The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
MIDAS Regressions: Further Results and New Directions
Abstract
We explore mixed data sampling (henceforth MIDAS) regression models. The regressions involve time series data sampled at different frequencies. Volatility and related processes are our prime focus, though the regression method has wider applications in macroeconomics and finance, among other areas. The regressions combine recent developments regarding estimation of volatility and a not-so-recent literature on distributed lag models. We study various lag structures to parameterize parsimoniously the regressions and relate them to existing models. We also propose several new extensions of the MIDAS framework. The paper concludes with an empirical section where we provide further evidence and new results on the risk–return trade-off. We also report empirical evidence on microstructure noise and volatility forecasting.
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Cites
Investigating causal relations by econometric models and cross-spectral methods
Granger, C. W. J. (1969) · Econometrica · doi:10.2307/1912791 · Cited by 22,989
Cited by
Stock Market Volatility and Macroeconomic Fundamentals
Engle, R. F., Ghysels, E., & Sohn, B. (2013) · Review of Economics and Statistics · doi:10.1162/rest_a_00300 · Cited by 1,117
Self-citationNHITS: Neural Hierarchical Interpolation for Time Series Forecasting
Challu, C., Olivares, K. G., Oreshkin, B. N., Garza Ramirez, F., Mergenthaler Canseco, M., & Dubrawski, A. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i6.25854 · Cited by 537
Now-Casting and the Real-Time Data Flow
Bańbura, M., Giannone, D., Modugno, M., & Reichlin, L. (2013) · Handbook of Economic Forecasting · doi:10.1016/b978-0-444-53683-9.00004-9 · Cited by 448
The impact of risk and uncertainty on expected returns☆
Anderson, E. W., Ghysels, E., & Juergens, J. L. (2009) · Journal of Financial Economics · doi:10.1016/j.jfineco.2008.11.001 · Cited by 408
Self-citationClimate policy uncertainty and world renewable energy index volatility forecasting
Liang, C., Umar, M., Ma, F., & Huynh, T. L. D. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121810 · Cited by 371
Metadata
- Authors
- Ghysels, E., Sinko, A., & Valkanov, R.
- Venue
- Econometric Reviews
- Publisher
- Informa UK Limited
- Published
- 2007-02-05
- Volume
- 26
- Issue
- 1
- Pages
- 53-90
- ISSN
- 0747-4938 (ISSN-L)
- 1532-4168
- OpenAlex
- W2053752134
- Cited by
- 1,001
- References
- 1
- FWCI
- 33.07
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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