dc.contributor.author | Andreou, Elena | en |
dc.creator | Andreou, Elena | en |
dc.date.accessioned | 2019-05-03T05:21:45Z | |
dc.date.available | 2019-05-03T05:21:45Z | |
dc.date.issued | 2016 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/47070 | |
dc.description.abstract | Many empirical studies link mixed data frequency variables such as low frequency macroeconomic or financial variables with high frequency financial indicators’ volatilities, especially within a predictive regression model context. The objective of this paper is threefold: First, we relate the standard Least Squares (LS) regression model with high frequency volatility predictors, with the corresponding Mixed Data Sampling Nonlinear LS (MIDAS-NLS) regression model (Ghysels et al., 2005, 2006), and evaluate the properties of the regression estimators of these models. We also consider alternative high frequency volatility measures as well as various continuous time models using their corresponding relevant higher-order moments to further analyze the properties of these estimators. Second, we derive the relative MSE efficiency of the slope estimator in the standard LS and MIDAS regressions, we provide conditions for relative efficiency and present the numerical results for different continuous time models. Third, we extend the analysis of the bias of the slope estimator in standard LS regressions with alternative realized measures of risk such as the Realized Covariance, Realized beta and the Realized Skewness when the true DGP is a MIDAS model. © 2016 Elsevier B.V. | en |
dc.language.iso | eng | en |
dc.source | Journal of Econometrics | en |
dc.subject | Bias | en |
dc.subject | Continuous time models | en |
dc.subject | Continuous time systems | en |
dc.subject | Efficiency | en |
dc.subject | Frequency estimation | en |
dc.subject | High frequency HF | en |
dc.subject | High-frequency volatility estimators | en |
dc.subject | Higher order moments | en |
dc.subject | MIDAS regression model | en |
dc.subject | Mixed data samplings | en |
dc.subject | Regression analysis | en |
dc.subject | Regression estimators | en |
dc.subject | Regression model | en |
dc.subject | Risk assessment | en |
dc.subject | Volatility predictors | en |
dc.title | On the use of high frequency measures of volatility in MIDAS regressions | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1016/j.jeconom.2016.04.012 | |
dc.description.volume | 193 | |
dc.description.startingpage | 367 | |
dc.description.endingpage | 389 | |
dc.author.faculty | Σχολή Οικονομικών Επιστημών και Διοίκησης / Faculty of Economics and Management | |
dc.author.department | Τμήμα Οικονομικών / Department of Economics | |
dc.type.uhtype | Article | en |
dc.description.totalnumpages | 367-389 | |