sampling frequencies
- Subsampling realised kernels
- Realized volatility forecasting and market microstructure noise
- Estimating stochastic volatility diffusion using conditional moments of integrated volatility
- Temporal aggregation of volatility models
- Two singular diffusion problems
- Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics
- On stationarity and ergodicity of the bilinear model with applications to GARCH models
- Temporal Aggregation of Garch Processes
- Stationarity and Ergodicity for an Affine Two-Factor Model
- Realized Beta: Persistence and Predictability
- Estimating Volatility in the Presence of Market Microstructure Noise: A Review of the Theory and Practical Considerations
- Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
- The Distribution of Realized Exchange Rate Volatility
- THE MULTIVARIATE supOU STOCHASTIC VOLATILITY MODEL
- Power Variation and Time Change
- Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics
- A Tale of Two Time Scales