The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Exploiting the errors: A simple approach for improved volatility forecasting
Open accessAbstract
We propose a new family of easy-to-implement realized volatility based forecasting models. The models exploit the asymptotic theory for high-frequency realized volatility estimation to improve the accuracy of the forecasts. By allowing the parameters of the models to vary explicitly with the (estimated) degree of measurement error, the models exhibit stronger persistence, and in turn generate more responsive forecasts, when the measurement error is relatively low. Implementing the new class of models for the S&P 500 equity index and the individual constituents of the Dow Jones Industrial Average, we document significant improvements in the accuracy of the resulting forecasts compared to the forecasts from some of the most popular existing models that implicitly ignore the temporal variation in the magnitude of the realized volatility measurement errors.
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Cites
Newey, W. K., & West, K. D. (1987) · Econometrica · doi:10.2307/1913610 · Cited by 16,936
A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix
Newey, W., & West, K. (1986) · National Bureau of Economic Research · doi:10.3386/t0055 · Cited by 12,278
Modeling and Forecasting Realized Volatility
Andersen, T. G., Bollerslev, T., Diebold, F. X., & Labys, P. (2003) · Econometrica · doi:10.1111/1468-0262.00418 · Cited by 3,863
Self-citationAnswering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts
Andersen, T. G., & Bollerslev, T. (1998) · International Economic Review · doi:10.2307/2527343 · Cited by 3,375
Self-citationPolitis, D. N., & Romano, J. P. (1994) · Journal of the American Statistical Association · doi:10.1080/01621459.1994.10476870 · Cited by 2,649
A Simple Approximate Long-Memory Model of Realized Volatility
Corsi, F. (2008) · Journal of Financial Econometrics · doi:10.1093/jjfinec/nbp001 · Cited by 2,495
Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
Barndorff-Nielsen, O. E., & Shephard, N. (2002) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00336 · Cited by 2,215
Power and Bipower Variation with Stochastic Volatility and Jumps
Barndorff-Nielsen, O. E. (2004) · Journal of Financial Econometrics · doi:10.1093/jjfinec/nbh001 · Cited by 2,023
A Reality Check for Data Snooping
White, H. (2000) · Econometrica · doi:10.1111/1468-0262.00152 · Cited by 1,851
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Cited by
Out‐of‐sample volatility prediction: Rolling window, expanding window, or both?
Feng, Y., Zhang, Y., & Wang, Y. (2024) · Journal of Forecasting · doi:10.1002/for.3046 · Cited by 22
Metadata
- Authors
- Bollerslev, T., Patton, A. J., & Quaedvlieg, R.
- Venue
- Journal of Econometrics
- Publisher
- Elsevier BV
- Published
- 2016-05
- Volume
- 192
- Issue
- 1
- Pages
- 1-18
- ISSN
- 0304-4076 (ISSN-L)
- OpenAlex
- W2158595111
- Cited by
- 444
- References
- 37
- FWCI
- 51.17
- Type
- journal article
- Language
- en
- Open access
- green
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